{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "BRICS QUERY TOOL APPLICATION PROGRAMMING INTERFACE" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Purpose: \n", "### The purpose of this notebook is to provide examples of the different endpoints for the Query Tool API using Python. \n", "\n", "### For More Information regarding Query-API endpoints please see \n", "FITBIR: https://fitbir.nih.gov/gateway/query-api/swagger-ui/index.html
\n", "PDBP: https://pdbp.ninds.nih.gov/gateway/query-api/swagger-ui/index.html
\n", "NEI: https://brics.nei.nih.gov/gateway/query-api/swagger-ui/index.html
\n", "CdRns: https://cdrns.nih.gov/gateway/query-api/swagger-ui/index.html
\n", "\n", "### For additional questions, please refer to the PDF API User Guide and additional Demo Jupyter Notebooks\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Instructions:\n", " 1. Import the Python Dependencies. \n", " 2. Authenticate user permissions and retrieve access token.\n", " 3. Create and send a query for the specific endpoint.\n", " - If the response 200, it means that the query was submitted successfully. For more information about the status codes please refer to this link: https://httpstatuses.com/\n", " 4. Save the data in a dataframe or in folder to perform analysis. \n", " \n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Table of contents\n", "- [I) Set BRICs Instance ](#I)\n", "- [II) Authentication](#II)\n", "- [III) Study API (Get Studies)](#III)\n", " - [A) Get all Study Information](#IIIA)\n", " - [B) Get Study Information for one study](#IIIB)\n", " - [C) Get All Studies Associated With a Form Structure](#IIIC)\n", "- [IV) Form Structure API (Get Forms)](#IV)\n", " - [A) Get Form Structures for a Study](#IVA)\n", "- [V) Data Element API (Get Data Elements)](#V)\n", " - [A) Get Data Elements from a Form Structure](#VA)\n", "- [VI) Data API (Get Data Stored in the Form Structures)](#VI)\n", " - [A) Get data from multiple form structures without doing joins](#VIA)\n", " - [B) Return data with a filter](#B)\n", " - [i) Output CSV Format](#Bi)\n", " - [ii)Output JSON Format](#Bii)" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "#Import Python Dependencies\n", "import pandas as pd\n", "import requests\n", "import json\n", "import getpass\n", "from io import StringIO\n", "import os\n", "import datetime as dt\n", "import time\n", "import sys" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "New Directory Created: C:\\Users\\bagonismm\\Desktop\\Coding\\api-development\\QueryToolandAPIPresentation_04112024\\UserGuides\\BRICsQueryTool_2024_04_10_outputfiles\n" ] } ], "source": [ "# define function for automatically creating an output folder \n", "def create_folder(folder_path):\n", " adjusted_folder_path = folder_path\n", " folder_found = os.path.isdir(adjusted_folder_path)\n", " counter = 0\n", " while folder_found == True:\n", " counter = counter + 1\n", " adjusted_folder_path = folder_path + ' (' + str(counter) + ')'\n", " folder_found = os.path.isdir(adjusted_folder_path)\n", " os.mkdir(adjusted_folder_path)\n", " return adjusted_folder_path\n", "\n", "x=dt.datetime.now()\n", "new_dir = os.getcwd()+'\\\\'+\"BRICsQueryTool_\"+x.strftime('%Y_%m_%d')+\"_outputfiles\"\n", "created_dir = create_folder(new_dir)\n", "print('New Directory Created: ' + new_dir)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Set BRICs Instance \n", "**Note the Query-API is designed similarly for all BRICs instances**:\n", "Endpoint names will be identical except for the name of the BRICs Instance
\n", "
\n", "**BRICs Instances:**
\n", "**FITBIR:**'fitbir.nih.gov'
\n", "**PDBP:** 'pdbp.ninds.nih.gov'
\n", "**NEI:** 'brics.nei.nih.gov'
\n", "**CDRNS:** 'cdrns.nih.gov'
\n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# Set BRICs Instance. Below examples are for 'fitbir.nih.gov'. However, the user can use the below code for any \n", "# BRICs instance for which the user has access (see available instances listed above). Just set that variable here.\n", "BRICSInstance = 'fitbir.nih.gov'" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Authentication " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To access the Query Tool API the user needs to provide an authentication 'token' in the header of each API request. This token is found by logging on to the user's BRICs account (FITBIR etc) and going to the 'Account Management' tab. Here you will be able to cut and paste the token and set it as a variable (See Below) \n" ] }, { "attachments": { "image.png": { "image/png": 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" } }, "cell_type": "markdown", "metadata": {}, "source": [ "\n", "![image.png](attachment:image.png)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Enter your user token:········\n" ] } ], "source": [ "#Set Input token: Tokens can be obtained by logging into your FITBIR repository account and clicking on Account Management tab\n", "\n", "#token = maskpass.askpass(prompt=\"Enter your user token\")\n", "token = getpass.getpass('Enter your user token:')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Study API \n", "\n", "## The Study APIs return the following information:\n", "1. Studies with data that the user has access to\n", "2. Information about the a study or studies.\n", "3. Studies associated with a form structure" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## GET ALL STUDY INFORMATION \n", "### This service will return all the studies that have data in the instance. Optional it will return information for a study with the Prefix ID (Study ID) provided.
\n", "See Swagger UI: https://fitbir.nih.gov/gateway/query-api/swagger-ui/index.html#/study/getStudies for more information regarding this endpoint" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "#get study prefix from title\n", "url = \"https://\" + BRICSInstance + \"/gateway/query-api/study\"\n", "\n", "headers = {\n", " 'accept': 'application/json',\n", " 'Content-type': 'application/json',\n", " 'Authorization':'Bearer ' + token \n", "}\n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query = requests.get(url,headers =headers)\n", "query\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Output: JSON\n", "The user will receive the following information in a JSON format:\n", "1. Study Abstract\n", "2. Study Status\n", "3. Study Prefix ID\n", "4. Study Title\n", "5. Principal Investigator" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[{'abstract': 'Every year 1.7 million people sustain a traumatic brain injury (TBI) in the US and of these, 84% are considered mild TBI (mTBI). Although imbalance is one of the most common and debilitating complaints after mTBI, we currently lack clear guidelines on when to initiate rehabilitation and it is unclear if early physical therapy is beneficial. Additionally, while wearable sensor data is not currently used in the clinic to assess or treat balance after mTBI, such technology may improve outcomes. Our research aligns directly with focus areas in JPC-8/CRMRP since we will study people with mTBI who also have complex, multisensory system impairments and complaints of imbalance. This call encourages studies of patients with dizziness and visual dysfunction that are slow to respond to current treatments. Our project also aligns with FY 16 PH/TBIRP CTRRA areas of encouragement for â\\x80\\x98interventional studies to evaluate emerging or existing rehabilitation strategies for the treatment of patients with complex TBI compared to existing standards of care.â\\x80\\x99 Our Phase 2 interventional study also addresses the interest in comorbidities (i.e. central sensory integration and/or peripheral vestibular dysfunction) that may be refractory to treatment. Our project includes a multidisciplinary team with an academic institution Oregon Health & Science university (OHSU) partnering with industry (APDM) in an effort to improve rehabilitation after mTBI. Our central hypothesis is that rehabilitation after mTBI is suboptimal due to late initiation of and inadequate performance of exercises that do not adequately challenge vestibular and sensory integration function. Our preliminary results show physical rehabilitation is initiated late (approximately 70 days post injury) and that individuals with mTBI have altered central sensorimotor integration and do not optimally perform balance exercises. We believe that wearable sensor technology could facilitate rehabilitation by monitoring the compliance and quality of balance exercises. There are 3 Aims of this proposal; Aim I. Early Intervention: To determine the effects of early vs late (standard of care) rehabilitation for balance deficits in mTBI; Aim II. Home Monitoring: To compare traditional balance rehabilitation versus balance rehabilitation with sensor-based home monitoring of the compliance and quality of prescribed exercises; Aim III. Real-time monitoring: To develop and evaluate a novel, wearable sensor system to provide real-time feedback to physical therapists on head and trunk movement during training of balance and vestibular exercises.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000381',\n", " 'title': 'Sensory Integration Balance Deficits in Complex mTBI: Can Early Initiation of Rehabilitation with Wearable Sensor Technology Improve Outcomes?',\n", " 'pi': 'Laurie King',\n", " 'fundingAmount': 4652120.0},\n", " {'abstract': 'Traumatic brain injury (TBI) and post-traumatic headache (PTH) are common conditions that exert substantial impacts in the military and in the civilian population. TBI is a signature injury of U.S. Soldiers during modern warfare with 20% of Operation Enduring Freedom and Operation Iraqi Freedom Veterans having experienced TBI, 75% of which are mild TBI (mTBI). In addition, approximately 1.7 million American civilians seek medical attention each year for TBI and there are 1.6-3.8 million sports-related mTBIs annually. Headache is the most common symptom following mTBI, with estimates of headache prevalence following mTBI as high as 90%. PTH is often persistent (i.e., endures for >3 months following the injury), with about 66% of people with mTBI reporting continued headaches at 3 months post-injury. Although progress has been achieved in understanding PTH epidemiology, there are significant shortcomings in the description of PTH mechanisms, diagnosis, and treatment. A major challenge for the investigation, diagnosis, and treatment of PTH is the inability to accurately diagnose persistent post-traumatic headache (PPTH) attributed to mTBI and to reliably differentiate PPTH attributed to mTBI from chronic migraine (CM). Rationale: It is often impossible to clinically differentiate the patient who had an exacerbation of their underlying migraine pattern following TBI, from the patient who had a new onset of migraine following TBI, from the patient with true PPTH. According to International Classification of Headache Disorders diagnostic criteria, the only evidence for headache being attributable to a preceding head injury is that the headache begins within 7 days of the injury. However, a substantial proportion of military PTH starts after a longer interval (up to 60% of cases), the majority of PPTH is phenotypically indistinguishable from CM according to information typically collected in the clinical setting (60%-97%), and many Soldiers and civilians with presumed PPTH have a personal history of migraine preceding the mTBI. Thus, it is commonly challenging to differentiate PPTH from CM in the clinical setting. The inability to accurately diagnose PPTH attributed to mTBI and differentiate it from CM has substantial negative implications on patient care and the ability to conduct meaningful research on PPTH.Objective: The objective of this study is to use machine-learning algorithms to construct multivariate models of structural and functional imaging data and patient symptoms that accurately diagnose PPTH attributed to mTBI and differentiate it from CM.Study Design: Functional and structural magnetic resonance imaging (MRI) data and patient symptoms will be used to build and test automated diagnostic models that most accurately diagnose PPTH attributed to mTBI and differentiate it from CM. This investigation uses MRI sequences that could easily be employed during the clinical investigation of patients, without adding risk to the patient, without the need for contrast administration, and with little additional financial burden.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000323',\n", " 'title': 'A Magnetic Resonance Imaging Based Classifier to Accurately Diagnose Persistent Post-Traumatic Headache and to Differentiate it from Chronic Migraine',\n", " 'pi': 'Todd Schwedt',\n", " 'fundingAmount': 1570260.0},\n", " {'abstract': 'TBI severity in the context of a closed head injury can be difficult to diagnose. There is a need for rapid triage of closed head injuries to identify the requirement for a higher level of care as well as monitor for a worsening condition in the field. A field medic has limited capability and may currently only be able to use subjective symptomatic or clinical signs which are often inaccurate and cannot assess complications such as life threatening increases in intracranial pressure (ICP) or other severe cerebral hemodynamic impairments.\\r\\n\\r\\nClinically, ICP is a fundamental physiologic parameter that, if elevated, can lead to a pathological reduction in cerebral blood flow and possible herniation of the brain, resulting in irreversible brain damage or death if left untreated. Current state-of-the-art assessment of non-penetrating TBI is limited to advanced imaging (CT and MRI), invasive monitoring devices (i.e. invasive ICP monitors), or ineffective clinical tools that lack accuracy, are not portable, have long assessment time, or do not have a direct physiological basis. Furthermore, many of these technologies require highly trained specialists to administer and interpret, resulting in a critical need for a comprehensive diagnostic and assessment technology for TBI.\\r\\n\\r\\nPrevious work has shown that life threatening ICP elevation after TBI can be diagnosed with a portable and non-invasive transcranial Doppler (TCD) system. The purpose of this study is to collect high-quality cerebral blood flow velocity (CBFV) measurements using TCD to develop an algorithmic framework to determine correlation to and estimates intracranial pressure when measured with invasive monitoring.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000401',\n", " 'title': 'A Prospective Non-Invasive Study of Cerebral Blood Flow Velocity Morphology for Quantification of Intracranial Pressure (ICP)',\n", " 'pi': 'Robert Hamilton',\n", " 'fundingAmount': 1482840.0},\n", " {'abstract': 'There is substantial variation in recovery after pediatric traumatic brain injury (TBI). If we could understand the underpinnings behind this variation, then treatments could be optimized to reduce the profound negative societal and economic impact associated with pediatric TBI. Predictors of recovery following TBI, particularly the roles of genes and environment, are incompletely understood. Elucidation of genetic and environmental influences on recovery after pediatric TBI is critically needed to advance development of precision medicine strategies. Novel systems biology analyses conducted by our group indicate genetic factors within two main biologic processes, response to injury (cell proliferation, cell death, inflammatory response, cellular metabolism) and neurocognitive and behavioral reserve (neurodevelopment, cognition, and behavior), are likely associated with recovery after TBI. An approach that seeks to identify genes and variants over-represented (gene-enrichment) across these biologic processes would improve upon prior candidate gene approaches. Genetic variants implicated in recovery after TBI interact with home and family environmental factors to influence cognitive and behavioral outcomes in other pediatric populations; however, the effects of the interaction between genes and environment on recovery after pediatric TBI have not been explored. The objective of this proposal is to understand the interplay between genetically influenced biologic processes and environment with respect to recovery after pediatric TBI. We hypothesize that genetic variants overrepresented in biologic processes important to TBI recovery will be associated with global, neurocognitive, and neurobehavioral functioning and that environmental factors will interact with genetic factors to influence recovery after severe pediatric TBI. We will collect salivary DNA samples from approximately 338 children participating in the Approaches and Decisions in Acute Pediatric TBI Trial (ADAPT, U01 NS081041). The primary outcome will be global functioning assessed by the pediatric Glasgow Outcome Scale-Extended (GOSE) at 3, 6, and 12 months post injury and secondary outcomes will include a comprehensive assessment of cognitive and behavioral functioning at 12 months post injury. We will use an analytic approach that seeks to identify genes and variants associated with recovery that are over-represented (gene-enrichment) across response to injury and neurocognitive and behavioral reserve biologic processes. Mixed model analyses will be used to evaluate the association of genotypes with recovery after severe pediatric TBI and to elucidate the association of environmental factors (family functioning, parenting practices, home environment, and socioeconomic status) with recovery. How genetic and environmental factors and genetic and early clinical factors interact to influence recovery after severe pediatric TBI will also be evaluated. This project will provide critically needed information to inform individualization of prognosis and development of novel, precision medicine approaches for pediatric TBI, which are considerably lacking for this population.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000351',\n", " 'title': 'ADAPT Sub-study: Genetic and environmental influences on recovery of severe pediatric brain injury',\n", " 'pi': 'Brad Kurowski',\n", " 'fundingAmount': 267558.0},\n", " {'abstract': 'Severe traumatic brain injury (TBI) is the leading cause of death and long-term disabilities in children, yet there remains a critical need for accurate markers of outcome in these patients. Identification of improved MRI markers of long-term neurocognitive outcome will improve clinical prognostication after an injury and help to direct and monitor rehabilitation strategies. Recent advances in neuroimaging have elucidated the existence of large-scale brain networks responsible for distinct cognitive and psychological functions. A network-based framework for TBI-induced cognitive dysfunction is a novel paradigm for investigating hypotheses regarding the relationship between patient-specific injury patterns and neurocognitive outcomes. Using this framework, this study will identify early imaging predictors of global and specific neuropsychological functions after severe pediatric TBI. In addition, the study will investigate the association between late MRI markers of brain network dysfunction and impairments in commonly affected cognitive domains (executive function, memory, and internalizing behavior). The project will leverage an ongoing, multi-center study of severe pediatric TBI to enable this large neuroimaging study with the following three aims: Aim 1: Test whether the severity and location of white and gray matter injuries identified on MRI early after injury independently predict functional and neurocognitive outcomes one year after severe pediatric TBI. Acute MRI scans will be assessed using standardized common data element (CDE) definitions, and MRI measures predictive of global and domain- specific cognitive outcomes will be determined. Aim 2: Test whether global or regional cerebral atrophy at one year post-injury is related to neurocognitive and behavioral impairments after TBI. Global and regional volumetrics will be determined from structural MRI scans, and correlated with neuropsychological testing measures of function in each cognitive domain. Aim 3: Test whether TBI-induced alterations in white matter microstructure and functional network connectivity are related to impairments in cognition and psychological functioning. Diffusion tensor imaging (DTI) and resting state functional MRI (rfMRI) will be used to investigate the relationship between damage to specific brain networks and neurocognitive function. Successful completion of this project will determine clinically useful MRI markers of neurocognitive outcome and will provide new information on the relationship between brain network dysfunction and cognitive impairments after TBI. Identifying early imaging predictors and late imaging markers of specific neuropsychological impairments would be a major advancement, providing new tools for directing rehabilitation strategies towards at-risk cognitive domains, and thereby improving long-term function and quality of life in this vulnerable population.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000346',\n", " 'title': 'ADAPT Sub-study: MRI Markers of Functional Outcome after Severe Pediatric Traumatic Brain Injury',\n", " 'pi': 'Peter A Ferrazzano, MD',\n", " 'fundingAmount': 588410.0},\n", " {'abstract': 'Traumatic brain injury (TBI) in older adults is common, accounting for over 25% of brain injuries in the US each year, with considerable mortality, long-term impairment and disability. Outcomes among older adults with TBI are disparately worse when compared to their younger counterparts with similar injuries. Clinical efforts to treat TBI in older adults have not yielded the expected improvements in physical impairment, disability and health- related quality of life. A critical barrier to the management of TBI is that there is limited knowledge about potential differences in the response to TBI that results from aging, and how older age may affect pathology and recovery following TBI. The current application proposes to use a novel set of immune biomarkers to enhance knowledge of the trajectory of recovery from TBI and the underlying mechanisms responsible for chronic symptoms, impairment and decrements in health-related quality of life in older adults following TBI. We propose that aging is a biological factor that contributes to the pathological response to injury by modulating the immune response to TBI and will test this hypothesis using a novel model of impairment and disability. The aims of this prospective cohort study are to: 1) Compare cellular immune responses, plasma inflammatory biomarker concentrations, and measures of impairments, disability and health-related quality of life up to 6 months post-injury in young and older adults with and without mild TBI (75 per group) and 2) Determine the association between selected cellular immune and plasma biomarkers and impairments, disability and health- related quality of life at 3 and 6 months post-injury in older adults with mild TBI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000266',\n", " 'title': 'AIM: TBI Impact of Aging on the Immune Response to Traumatic Brain Injury',\n", " 'pi': 'Hilaire J Thompson',\n", " 'fundingAmount': 555511.0},\n", " {'abstract': ' Traumatic brain injury (TBI) is a major cause of death and disability. In the United States alone approximately 1.4 million people sustain a TBI each year, of which 50,000 people die and over 200,000 are hospitalized. In addition, new research suggests that TBI is an independent significant risk factor of developing dementia and Alzheimer\\'s disease. Despite the scientific and cost benefits of cross-study analyses, variability in measurement across studies has limited the ability to combine TBI data. To address this, the Federal Interagency TBI Research (FITBIR) Informatics System was developed as a platform to define, refine, and standardize data definitions for performing cross-study TBI research and as a central repository for phenotypic, genomic, and imaging data from TBI studies. The goal of this proposed work is to accelerate the process of building FITBIR into a large, rich database for meta- and secondary analysis of TBI clinical research data by archiving legacy data from the Citicoline Brain Injury Treatment Trial (COBRIT). COBRIT is a randomized, double-blind, placebo- controlled, multicenter trial studying the effects of 90 days of Citicoline on improving functional outcome in patients with complicated mild, moderate, and severe TBI. A comprehensive TBI assessment and drug test data were collected using 43 Case Report Forms (CRFs) in 16 modules containing more than 1,600 variables from approximately 1,200 patients over a 4 year period across eight clinical sites. The archiving of COBRIT in a standardized and harmonized format will help TBI investigators perform cross-study analyses about the natural history of TBI and the feasibility of new TBI therapeutics. Specifically, we will standardize and harmonize COBRIT variables using FITBIR Common Data Elements (CDEs) and Unique Data Elements (UDEs) by (1) assigning CDEs/UDEs to COBRIT variables that are \\\\\"Identical\\\\\" to FITBIR CDEs/UDEs; (2) defining and annotating COBRIT variables that are \\\\\"Comparable\\\\\" to FITBIR CDE/UDE; (3) defining and harmonizing COBRIT variables that are \\\\\"Related\\\\\" to FITBIR CDE/UDEs; and (4) Creating new data elements for COBRIT variables not found in FITBIR CDEs/UDEs. Next, we will contribute the standardized and harmonized COBRIT data to FITBIR by (1) generating FITBIR Global Unique Identifiers (GUID) for COBRIT subjects; (2) validating data formats using the FITBIR Data Validation Tool; and (3) submitting standardized and harmonized COBRIT data using the FITBIR Upload Tool. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000240',\n", " 'title': 'Adding Legacy Clinical Data to the Federal Interagency Traumatic Brain Injury: Citicoline Brain Injury Treatment Trial (COBRIT)',\n", " 'pi': 'Ross Zafonte, DO',\n", " 'fundingAmount': 146586.0},\n", " {'abstract': 'The Child Health After Injury (CHAI) study was funded by the CDC (9/2006 to 8/2012) to determine the population-based rates of disability after traumatic brain injury (TBI) to children and adolescents. This study was one of the largest prospective longitudinal studies on pediatric TBI, had outstanding follow-up over three years, included controls, provided a comprehensive examination of functional outcomes after TBI and collected a wealth of clean and validated data. These high quality data are currently available to be entered into the Federal Interagency Traumatic Brain Injury Research (FITBIR) database and combined with other existing or future pediatric data to advance the field of pediatric TBI research. There are still a number of questions which could be explored using these legacy data in combination with other pediatric TBI data to be entered into FITBIR. Specifically, the legacy CHAI data would be available for use to study: 1. Effects of treatment on 1, 2 and 3 year outcomes after moderate or severe TBI 2. Effects of TBI and its treatment on school outcomes 3. Comparison of adolescent reported functional outcomes after pediatric TBI to parent reported outcomes 4. Comparison of outcomes after TBI in children < 5 years due to abuse with that due to unintentional mechanisms 5. Comparison of outcomes after TBI in children at different ages as well as to adults.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000230',\n", " 'title': 'Addition of Pediatric TBI Data to FITBIR: Child Health After Injury (CHAI) study',\n", " 'pi': 'Frederick P Rivara, MD, MPH',\n", " 'fundingAmount': 153500.0},\n", " {'abstract': 'Uploading legacy clinical neuroimaging and neuropsych data from the National Intrepid Center of Excellence to FITBIR: This project establishes an accessible centralized location for legacy neuroimaging, neuropsychiatric, self-reported and demographics data from a unique military TBI population, establishing a methodology for continued data submission to FITBIR.\\r\\n\\r\\nThe National Intrepid Center of Excellence (NICoE) is an institute that generates clinical knowledge, improves diagnosis and advances treatment related to the pathophysiological and natural history of comorbid mild traumatic brain injury and psychological health conditions.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000234',\n", " 'title': 'Advanced Imaging Acquisition and Data Analysis for a Military TBI Neuroimaging Database at NICoE',\n", " 'pi': 'John M Ollinger, DSc',\n", " 'fundingAmount': 5724880.0},\n", " {'abstract': 'The purpose of the proposed study is to evaluate a new method to quantify cerebral hemodynamic dysfunction following mild traumatic brain injury (mild TBI). The investigators of this study will assess the cerebrovascular reactivity (CVR) of individuals who have sustained a clinically verified mild TBI using a newly developed transcranial Doppler ultrasonography (TCD) analysis platform, called quantitative Cerebral Hemodynamics (qCH). This platform was recently used in a NIH funded (1R43NS092209-01) study which demonstrated significant cerebral hemodynamic impairment following sports related concussion in high school athletes.1 This study looks to expand on previous work by comparing cerebral hemodynamic impairment measured using qCH (ultrasound) to clinical evaluations and magnetic resonance imaging (MRI) techniques. Findings from this study may lead to improved mild TBI care and management by enabling the development of a software product that will simplify brain health assessment and provide objective, physiological relevant information for the diagnosis of mild TBI and Return-to-Play (RTP) determination. Reliable diagnosis and proper management is vital to managing the often-serious short and long-term sequelae resulting from mild TBI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000377',\n", " 'title': 'Advanced morphological analysis of cerebral blood flow for acute concussion diagnosis and return-to-play determination',\n", " 'pi': 'Robert Hamilton, PhD',\n", " 'fundingAmount': 1500000.0},\n", " {'abstract': 'The development of symptomatic Alzheimerâ\\x80\\x99s disease (AD) in older adults is a protracted and heterogeneous process that may be exacerbated or influenced by environmental risk factors. Recent evidence suggests that mild traumatic brain injury (mTBI) may have differential effects on clinical outcomes when sustained in late-life relative to early life, and may not only accelerate the aging process, but also impact immune cascades and AD pathogenesis. Despite considerable interest in the biological connections between aging, mTBI, and AD, there is a dearth of prospective research on the pathophysiological processes that may underlie these associations. In order to develop preventative or acute therapies that minimize the impact of mTBI on negative aging trajectories, it is important to disentangle the relative contributions of mTBI, immune dysregulation, and AD-related pathology on longitudinal neuroanatomical and cognitive outcomes in older adults.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000408',\n", " 'title': 'An investigation of immune biology and Alzheimers Disease-related biomarkers in asymptomatic, late life mild TBI',\n", " 'pi': 'Brianne Bettcher, PhD ABPPCN',\n", " 'fundingAmount': 777499.0},\n", " {'abstract': 'Traumatic brain injury (TBI) is the leading killer of children with over 7000 deaths reported in the US in 2005. In addition to this loss of life, the yearly costs of TBI on the health and welfare of children in the US is over $2 billion for acute care along and more than a million life-years are potentially at risk. Advances in care for children with severe TBI have been disappointingly slow. Randomized controlled trials (RCTs) of novel therapeutic agents and approaches have universally failed when applied in multiple centers. Evidenced-based guidelines are not sufficiently robust to generate meaningful recommendations because the literature has failed to demonstrate best practices for most aspects of TBI care. Variations in practices such as intracranial hypertension control, mitigation of secondary insults and metabolic support are substantial in contemporary clinical practice, leading to wide variations in patient outcomes and may ultimately overwhelm treatment effects that might be observed in a well-designed RCT. We propose an observational cohort study of 1000 children with severe TBI to compare the effectiveness of pediatric TBI therapies within an international consortium from the US, UK and EU. We will test 3 specific aims that encompass a total of 6 TBI therapies - (i) intracranial hypertension strategies - cerebrospinal fluid diversion and hyperosmolar therapies; (ii) secondary insult detection - prophylactic hyperventilation and brain tissue oxygen monitoring (PbO2); (iii) metabolic support - nutritional support and glucose management. Several statistical approaches, often used in comparative effectiveness research (CER) to control for confounders, will be employed including propensity score adjustments, regression analyses and novel statistical modeling. Successful completion of this proposal would provide compelling evidence to change clinical practices, provide evidence for several new recommendations for future guidelines and lead to improved research protocols that would be limit variability in TBI treatments - helping children immediately through better clinical practices and ultimately through more effective investigation.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000231',\n", " 'title': 'Approaches and Decisions in Acute Pediatric TBI Trial (ADAPT)',\n", " 'pi': 'Stephen Wisniewski, PhD',\n", " 'fundingAmount': 2886330.0},\n", " {'abstract': 'We plan to create biomarker panels to use as a tool in the precision medicine approach to tailoring the treatment and recovery of individuals with TBI. We will collect functional, behavioral, and neuropsychological outcomes at 3, 9, and 24+ months after injury (up to year 10 post-injury). Home visits and/or clinic appointments are conducted at 3 & 9 months, and an additional neuropsychological assessment will be conducted at the long-term follow up point.\\r\\n\\r\\nThe University of Pittsburgh will be responsible for recruitment of subjects in the chronic phase of TBI (months to years post-injury) as part of a greater body of work and collaboration with SUNY Downstate Medical Center, Baylor College, Malcolm Randall VA Medical Center Gainesville, and the University of Florida, who will be responsible for recruitment at the acute admission phase (<72 hours post-injury), and subacute phase (>72 hrs to 2 weeks post-injury).',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000396',\n", " 'title': 'Biomarker-Based Precision Medicine Approach to Traumatic Brain Injury Subphenotypes',\n", " 'pi': 'Richard Rubenstein',\n", " 'fundingAmount': 4444380.0},\n", " {'abstract': 'We propose to develop a quantitative model of the biomechanical basis of mild traumatic brain injury (MTBI) for a pediatric population. This expands upon our initial five year Bioengineering Research Partnership (BRP) in which we developed a biomechanical model of MTBI for a collegiate population, which has resulted in a database of more than 500,000 recorded head impacts in collegiate sports. This work has produced substantial advancements in the knowledge of injury mechanisms and head impact exposure, and resulted in translational outcomes, including: 1) adult brain injury criteria that provide improved diagnosis strategies and prevention systems, 2) optimized helmet design criteria and publically available helmet evaluations that have improved helmet technologies, and 3) football practice guidelines that have reduced head impact exposure in collegiate football. The proposed pediatric MTBI model will enable translational research and the development of new clinical and therapeutic approaches to reduce the incidence and negative effects of MTBI in youth athletes. Experimental and clinical projects among our team members will allow us to test hypotheses specific to the underlying pathomechanics and clinical sequelae of pediatric MTBI. A cohort of 1050 youth football players between the ages of 6 and 14 years will wear instrumented helmets to collect head acceleration data and clinical data over a 5 year period. Athletic environments offer a rich opportunity for collecting data on large numbers of head impacts, which enables research that combines biomechanical head impact data with the subsequent neurobiologic and functional changes in the brain. To date, biomechanical MTBI research has focused primarily on the approximately 100,000 athletes participating in college and professional football in the United States; however, little is known about the 3,500,000 youth (6 years to 14 years) athletes playing football each year. We hypothesize that head acceleration due to impact is predictive of the type and severity of brain injury, and correlates t specific clinical measures of pediatric MTBI. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000274',\n", " 'title': 'Biomechanical Basis of Pediatric mTBI Due to Sports Related Concussion',\n", " 'pi': 'Stefan Duma, PhD',\n", " 'fundingAmount': 712180.0},\n", " {'abstract': 'The goal of this project is to define the biomarker profile of TBI-associated CI in veterans and compare it to that of veterans with AD and to age-matched controls. Our overall hypothesis is that TBI-associated CI involves a unique biomarker profile that has features distinguishable from AD and normal aging. Specifically, we hypothesize that: 1) patients with TBI associated CI will have higher phospho-tau/total tau ratio than controls who have not had a TBI, and that 2) TBI-associated CI will be associated with elevations in inflammatory markers compared to controls and 3) a decrease in b-amyloid measures compared to controls but not as low as in the setting of AD. This study will refine our understanding of the underlying mechanisms in TBI-associated CI, help predict who is at greatest risk of developing CI in veterans with TBI, and identify who may benefit from interventions and treatment for CI and its prevention.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000334',\n", " 'title': 'Blood Biomarker Profile of TBI-Associated Cognitive Impairment Among Old and Young Veterans',\n", " 'pi': 'Kristine Yaffe, M.D.',\n", " 'fundingAmount': 593534.0},\n", " {'abstract': 'A multicenter, randomized, blinded-endpoint, comparative effectiveness study of goal-directed critical care based upon monitoring of brain tissue oxygen and intracranial pressure versus monitoring of intracranial pressure alone in patients with severe traumatic brain injury.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000382',\n", " 'title': 'Brain Oxygen Optimization in Severe Traumatic Brain Injury - Phase 3 (BOOST-3)',\n", " 'pi': 'Ramon Diaz-Arrastia, MD',\n", " 'fundingAmount': 2742530.0},\n", " {'abstract': 'Sleep disruption of one of the most common complaints in patients suffering from traumatic brain injuries and is associated with poorer outcome. It has been suggested that mTBI might produce alterations of the normal circadian rhythm, leading to delayed sleep phase syndrome and irregular sleep-wake patterns. A particularly promising non-pharmacologic approach that shows potential in improving/modifying abnormalities of the circadian rhythm and sleep-wake schedule is bright light therapy, particularly within the blue-wavelength spectrum. Presently, no published studies have examined the effects of bright or blue-enriched light therapy on outcome in mTBI patients. For the proposed investigation, we hypothesize that blue wavelength light therapy may be helpful in improving the sleep of patients with a recent history of mTBI and may also have other mood elevating effects, both of which should promote positive treatment outcome in these individuals. We propose that direct intervention to improve the sleep difficulties in mTBI via blue light therapy may lead to entrainment of the circadian rhythm, improved sleep, and enhancement of daytime alertness. These improvements are predicted to lead to improved emotional regulation, neurocognitive performance, and accelerated improvement in symptoms among patients with mTBI.\\r\\n\\r\\nThe primary aims of the proposed study are to examine the effectiveness of an six-week course of morning blue light therapy (MBLT) on objective and subjective measures of sleep, emotional functioning, mood, psychiatric symptom expression, and neuropsychological assessment using the most current version of the Automated Neuropsychological Assessment Metric (ANAM4) TBI battery. In addition, changes in behavioral functioning produced by MBLT will also be correlated with changes in Blood Oxygen Level Dependent (BOLD) functional magnetic resonance imaging (fMRI) during an executive control task, a virtual reality water-maze task that assesses hippocampal memory function, and a working memory n-back task. These tasks have been used extensively in our laboratory and provide excellent resolution for evaluating functional changes within the target regions of the anterior cingulate gyrus, hippocampus, and prefrontal cortex. Furthermore, the proposed project will directly assess sleep functioning using actigraphy and correlate these changes in sleep with pre-to post-treatment changes in neurocognitive performance and symptom presentation, as well as functional activity changes.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000242',\n", " 'title': 'Bright Light Therapy for Treatment of Sleep Problems Following Mild TBI',\n", " 'pi': 'William D Killgore, PhD',\n", " 'fundingAmount': 1853910.0},\n", " {'abstract': 'PROJECT SUMMARY/ABSTRACT â\\x80\\x93 Research Project Concussion or mild traumatic brain injury (mTBI) is the most common type of acquired brain injury in children and adolescents. While the majority of youth with concussion recover within 2-4 weeks, a substantial subset (15-30%) take longer to recover and develop persistent post-concussive symptoms (PPCS). This group experiences worse function, more pain and seeks a greater amount of medical assessments and treatments. Prolonged impairments in early and middle adolescents (EMA) can result in changes in developmental trajectory and long-term disability. There is no single agreed upon definition for PPCS and predictive algorithms are largely based on nonspecific subjective clinical symptoms. Furthermore, there are currently no good preventive strategies or targeted treatments. It is a major public health challenge to develop objective biological markers that better predict PPCS, which will provide the opportunity for improved prognostication, potential preventive interventions and new therapeutics based on underlying biological mechanisms. It is the central goal of this CARE4Kids Center Without Walls to discover objective autonomic, imaging and blood-based biomarkers that, when integrated with neuropsychological and neurological signs and symptoms, will optimally predict PPCS in EMA. Once identified, these biomarkers and clinical measures will then be validated in a more generalized group and developed into an improved predictive algorithm for PPCS. The linkage of objective biological measures to different clinical phenotypes (termed endophenotypes in this application) will provide a mechanistic understanding of different types of PPCS. It is hypothesized that endophenotypes may share pathobiology with migraine, dysautonomia, anxiety, depression or other symptoms commonly seen in those with PPCS. By understanding the underlying neurobiology of PPCS, it will become possible to develop mechanism- based prevention or treatment measures.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000437',\n", " 'title': 'CARE4Kids',\n", " 'pi': 'Chris Giza',\n", " 'fundingAmount': 1785930.0},\n", " {'abstract': 'This is a prospective case-controlled study designed to determine: (1) the effect of otolith dysfunction, and (2) the interaction between otolith dysfunction and mTBI/blast on balance, gait, and quality of life. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000265',\n", " 'title': 'CENC Study 08: Otolith Dysfunction and Postural Stability',\n", " 'pi': 'Faith Akin, PhD',\n", " 'fundingAmount': 37175000.0},\n", " {'abstract': \"This study's overall goal is to establish a large, longitudinal cohort of former U.S. OEF/OIF/OND combatants, including those exposed and unexposed to mTBI(s), and measure their chronic sequelae and comorbidities. All subjects will undergo an initial comprehensive assessment to determine their TBI status along with the prevalence, type, and intensity of chronic sequelae from TBI and associated comorbidities. All subjects will undergo periodic in-person and telephone reassessment to monitor the status of the sequelae and comorbidities and to assess for evidence of neurologic (cognitive, behavioral, physical) decline.\",\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000263',\n", " 'title': 'CENC Study 1: Observational Study on Late Neurologic Effects of OEF OIF OND Combat',\n", " 'pi': 'William Walker, MD',\n", " 'fundingAmount': 37175000.0},\n", " {'abstract': 'Traditional structural neuroimaging techniques are largely insensitive to the subtle damage resulting from mTBI and DTI represents a substantial improvement over structural imaging in its ability to detect subtle white matter changes following mTBI. This proposal will utilize a novel imaging sequence, mcDESPOT, to specifically calculate myelin volume in vivo in a sample of Veterans with mTBI, PTSD, or both, as well as controls. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000330',\n", " 'title': 'CENC Study 20: Novel White Matter Imaging to Improve Diagnosis of Mild TBI',\n", " 'pi': 'Amy Jak',\n", " 'fundingAmount': 37175000.0},\n", " {'abstract': 'Traumatic brain injury (TBI) affects approximately 3.5 million individuals annually in the United States and approximately 75% are the result of \\\\\"mild\\\\\" or concussive events. In the US military, it is estimated that roughly 20% of the deployed force suffered a head injury in the wars in Iraq and Afghanistan, 83.3% of whom endured a mild, uncomplicated TBI or concussion, the long-term impact of which is just beginning to be appreciated. Many of these Service members are young males, 20-30 years old who have decades of life to live with the complex and often debilitating impact of war-time brain injury. Although much effort has been placed on trying to better understand this type of injury, many of these studies have been forced to rely largely on self-reporting, retrospective medical records review or evaluations of only later stages of injury No study to date has prospectively followed active-duty US military from concussive brain injury to long-term outcome with advanced Magnetic Resonance Imaging (MRI) and clinical evaluation.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000264',\n", " 'title': 'CENC Study 25: Assessment of long term outcome & Disability in Active-duty military Prospectively examined following concussive TBI The ADAPT Study',\n", " 'pi': 'Christine MacDonald, PhD',\n", " 'fundingAmount': 37175000.0},\n", " {'abstract': 'The goal of the current research is to more fully characterize the neurobiological sequelae of exposure to primary blast forces, extending our previous findings of white matter injury in primary blast exposed Veterans both with and without acute symptoms of concussion at the time of exposure.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000329',\n", " 'title': 'CENC Study 34: Structural and Functional Neurobiology of Veterans Exposed to Primary Blast Forces',\n", " 'pi': 'Katherine Taber',\n", " 'fundingAmount': 37175000.0},\n", " {'abstract': 'Mild traumatic brain injury (mTBI) is common among military service members returning from OEF/OIF deployments. While a history of military mTBI has been demonstrated to be associated with increased risk of negative psychological outcomes (e.g., PTSD, depression, alcohol dependence), as well as disrupted brain connectivity, it is unknown how these conditions relate to neurodegenerative conditions, such as chronic traumatic encephalopathy (CTE). The purpose of this study is to better understand biological and psychological factors contributing to progressive functional deterioration among Veterans with a history of military concussion.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000348',\n", " 'title': 'CENC Study 49: Clinical and Neuroimaging Correlates of Neurodegeneration in Military mTBI',\n", " 'pi': 'Nicholas Davenport, PhD',\n", " 'fundingAmount': 37175000.0},\n", " {'abstract': 'This 3-year, prospective, case-control study of veterans will evaluate the consequences of mild TBI on the visual pathways in the eye and brain over time. Two main veteran cohorts with mild TBI and without TBI will be studied, and we will analyse visual function, eye movement and pupil recordings, and OCT imagining. An estimated 200-400 thoUnited States of Americand veterans have suffered a TBI in the Iraq and Afghanistan conflicts. Many of them have visual symptoms as a result of their TBI, but to date, a longitudinal study using quantitative visual and brain measures has not been performed.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000349',\n", " 'title': 'CENC Study 56: Visual Sensory Impairments and Progression Following Mild Traumatic Brain Injury',\n", " 'pi': 'Randy Kardon',\n", " 'fundingAmount': 37175000.0},\n", " {'abstract': \"Traumatic brain injury (TBI) is associated clinically with progressive cognitive decline and dementia and pathologically with axonal injury and the deposition of multiple aggregated proteins. Repetitive mild TBI can trigger chronic traumatic encephalopathy (CTE), a unique tauopathy, and single TBI can provoke an Alzheimer's-like neurodegeneration. Unfortunately, the only way to diagnose these posttraumatic neurodegenerations, including CTE, is by post-mortem brain examination. In order to conduct prospective research into the incidence, prevalence, risk factors, clinical course, and ultimately, treatment for posttraumatic neurodegeneration, consensus criteria for diagnosis as well as objective biomarkers for disease must first be established. This initiative will assemble a multicenter team of expert neuroscientists to evaluate the late effects of TBI, including single and repetitive TBI of varying severity, and CTE, using histological examination of postmortem biospecimens and neuroimaging tools as a foundation to develop in vivo diagnostics. As a first aim, this proposal will bring together a team of 5 accomplished neuropathologists in neurodegenerative disease to establish consensus criteria for the post-mortem diagnosis of CTE. This team will also define the stages of CTE pathology, the features that differentiate CTE from other neurodegenerations and the effects of substance abuse, and the characteristics of posttraumatic neurodegeneration after single TBI. As a second aim, this proposal will establish a national biospecimen and data bank for TBI (Understanding Neurological Injury and Traumatic Encephalopathy (UNITE) biobank) by developing a nationwide brain donor registry and hotline to acquire high quality biospecimens and data. The UNITE bank will use strictly standardized protocols and a web-based interface to ensure that tissue and data are readily available to qualified investigators. Comprehensive retrospective clinical data including clinical symptoms, brain trauma and substance abuse history, and medical records (including common data elements) will be entered into a secure database. Behavioral/ mood dysfunction, cognitive changes, substance abuse and traumatic exposure will be correlated with quantitative assessment of the multifocal tauopathy, A? deposition and axonal injury. As a third aim, neuroimaging signatures of the neuropathology will be determined in post-mortem tissue using high spatial resolution diffusion tensor imaging (DTI) and autoradiography using a highly selective PET ligand for tau. Quantitative assessment of axonal injury, tau, and A? will be correlated with ex vivo DTI abnormalities and tau ligand autoradiography. Pilot neuroimaging studies of individuals at high risk for the development of CTE will also be conducted in the final 2 years of the proposal. This proposal will determine the clinical and neuroimaging correlates of CTE and posttraumatic neurodegeneration and create the groundwork for establishing their incidence and prevalence. This study will have a tremendous impact on public health of millions of Americans and greatly increase our understanding of the latent effects of brain trauma.\",\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000227',\n", " 'title': 'CTE and Posttraumatic Neurodegeneration: Neuropathology and Ex Vivo Imaging (UNITE)',\n", " 'pi': 'Ann C McKee, MD',\n", " 'fundingAmount': 1541440.0},\n", " {'abstract': 'Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease characterized by a distinct deposition of an abnormal form of the tau protein in a pattern that is unique from other diseases, including Alzheimer\\'s\\r\\ndisease (AD). CTE has been found most often in professional contact sport athletes (e.g., boxing, football) who\\r\\nhave been subjected to repetitive blows to the head resulting in concussive and subconcussive trauma.\\r\\nNeuropathologically-confirmed CTE has been reported in individuals as young as 17 and in athletes who only\\r\\nplayed sports through high school or college. It also has been found in non-athletes who experienced repetitive\\r\\nhead impacts, including epileptics, victims of physical abuse, and military service members. In contrast to what\\r\\nmay be inferred by the extensive media attention on CTE, the science of CTE remains in its infancy; critical\\r\\nquestions remain, such as whether or not it is a common disease. Although the neuropathological features of\\r\\nCTE have become further clarified in recent years, the clinical presentation of CTE is still not well\\r\\ncharacterized, even though there have been case reports in the literature of \\\\\"dementia pugilistica\\\\\" in boxers since the early 1900\\'s. Clinical diagnostic criteria have only recently been published and lack validation.\\r\\nNeuroimaging and fluid biomarkers developed for the diagnosis of other neurodegenerative diseases have only\\r\\nbeen used in preliminary studies. There is thus an urgent need to develop accurate methods for detecting and\\r\\ndiagnosing CTE during life so that effective interventions for prevention and treatment can be developed.\\r\\nMoreover, though a history of repetitive head impacts is a necessary risk factor for CTE, it alone is not\\r\\nsufficient. There is a need to understand what specific aspects of the head impact exposure places an\\r\\nindividual at increased risk for CTE and to examine potential genetic modifiers of that risk. To address these\\r\\nneeds, we propose a multidisciplinary, multicenter, longitudinal study of former athletes with high exposure to\\r\\nrepetitive head impacts (120 former NFL players with and without symptoms) or medium exposure to repetitive\\r\\nhead impact (60 former college football players with and without symptoms) and a control group of 60\\r\\nasymptomatic same-age men without any history of repetitive head impact exposure or traumatic brain injury.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000305',\n", " 'title': 'Chronic Traumatic Encephalopathy: Detection, Diagnosis, Course, and Risk Factors',\n", " 'pi': 'Robert A Stern, PhD',\n", " 'fundingAmount': 2574020.0},\n", " {'abstract': 'Thirty chronic TBI participants with signs of suspected cognitive impairment, as determined by screening assessments, and 10 healthy age-matched controls will be recruited to complete neuropsychological assessments/self-report questionnaires, MRI, up to 3 PET scans ([C11]PiB, [C11]PBR-28) and [F18]AV-1451), and biospecimen collection (cerebrospinal fluid {CSF} and blood). Comparison of HDFT and PET results provide a method of determining an association among axonal injury, neuroinflammation and indications of neurodegeneration. Blood and CSF indicators will be evaluated as potential biomarkers of neurodegeneration, neuroinflammation and axonal injury.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000393',\n", " 'title': 'Comprehensive Biomarker Panel for Trauma-Related Dementia: Mechanistic links among axonal injury, neuroinflammation, and neurodegeneration',\n", " 'pi': 'David O Okonkwo',\n", " 'fundingAmount': 1300000.0},\n", " {'abstract': 'Background: During the acute phase, mild traumatic brain injury (mTBI) is known to cause serious disruption in normal biological, cognitive, and behavioral function. While research over the last decade has significantly advanced the science of mTBI, a comprehensive neurobiopsychosocial model of mTBI is yet to be achieved. \\r\\n\\r\\nObjective/Hypothesis: With the goal of conducting the most comprehensive study of mTBI to date, this proposal leverages the existing infrastructure of a current DoD-funded study by ?piggy-backing? additional scientific aims that have major significance to our scientific understanding of mTBI. We hypothesize that there will be a significant correlation between biomechanical, clinical, neurobiological, and neuroradiological markers of mTBI, which will more fully inform a neurobiopsychosocial model of mTBI. \\r\\nStudy Design: This is a prospective, cohort study that will include pre-exposure baseline assessment of a large sample of athletes enrolled, as well as acute and longitudinal follow-up assessment of a cohort with concussion, a matched control group of non- concussed athlete from the same contact sport, and a noncontact sport athlete control groups. 900 athletes participating in contact sports will undergo extensive pre-exposure baseline clinical, genetic, and biological studies. A subgroup of 50 contact sport athletes and the noncontact sport control group (n=50) will undergo preseason MRI studies as well. All participating athletes will be dually-equipped with the Riddell Head Impact Telemetry (HIT) system and non-helmet based sensor technologies to record biomechanical measurements of head impact exposure. Concussed athletes (n=50), a matched contact sport athlete control (n=50), and noncontact sport athlete control (n=50) will then undergo extensive post-injury follow-up studies at multiple time points. An array of blood biomarkers will be collected in concussed and control athletes within 6 hours of injury. Both groups will also then undergo clinical, blood biomarker, and advanced neuroimaging studies again at 24 hours, 8 days, 15 days and 45 days postinjury. Our study design will allow us to analyze the diagnostic and predictive value of each mTBI biomarker domain over time, as well as create a correlative, multi-dimensional diagnostic and prognostic model of mTBI. \\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000279',\n", " 'title': 'Comprehensive study of acute effects and recovery after concussion: An integrated investigation of head impact sensor technology, blood biomarkers, advanced neuroimaging, genetic testing and clinical outcome metrics',\n", " 'pi': 'Michael McCrea',\n", " 'fundingAmount': 6158640.0},\n", " {'abstract': 'Mild traumatic brain injury (TBI) and sport-related concussion (SRC) are major public health problems. Although significant advances have been made in our understanding of concussion, to date, the natural history of concussion remains poorly defined, no objective biomarker of physiological recovery exists for clinical use, and athlete knowledge of the injury remains low. This investigation is poised to address the true natural history of clinical and physiological recovery of SRC, which has critical implications for improving safety, injury prevention, and medical care in athletes and military personnel. Objective: In keeping with the identified priorities of the National Collegiate Atheletic Association (NCAA) and Department of Defense (DoD), we propose the Concussion Assessment, Research and Education (CARE) Consortium as a scientific and operational framework for the NCAA-DoD Grand Alliance. Hypotheses: There are two over-arching hypotheses driving this proposal:(1) Neurophysiological recovery from concussion extends beyond clinical signs and symptoms resolution.(2) A multidimensional combination of biomechanical, genetic, neuroradiological, biological, and clinical variables will be more strongly predictive of concussion risk and recovery than any single predictor variable. This study led by the Indiana University School of Medicine, Medical College of Wisconsin, and University of Michigan marks what is considered to be the most comprehensive investigation of sport-related concussion (SRC) ever conducted. This study will allow scientists to better understand the true natural history of concussion in athletes and investigate the correlation between multi-dimensional predictor and outcome variables associated with SRC from a fully neurobiopsychosocial perspective in a common injured sample and single study design.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000310',\n", " 'title': 'Concussion Assessment, Research and Education (CARE) Consortium',\n", " 'pi': 'Steven P Broglio',\n", " 'fundingAmount': 14636000.0},\n", " {'abstract': \"This study will use neuroimaging to understand how the connections in the brain change in Alzheimer's Disease. Changes will also be examined in individuals with mild cognitive impairment and healthy aging. The goal is to discover which brain changes are present in healthy aging and MCI so that future studies can assess the risk for developing Alzheimer's Disease. The study involves 3 visits to MUSC: a screening visit for cognitive testing and neuroimaging, a second visit for additional neuroimaging for those who qualify for the study, and a 6-month follow-up visit for cognitive testing.\",\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000385',\n", " 'title': \"Connectome Biomarkers for Predicting Alzheimer's Risk in Traumatic Brain Injury\",\n", " 'pi': 'Jane E Joseph, PhD',\n", " 'fundingAmount': 670969.0},\n", " {'abstract': 'Pediatric concussion remains without a reliable scanning tool to image injury or guide therapies. Previous studies with MRI use methods, such as diffusion tensor imaging, functional MRI and functional connectivity MRI, that have not yet been sensitive or specific enough to be used as clinical scans. MR spectroscopy allows measures of the chemical composition in parts of the brain. Recent advances in MR spectroscopy allow for the detection of levels of neurotransmitters, including gamma-amino butyric acid (GABA) which is a widespread inhibitory transmitter. GABA function is critical for cognition and may be abnormal in trauma. Abnormal GABA levels may impair recovery in animal models of injury. Our group combines a dedicated sports concussion program, a work-in-progress collaboration with Siemens Medical Imaging group, and an advanced imaging system (3T magnet with 32 channel head coil) along with a radiology research group with expertise in pediatric neuroimaging. We will address several areas of research interest by developing and studying MR spectroscopy of GABA in a tightly defined pediatric sports concussion population, with appropriate controls. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000239',\n", " 'title': 'Cortical GABA in pediatric sports concussion',\n", " 'pi': 'Jeffrey G Ojemann, MD',\n", " 'fundingAmount': 71821.0},\n", " {'abstract': 'The goal of acute traumatic brain injury (TBI) treatment is to minimize secondary damage that evolves over hours to days after the primary injury. Until now, however, there have been no methods for monitoring heterogeneous pathomechanisms to identify patients for appropriate neuroprotection therapies. Using invasive monitoring in TBI patients requiring craniotomy, we have documented that spreading depolarizations (SD), a seizure-like pathology of cerebral gray matter that has been well-characterized through 60 years of research in animal models, are the dominant pathophysiologic process in peri-lesion cortex of many, but not all, severe TBI patients. Furthermore, we found that the occurrence of SD as a secondary injury process in patients is an independent predictor of worse neurologic outcomes. Thus, monitoring of SD provides the first real-time measure of neuronal secondary injury processes in patients to determine the selective application and benefit of neuroprotective therapies. However, since surgical patients are <10% of all TBI, less invasive and non-invasive techniques for SD monitoring are now required to generalize these findings. The premise of this proposal is that SD occurs across the spectrum of TBI severity as a pathologic mechanism of disease process and outcome heterogeneity.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000389',\n", " 'title': 'Development and validation of spreading depolarization monitoring for TBI management',\n", " 'pi': 'Jed Hartings',\n", " 'fundingAmount': 4729860.0},\n", " {'abstract': 'Chronic migraine (CM) is a syndrome producing significant morbidity for the sufferer in terms of interfering with employment and career advancement, family relations/responsibilities, leisure activities and enjoyment of life, and has a course that may last for months to years. While this syndrome is described as a primary headache that may occur in 1-2 % of the population, the phenotype of CM is a common sequel of Deployment-related TBI (D-TBI) occurring in up to 40% of OEF/OIF Veterans with a D-TBI. Post-Traumatic CM (PT-CM) may continue unabated for 2-11 years after the TBI. The biochemical mechanism producing this recurrent headache, varying from 15 headache days per month to virtually continuous headache, is not understood. The hypothesis is that PT-CM and Idiopathic CM (I-CM) are related to ongoing neuro-inflammatory processes, possibly with neuro-degenerative and vascular components, that are producing unique biomolecules which are shed into the interstitial spaces and then cross the blood-brain barrier into the peripheral blood. This hypothesis further states that this study will be able to identify these different biomolecules and their mass profiles in the blood and determine if the CM syndromes they reflect are different or similar. This study will utilize the Electrospray Ionization Mass Spectrometry (ESI-MS) technology, which is very simple, robust, and low-cost, to identify distinguish and monitor serum mass profiles for PT-CM, I-CM, and matched controls, and show differences as well as similarities in these serum mass profiles. Tandem MS/MS will then identify biomolecules and biomarkers unique to the TBI and I-CM conditions. These biomolecules and their profiles can provide clues to the biochemical mechanisms underlying PT-CM and I-CM, and may suggest possibilities for therapy. This is a translational project that will evaluate and compare serum mass profiles produces by the ESI-MS technology in four groups of subjects. These groups include: (a) Veterans of OEF/OIF who have suffered a D-TBI and subsequently manifest the syndrome of CM (PT-CM); (b) control subjects drawn from OEF/OIF Veterans who are matched to the PT-CM subjects by age sex , race and time of deployment; (c) Veterans with CM who did not have a D-TBI and who developed idiopathic CM during or after deployment; and (d) control subjects drawn from veterans who do not have headaches more than 1/month and who have not had a D-TBI who will be matched to the subjects in group c by age, sex and race. (e) Veterans who have suffered a D-TBI and have headaches <10 days/month. The intent is to collect 75 subjects in each group. As some problems with drop-outs is anticipated we will collect up to 90 subjects in each group Recruiting these four groups will allow comparison of the serum mass profiles of the subjects in the following format: 1. Group a vs Group b 2. Group c vs Group d 3. Group a vs Group c 4. Group b vs Group d 5. Group a vs group e 6. Group c vs group d 7. Group b + d vs group e.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000354',\n", " 'title': 'Development of Unique Serum Biomarkers with mass Spectroscopy for Diagnosis of Veterans with Chronic Posttraumatic Headache Versus Idiopathic Chronic Migraine',\n", " 'pi': 'James Couch',\n", " 'fundingAmount': 251165.0},\n", " {'abstract': 'Background: Persistent and disabling cognitive difficulties are frequently reported by Veterans and ADSM with a history of mild TBI (mTBI), but interventions that are both accessible and effective remain limited. The proposed study will build on the existing literature, which supports the effectiveness of longer/more intensive cognitive rehabilitation (CR) interventions for Veterans/ADSM, by developing a non-invasive, inexpensive brief CR intervention that is specifically targeted to the unique needs of this population. Using an empirically validated 10-week CR intervention called Compensatory Cognitive Training (CCT) as the starting point, the proposed study aims to develop a brief CR intervention using a rigorous multi-faceted approach to identify the content for this intervention that will be specifically designed to address the needs and treatment goals of Veterans who have persisting cognitive difficulties secondary to mTBI. This intervention will address several current barriers to care including (1) reducing time and associated financial demands of a more extensive treatment, (2) offering strategies to improve day to day functioning that may lead to increased treatment compliance due to reductions in forgotten appointments and medications, and (3) potentially increasing the ability to benefit from other treatments for common comorbid conditions by improving current cognitive functioning. \\r\\nObjective/Hypothesis: The primary goal of this study is to develop the treatment manual for the proposed brief CR intervention, as well as other materials necessary to conduct the future RCT. In order to develop the manual, we propose to integrate information from multiple sources including (1) a survey to assess treatment preferences, barriers to care, attitudes toward CR, and the nature/functional impact of ongoing cognitive difficulties and other symptoms among Veterans who were previously diagnosed with mTBI and endorsed persisting symptoms,(2) a survey of clinicians who currently provide CR interventions in VA settings, (3) review and comparison of findings from step 1 and 2 with the completed full-length CCT randomized controlled trial in Veterans with a history of mTBI, and (4) feedback from Veterans who participate in the newly developed brief CR intervention. \\r\\nImpact and Military Relevance: Persisting cognitive difficulties are common among Veterans and ADSM with a history of mTBI and can have significant and wide range impact on day to day functioning. Empirically validated treatment options for CR exist for this population, but the length of treatment may pose a financial and time barrier. A brief CR intervention has the potential to significantly improve access to care for persisting cognitive difficulties among individuals with a history of mTBI and improve overall functioning and quality of life as well as serving as a possible gateway for engagement in other needed treatments. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000412',\n", " 'title': 'Development of a Brief Version of Compensatory Cognitive Training for Veterans with Mild Traumatic Brain Injury',\n", " 'pi': 'Kathleen Pagulayan, PhD',\n", " 'fundingAmount': 196895.0},\n", " {'abstract': 'Many Service Members returning from deployment complain of problems communicating in noisy settings, especially when they are trying to understand speech when there are competing sounds. However, when they go to the audiological clinic, they are often found to have ?normal hearing,? meaning that they can detect quiet sounds as easily as healthy young adults without hearing dysfunction. To date, the reasons for these kinds of hearing difficulties are not well understood, and, therefore, there is no evidence-based approach to treating such problems. Anecdotally, blast exposure, which many returning Service Members have suffered, seems to cause or exacerbate these kinds of complaints. An ongoing study of the prevalence of hearing dysfunction in Service Members at Walter Reed National Military Medical Center (WRNMMC) on the impact of hearing dysfunction on Fitness for Duty suggests that as many as 40% of Service Members deployed to Iraq or Afghanistan experienced high-intensity blasts, and that roughly 40% of these blast-exposed personnel show functional hearing deficits, despite having normal hearing thresholds?leading to the staggering suggestion that 15-20% of returning Service Members may fall into this category of listeners with ?normal hearing? who nonetheless have difficulty communicating in everyday environments.\\r\\nThe current project builds on emerging evidence that suggest that in listeners with ?normal? hearing, there are at least two quite distinct deficits that can contribute to problems understanding speech amidst competing sources, but through very different mechanisms. The first, a sensory deficit, is thought to arise from a loss in the number of auditory nerve fibers conveying sound from the cochlea to the brain. This ?auditory neuropathy,? which is now well documented in animals, does not always affect hearing thresholds, but degrades the fidelity with which auditory information is encoded. Auditory neuropathy is associated with noise exposure, which may explain why Service Members are particularly prone to experiencing difficulty. The second, a cortical deficit, is thought to arise from damage to cortical structures that are engaged when a listener is trying to focus attention on one sound and ignore competing sounds. This process of directing attention changes the information that the brain extracts from a scene, but depends on many different neural regions coordinating their activity in precise ways. Blast exposure experienced by Service Members is likely damaging parts of the brain (and connections between brain regions) that are critical for controlling this ?auditory selective attention,? thus leading to communication disorders.\\r\\nThe first and second goals of this project are to test Service Members who have clinically ?normal hearing? (based on current audiometric tests) to determine how both sensory and cortical deficits (respectively) contribute to their problems. The third goal is to develop rapid, reliable, and repeatable tests that can separately quantify sensory coding fidelity and the ability of an individual listener to cortically control selective auditory attention. Five to eight years from now, such tests could be in the clinic, revolutionizing how audiologists think about hearing function, and how they counsel their clients.\\r\\nResults from the proposed study will build new understanding of the mechanisms that lead to hearing dysfunction that is currently ?invisible.? By uncovering the core deficiencies leading to difficulties communicating in noisy settings and developing robust diagnostic tests, new interventions and therapies may be developed that target specific deficits in individual patients. Results are likely to aid in the development of appropriate evaluations of auditory Fitness for Duty, ensuring more Service Members are operating effectively in their military roles.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000342',\n", " 'title': 'Diagnosing contributions of sensory and cognitive deficits to hearing dysfunction in blast-exposed/TBI Service Members',\n", " 'pi': 'Barbara Shinn-Cunningham',\n", " 'fundingAmount': 1490290.0},\n", " {'abstract': 'An observational cohort study within BOOST-3 evaluating the relationship between\\r\\nestablished biomarkers of metabolic demand (PbtO2), EEG abnormalities (ESz and\\r\\nHFPD), clinical outcome, and treatment, seeking to identify dynamic EEG biomarkers of\\r\\nsecondary injury that will enable future clinical trials seeking to improve functional\\r\\noutcomes for sTBI patients.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000435',\n", " 'title': 'ELECTRO-BOOST',\n", " 'pi': 'Emily Gilmore',\n", " 'fundingAmount': 707787.0},\n", " {'abstract': 'Blast injuries and other head injuries sustained in battle have been associated with the development of chronic traumatic encephalopathy (CTE). This disorder is considered to be a progressive neurodegenerative disease manifest by cognitive, motoric, and behavioral impairment, possibly including post traumatic stress disorder in the military. Cumulative head trauma is also linked to CTE in other settings such as professional contact/combat sports. \\r\\n\\r\\nPathological series have indicated that a characteristic feature of CTE is accumulation of tau protein in the brain. Recent animal models of blast injuries have reported that tau is expressed very early after trauma. Moreover, it has been discovered that tau, once expressed, can spread from cell to cell on an ongoing basis. \\r\\n\\r\\nOur understanding of the natural history of CTE is limited to say the least. Most previous studies examining the effects of cumulative head trauma are cross sectional, retrospective, utilize single outcomes (either psychometric or imaging), or did not have access to newer investigative technology including new imaging technology. Having the ability to image tau deposition during life in those exposed to repetitive head trauma, and showing an association between this and a behavioral marker such as cognitive test scores, will provide a tool to expand our understanding of the course and manifestations of CTE in the living human. \\r\\n\\r\\nUntil very recently, there has been no reliable way of measuring tau deposition in the brain during life. Rather, families of affected individuals waited until autopsy for a confirmed diagnosis. One PET biomarker, F-FDDNP (2-(1-{6-[(2-[F-18]fluoroethyl(methyl)amino]-2-naphthyl} ethylidene) malononitrile) [FDDNP] has shown sensitivity for in vivo detection of tau in addition to brain amyloid neuroaggregates, and beta amyloid among others. This ligand has been used in Alzheimer?s disease, frontotemporal lobe dementia and progressive supranuclear palsy to establish associations between neuroaggregate deposition and behavior. There is a relationship between the extent of tau deposition in the brain, neuronal losses and level of cognitive impairment in Alzheimer?s disease, suggesting that increased deposition is related to further decline.\\r\\n\\r\\nThis project will examine whether FDDNP PET imaging correlates with, and/or can predict, decline in cognitive function in those exposed to cumulative head trauma. Furthermore, experience will be gained regarding the value of FDDNP PET in early (possibly preclinical) identification of developing neurodegeneration such as CTE. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000270',\n", " 'title': 'Early Recognition of Chronic Traumatic Encephalopathy Through FDDNP PET Imaging',\n", " 'pi': 'Charles Bernick, MD, MPH',\n", " 'fundingAmount': 746068.0},\n", " {'abstract': \"The overall goal is to determine the relationships between traumatic brain injury (TBI), post-traumatic stress disorder (PTSD), aging and cognitive decline on brain tau at baseline and longitudinally. This will be achieved by using the tau positron emission tomography (PET) ligand [18F]-T807 (AVID/Lilly) in existing cohorts of veterans and civilians. Our major hypotheses will be that (1) the distribution of brain tau will correspond to the previously reported Braak & Braak staging; (2) brain tau in older subjects is associated with cognitive impairment and increased in the presence of brain amyloid beta deposition (measured by Amyloid beta PET); (3) a prior history of TBI is associated with increased brain tau relative to Amyloid beta deposition, after controlling for age and Apoe4 gene status; and (4) longitudinal changes of brain tau correlate with Amyloid beta PET, cognition, and history of TBI. These objectives will be achieved by performing baseline and longitudinal tau PET scanning with the [18F]-T807 ligand on 450 subjects currently enrolled in three currently funded grants; 1) A DOD funded grant entitled: Effects of traumatic brain injury and post-traumatic stress disorder on Alzheimer's disease in Vietnam Veterans using ADNI, 2) A DOD funded grant entitled: Effects of traumatic brain injury and post-traumatic stress disorder on Alzheimer's disease in Vietnam Veterans with mild cognitive impairment (MCI) using ADNI, 3) An NIA funded grant entitled: The Alzheimer's Disease Neuroimaging Initiative (ADNI). The 450 subjects will be divided into 9 groups of approximately 50 subjects each for baseline scans and 20 subjects per group will be restudied after two years.\",\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000352',\n", " 'title': \"Effects of Traumatic Brain Injury and Post-Traumatic Stress Disorder and Alzheimer's Disease on Brain Tau in Vietnam Veterans using ADNI\",\n", " 'pi': 'Michael Weiner',\n", " 'fundingAmount': 5281400.0},\n", " {'abstract': 'The goal of this project is to determine the efficacy of using biomechanical data gathered from a mobile device to objectively and quantitatively evaluate balance and postural stability under cognitive conditions that resemble those routinely performed by military service members. Data will be collected from civilians as well as service members.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000371',\n", " 'title': 'Enhancing the detection and management of mTBI in military personnel',\n", " 'pi': 'Jay Alberts, Ph. D.',\n", " 'fundingAmount': 643321.0},\n", " {'abstract': 'Study In the US military, it is estimated that roughly 20% of the deployed force suffered a head injury1 in the wars in Iraq and Afghanistan, 83.3% of whom endured a mild, uncomplicated TBI or concussion2,3. The long term impact of these injuries is just beginning to be appreciated. Many of these service members are young males, 20-30 years old who have decades of life to live with the complex and often debilitating impact of war-time brain injury. The total lifetime health care costs are largely unknown. Although substantial effort has been placed on trying to better understand this type of injury, much research has been forced to rely largely on self- reporting4-11, retrospective medical records review 12-16, or evaluations of only later stages of injury17, 18. No study to date has prospectively followed active-duty US military from injury to long term outcome with advanced MR imaging and clinical evaluation. The overall goal is to investigate long-term advanced MR imaging measures and clinical outcome of concussive traumatic brain injury (TBI) sustained during deployment in US military personnel. We will relate these findings to prospectively acquired longitudinal imaging and clinical data from the acute/sub-acute, and early chronic stages following concussion collected on these patients as part of previous collaborative efforts. We hypothesize that early clinical and imaging measures will offer predictive insight into late stage clinical outcome. Study Design: As part of previous collaborative efforts, we have successfully completed early prospective, longitudinal studies enrolling active-duty US military at 0-7 days (median 4), 0-30 days (median 8), and 0-90 days (median 14) post-injury19-21 where early advanced MR imaging and clinical data were collected. In total, 591 subjects were enrolled through these efforts; 54% TBI, 46% control. We propose to re-examine control and TBI subjects now 5-7 years post-injury and compare their current clinical and imaging presentation with the previously acquired longitudinal data. We believe that this population offers a unique opportunity to rigorously evaluate the long term impact of war-time concussive TBI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000273',\n", " 'title': 'Evaluation Of Longitudinal outcomes in mild TBI Active-Duty Military and Veterans',\n", " 'pi': 'Christine M MacDonald, PhD',\n", " 'fundingAmount': 621261.0},\n", " {'abstract': 'Sports-related traumatic brain injuries (TBIs), including mTBIs?commonly referred to as concussions?are a serious public health concern. Although most sports-related concussions are mild injuries TBIs contribute to a substantial number of deaths and cases of permanent disability. While contact sports such as football have the highest incidence and rates of concussion, these injuries occur across a wide range of sports. Diagnostic criteria and consensus return to play (RTP) guidelines exist, but clinicians have varying approaches to the\\r\\ndiagnosis and management of sports-related concussion as these guidelines are almost completely unsupported by an evidence base. It is well known that by increasing awareness of concussion signs and symptoms as well as the importance of addressing this injury, improving coaching on proper sports activity techniques and good sportsmanship, providing appropriate protective equipment, and quickly responding to injuries, the incidence, severity, and long-term negative health effects of sports-related concussion among children and adolescents can be reduced. Thus there is a critical need for the development of tools for prevention. Our long-term goal is to reduce the negative consequences of sports-related concussion, specifically in youth sports. The overall objective of this application, which is the first step toward attainment of\\r\\nour long-term goal, is to evaluate the effectiveness of Spot Light (a concussion injury management application [app] that coordinates diagnosis, management, and RTP procedures from injury to safe return to sport) when utilized by youth football teams. Our central hypothesis is that youth football teams randomized to receive Spot Light will report increased rates of concussion, increased referrals to physicians for care, and increased athlete compliance with RTP guidelines. The rationale that underlies the proposed research is that providing an easy to-\\r\\nuse app has a high probability of effectively helping people involved with youth sports better recognize, respond to, and ensure athletes are fully recovered from sports-related concussion. We will test our hypothesis by pursuing the following aims: 1: Evaluate whether Spot Light will increase reported rates of sports-related concussion; Aim 2: Evaluate whether Spot Light increases referrals to physicians following concussion; Aim 3: Evaluate whether Spot Light improves the management of sports-related concussion. We expect to determine\\r\\nwhether there is increased reporting, referrals to physicians, and athlete compliance with RTP guidelines. This contribution will be significant because it will allow physicians, athletic trainers (ATs), coaches, and parents to collaboratively track concussions from injury through safe RTP thereby lessoning the chances of long-term negative outcomes as well as acute catastrophic outcomes. This research is innovative because it will have both immediate and long-term impacts on the scientific knowledge in the areas of sports injury prevention and the use of mobile app technology as a tool for injury recognition, management/treatment, and prevention.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000269',\n", " 'title': 'Evaluation of Spot Light: A concussion injury management app for youth',\n", " 'pi': 'Lara McKenzie',\n", " 'fundingAmount': 221771.0},\n", " {'abstract': 'This is a multi-site observational study with the primary purpose of collecting overpressure (OP) exposure data and measuring associated effects. The study will occur in conjunction with training exercises at local and national military and law enforcement training facilities that involve exposure to OP (pressure in excess of atmospheric pressure). OP exposure will be quantified from a variety of weapon systems/environments ranging from safe (< 4 psi) to high exposure (> 8 psi). Associated effects data will be collected immediately after OP exposure (i.e., within 20 min) and/or at the end of the exposure day to measure acute effects; the data collection schedule will vary by site. The data measures collected will vary by site and may include neurocognitive (short, computed-based tests) and physiological (blood-based biomarkers, eye-tracking, tactile sensory perception, balance, symptom reporting).',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000353',\n", " 'title': 'Evaluation of the Effects of High Level Overpressure (8 Plus psi) on Cognitive Performance, Brain Blood Biomarkers and Symptom Reporting',\n", " 'pi': 'Walter S Carr',\n", " 'fundingAmount': 1670200.0},\n", " {'abstract': 'Background: During viewing of complex scenes, eye movements are planned in high-level regions of the brain. Just as eye movements are directed towards particular locations in space, attention can be focused on discrete locations in a visual scene; the neural mechanisms of visual spatial attention and eye movements strongly indicates that there is a great deal of overlap between the two systems. Accurate eye movements and successful re-direction of attention therefore require intact function in frontal and parietal cortical regions. We propose a series of behavioral and magnetic resonance imaging (MRI) experiments that will determine the degree to which difficulties with visual attention, saccade targeting and motion perception associated with mild traumatic brain injury (mTBI) can be attributed to damaged cortical brain networks serving attention and eye movement planning. Broadly, the Focus Area is mitigation and treatment of visual dysfunction associated with mTBI. Specifically: the objective of this research is to identify biomarkers of visual system injuries in the brain associated with mTBI.\\r\\n\\r\\nObjective/Hypothesis: The proposed research will test the hypothesis that spatial attention and eye movement deficits associated with mTBI result from disruption of the gray matter and/or the white matter in cortical networks that control attention allocation and eye movements. A combination of functional MRI and diffusion-weighted imaging will allow us to measure (1) integrity in cortical networks in frontal and parietal brain regions responsible for attention allocation and eye-movement planning, and (2) integrity in the white matter that contains the axons that carry the outputs of these cortical computations to the sub-cortical nuclei that actually control eye movements.\\r\\n\\r\\nSpecific Aim 1 is to establish a measure of the health of visual spatial attention and eye-movement planning networks. In this aim, we hypothesize that fronto-parietal priority networks show reduced selectivity for spatial location in subjects who demonstrate relatively weak spatial attention performance. Our objective is to quantify(1) performance on tasks that require either spatial attention allocation or eye movements and (2) contrast-to-noise ratio, as measured with functional MRI, in brain regions with spatial attention and eye movement.\\r\\n\\r\\nSpecific Aim 2 is to determine strength of correlation between frontoparietal white matter fractional anisotropy and accuracy of eye movements. We hypothesize that damage to cortical white matter impairs eye-movement. Our objective is to measure, in the same scanning session as Aim 1, the white matter integrity in the WM tracts carrying information within and from the fronto-parietal priority network.\\r\\n\\r\\nStudy design: For Aim 1, the association between behavioral and neuroimaging measures (assessed in two study visits, each 2h long) will be measured within a group of 24 subjects with mTBI and weak spatial attention skills. Results will be compared against a control group of 24 subjects with TBI but no visual complaints.\\r\\n\\r\\nPerformance on static tasks that do not require attention shifting, eye movement or motion perception will be measured to test whether association with neuroimaging data is specific to oculomotor skills. For Aim 2, the associations between successful eye movements, successful visual attention allocation, and white matter integrity in four a priori frontoparietal regions of interest (and 2 control regions) will be quantified. Again, performance on static tasks that do not require eye movement or motion perception will be measured to test whether the association with fronto-parietal FA measurements is specific to oculomotor skills.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000256',\n", " 'title': 'Frontoparietal priority maps as biomarkers for mTBI',\n", " 'pi': 'Cheryl Olman',\n", " 'fundingAmount': 249910.0},\n", " {'abstract': 'The purpose of the proposed research is to determine the value of Constraint-Induced Movement therapy (CIMT) and Lakeshore Enriched Fitness Training (LEFT) for improving motor ability in veterans/warfighters and civilians with traumatic brain injury (TBI) and test whether any therapeutic effects observed are correlated with neuroplastic white matter or grey matter changes. In the proposed study we plan to carry out a rigorous, single-blind randomized controlled trial to determine the efficacy of CIMT to improve motor function and general fitness in patients with TBI in comparison to a LEFT group that controls for amount of physical activity, therapist interaction, and setting. The study will also test the effect of a set of enhanced versus ?standard? procedures for transferring therapeutic gains from treatment setting to everyday life. Thus, there will be a total of four groups: 1. CIMT with standard Transfer Package (sTP), 2. CIMT with enhanced Transfer Package (eTP), 3. LEFT with sTP, and 4. LEFT with eTP. There will be 20 participants per group. Treatment, testing, and follow-up testing will be carried out in the first 2 grant years and the 1-year follow-up will be completed in the third year. Immediately after the first year, longitudinal neuroimaging studies to determine the treatment change in white matter, grey matter, and functional brain connectivity will be carried out across the above-noted time points by different diffusion tensor imaging analysis variants, voxel-based morphometry analysis of structural magnetic resonance imaging (MRI) scans, and analysis of resting state functional MRI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000343',\n", " 'title': 'Harnessing Neuroplasticity to Promote Rehabilitation: CI Therapy for TBI',\n", " 'pi': 'Edward Taub, PhD',\n", " 'fundingAmount': 2664760.0},\n", " {'abstract': 'United States Veterans and Warfighters with mild traumatic brain injury (mTBI) sustained in recent conflicts frequently report sensory post-concussive symptoms (PCS) in multiple domains, despite near-normal visual and auditory acuity. These findings suggest that symptoms may arise not from a problem with unisensory perception but from impaired â\\x80\\x9ctop-downâ\\x80\\x9d processing of sensory information by a cognitive control network (CCN). \\r\\nPrior work by our group in functional magnetic resonance imaging and magnetoencephalography (MEG) of mTBI confirms the existence of CCN dysfunction after mTBI and an association with post-concussive symptom scores. Unfortunately, no treatments for sensory PCS have been validated for military mTBI at this time. Vision therapy, a type of rehabilitation shown effective for post-concussive convergence insufficiency by our study team, involves significant time, expertise, and cumbersome equipment to deliver. \\r\\nOne promising intervention that can improve aberrant network activity is high-definition transcranial direct current stimulation (HD-tDCS). HD-tDCS is a well-tolerated, non-invasive brain stimulation technique that utilizes focused electrical fields applied through the scalp to\\r\\nmodulate neuroplasticity. When paired with rehabilitation tasks, HD-tDCS can increase functional gains beyond what is obtained from a task alone. Our study team has shown efficacy of HD-tDCS for post-stroke aphasia, and is currently conducting a trial of conventional tDCS for cognitive PCS in civilians. To date, HD-tDCS has never been studied in military mTBI and represents a highly innovative treatment approach. \\r\\nThe NAVIGATe Study is a randomized, sham-controlled trial of HD-tDCS paired with training tasks for the treatment of sensory PCS. Eighty Veterans and Active Duty Service members with mTBI will be recruited from the New Mexico Veterans Affairs Health Care System (NMVAHCS) Polytrauma Support Clinic and the 377th Medical Group at Kirtland Air Force Base for the stimulation arm of the protocol. They will undergo MEG combined with structural MRI to perform magnetic source imaging (MSI) and functional MRI to characterize the temporal and spatial characteristics of involved brain networks, along with sensory and cognitive batteries. \\r\\nThey will then undergo 10 daily sessions of sensory training combined with active or sham HD-tDCS delivered to the dorsolateral prefrontal cortex, a key node in the CCN. Sensory training consists of vision therapy administered through a virtual reality headset equipped with eye-tracking capability, and a dual auditory/visual working memory task validated by our study team in numerous protocols. Each session will last for 30 minutes. \\r\\nFollowing the 10th stimulation session, the cognitive and sensory batteries will be repeated, along with MSI. Long-term improvements in quality of life will be assessed at 1, 3, and 6 months after stimulation. The primary outcome variable is change in the somatic symptom subscale of the Neurobehavioral Symptom Inventory, a measure of PCS. In addition to active versus sham comparisons of HD-tDCS effect, a group of 40 healthy subjects will be enrolled to serve as imaging-only controls to evaluate natural variations in brain and behavior in the absence of stimulation.\\r\\n\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000416',\n", " 'title': 'High-Definition Transcranial Direct Current Stimulation for Sensory Deficits in Complex TBI',\n", " 'pi': 'Davin Quinn, MD',\n", " 'fundingAmount': 2924310.0},\n", " {'abstract': 'We will conduct a parallel arm, randomized controlled trial with 80 veterans with TBI to 12-weeks of in-home CT (BrainHQ) + MT (Start Moving Forward) vs. an active control intervention. In CT+MT, every session shall begin with 10 minutes of a MT session in which trainees receive useful attitudes and skills (problem solving therapy) followed by 30 minutes of computer-based training 5 days/week for 12 weeks. The active control program shall be composed of 10 minutes online information session and commercially available casual video games. For the primary outcome variable, we have chosen performance on tasks of processing speed that are included in the NIH Toolbox and other standardized batteries to evaluate the outcome of intervention. As secondary measures, we will examine performances on tasks of attention, working memory and executive function. Functional and structural changes of the brain will be measured with MRI. Additionally, to assess transfer to everyday functioning, we will administer the Functional Status Battery. Daily-based subjective logging of participants? mood, brain healthy diet, physical activity and sleep quality will document real-world impacts of brain training on subjective indices of quality of life.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000345',\n", " 'title': 'Home-based, Online Mindfulness and Cognitive Training for Soldiers and Veterans with TBI',\n", " 'pi': 'Hyun K Lee',\n", " 'fundingAmount': 565263.0},\n", " {'abstract': 'Approximately 80% of military mTBI, affecting hundreds of thousands of soldiers, occur in non-deployed settings\\r\\nlike combative training activities.\\r\\n\\r\\nConcussion and mTBI caused by loss of consciousness is\\r\\nserious concern to the Departments of Defense and Transportation because it is a major impediment to egress in\\r\\naviation crashes. \\r\\n\\r\\nMilitary, athletic and transportation authorities have long desired a system that can monitor\\r\\nconcussion and mTBI risk in real-time, as well as quantify head impacts that cause acute and long-term brain health\\r\\ndecline. In spite of recent proliferation in head impact instrumentation, there still is no objective means to identify\\r\\nconcussion risk in real-time from any single impact.\\r\\n\\r\\nIn this proposal we will use valid measurements to quantify head impact severity, clinical behavioral\\r\\nassessments and brain damage locations in comprehensive studies of soldiers and athletes.\\r\\n\\r\\nWe specifically aim to\\r\\n(1)Monitor dangerous head impacts to US Army Soldiers undergoing combative training without negatively\\r\\nimpacting concept of operations. Provide head injury risk functions and dose-response relationships gathered from\\r\\nModern Army Combatives Program (MACP) personnel, \\r\\n\\r\\n(2) Develop a prototype military-specific boil-and-bite\\r\\nIntelligent Mouthguard to instrument and monitor large numbers of personnel simultaneously without negatively\\r\\nimpacting the concept of operations, \\r\\n\\r\\n(3) Conduct a pilot project to determine how to best monitor head impacts and\\r\\nquantify injury risk in Federal Service Academy personnel participating in American Football, Ice Hockey,\\r\\nLacrosse, Rugby, Soccer, Wrestling and Boxing, \\r\\n\\r\\n(4) Conduct a pilot project to monitor head impacts in the airborne\\r\\nenvironment and determine how to utilize this population to best quantify dose-response relationship without\\r\\nnegatively impacting concept of operations and \\r\\n\\r\\n(5) Assist USAARL in laboratory testing to develop standard means\\r\\nto quantify sensitivity and specificity of head impact dosimeters in ATD and PMHS tests.\\r\\nAfter completing these projects, we will have defined the relationship(s) between head impact kinematics,\\r\\nbehavioral outcomes and likely locations of brain injury for US Military and athletic populations. We will be able to\\r\\ndefine performance specifications for environmental sensing instruments that can monitor US Military members at\\r\\nrisk of short- and long-term head injury in training. We will know kinematic inputs responsible for highest head\\r\\ninjury risk and be able to pursue subsequent projects that design military, athletic and transportation-specific\\r\\nprotective systems to reduce impact kinematics in a physics-based manner. Finally, we will have pre-production,\\r\\nruggedized and user-friendly systems ready to monitor future US Military members.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000413',\n", " 'title': 'Human Head Impact Dose Concussion Risk Functions and Sensor-Based Military-Specific Environmental Monitoring System',\n", " 'pi': 'Adam J Bartsch',\n", " 'fundingAmount': 2886200.0},\n", " {'abstract': 'A Multicenter, Randomized, Prospective Phase II Adaptive Clinical Trial Evaluating the Most Effective Hyperbaric Oxygen Treatment Paradigm for Severe Traumatic Brain Injury.\\r\\n\\r\\nThere continues to be an overarching problem of high mortality and poor outcome for victims of severe traumatic brain injury (TBI). Preclinical and clinical investigations indicate that hyperbaric oxygen (HBO) has a positive impact on reducing brain injury and improving outcomes in severe TBI. By markedly increasing oxygen (O2) delivery to the traumatized brain, HBO can reverse the lack of O2 that precipitates cellular energy failure and subsequent brain cell death. However, prior to a formal phase III definitive efficacy study, important information is required regarding optimizing the HBO treatment schedule to be instituted in terms of pressure, frequency and other parameters. The lungs in severe TBI subjects have frequently been compromised by direct lung injury and/or acquired ventilator pneumonia and are susceptible to O2 toxicity. It is essential to determine the most effective HBO dose schedule without producing O2 toxicity and clinical complications. This proposed adaptive clinical trial is designed to answer these questions and to provide important data to plan a definitive phase III efficacy trial.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000383',\n", " 'title': 'Hyperbaric Oxygen Brain Injury Treatment (HOBIT) Trial',\n", " 'pi': 'Gaylan L Rockswold, MD',\n", " 'fundingAmount': 1919650.0},\n", " {'abstract': 'The primary goal of the proposed study is to evaluate the potential of existing FDA-cleared tools to identify impairment, track recovery, and predict military readiness among active duty Service Members (SM) receiving rehabilitation for mild traumatic brain injury (mTBI). The study also aims to extend and advance scientific understanding of post-mTBI and to provide initial research findings as to the extent by which improvements in sleep may impact cognitive function in this population. To achieve these goals, our group will conduct an independent, longitudinal, observational study of SM completing mTBI rehabilitation. N=120 service members (n=40 subacute mTBI; n=40 chronic mTBI, n=40 uninjured controls) will be recruited for this study. Abbreviated midpoint evaluations will be performed at 4 weeks (all groups) and 8 weeks (chronic mTBI). Comprehensive evaluations will include TBI history, a battery of neurocognitive tests, vestibular/oculomotor screening, activity/sleep monitoring, neurobehavioral symptoms and Fusion-VR, a series of shooting adversary dual-task scenarios conducted in virtual reality with metrics derived from eye movements, EEG and operational performance.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000439',\n", " 'title': 'Identifying Objective Multimodal Predictors of Military/Operational Readiness and Recovery in Mild TBI Rehabilitation',\n", " 'pi': 'Mark Ettenhofer',\n", " 'fundingAmount': 965677.0},\n", " {'abstract': 'Intimate partner violence (IPV), the physical violence, sexual violence, psychological aggression, or stalking by a current or former intimate partner, is a significant public health concern affecting approximately 10 million people in the United States annually. Approximately 33% of women exposed to IPV report physical trauma resulting in heighted risk of head injury in this population. Recent work suggests that anywhere from 40-90% of women experience head trauma due to IPV. IPV-related head trauma is caused by blunt force trauma, being pushed or violently shaken, and/or strangulation, which can result in focal trauma or contusions, acceleration and deceleration injuries, as well as hypoxia and anoxia due to strangulation, respectively. Limited research has shown that women exposed to IPV with head trauma report higher depression, anxiety, and post-traumatic stress disorder symptomatology, as well as impaired cognitive function relative to women with IPV and no exposure to head trauma. Although the clinical features of repeated exposure to head trauma identified in IPV are similar to the effects observed in military traumatic brain injury (TBI) and sports-related concussion, limited work has been done to understand IPV-related head trauma, in particular its chronic cognitive and psychological effects as well as associated brain changes. Through a multi-site research collaboration consisting of members of the Enhancing NeuroImaging and Genetics through Meta-Analysis (ENIGMA) IPV Working Group, the proposed study will characterize the cognitive, psychological, and neural profiles of IPV-related head trauma. Semi-structured interviews will be used to obtain IPV specific information such as abuse and head trauma history and frequency. A comprehensive neuropsychological battery will be used to determine cognitive and psychological status, while sophisticated neuroimaging techniques will be used to characterize neural structure, function, and brain metabolites in IPV with exposure to head trauma relative to IPV without exposure to head trauma. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000424',\n", " 'title': 'Identifying the Cognitive, Psychological, and Neuroimaging Signatures of Head Trauma in Female Survivors of Intimate Partner Violence',\n", " 'pi': 'Carrie Esopenko',\n", " 'fundingAmount': 697432.0},\n", " {'abstract': 'As sport-related concussion (SRC) remains a significant health problem, there is growing concern that even repetitive head impact (RHI) exposure while playing contact sports (CS) may lead to a variety of worrisome outcomes, including neurobehavioral problems and long-term cognitive deficits. Although the number of head impacts per athlete in CS such as football can be very high, there are typically relatively few diagnosed concussions in a career. This fuels the worry that RHI may have cumulative effects on brain structure and function. An increasing realization is that brain injury is not an all-or-nothing phenomenon (e.g., presence or absence of concussion) but may also result from accumulated head impact. While the concept â\\x80\\x9csubconcussiveâ\\x80\\x9d is yet to be clearly defined, athletes who receive non-concussive blows are unlikely to undergo clinical assessment and will continue to play, exposing their compromised brains to further injury. Emerging evidence has demonstrated that RHI over even a single season in college or high school football players might be associated with measurable neurocognitive and neurophysiologic deficits without concussion. However, studies of RHI during routine CS exposure are still scarce. Findings from existing neuropsychological and neuroimaging studies are inconclusive and contradictory. To date, no clear link between the biomechanical dose of RHI exposure and their short- and long-term effects on the brain has been established. The extent to which RHI exposure differentially affects the developing brain remains unknown. A firm understanding of this problem is critical, because the accurate estimation of effects of the accumulation of RHI on brain structure and function could allow for the protection of young athletes.\\r\\nThe overarching goal of this research is to combine state-of-art neuroimaging and biomechanical metrics to identify key neurophysiological processes in young athletes associated with RHI exposure during routine CS. Based on our promising preliminary work and existing data, our central hypothesis is that RHI exposure during routine CS are related to abnormalities of underlying neurophysiological state, including alterations of functional connectivity and cerebral blood flow (CBF) and potential microstructural damage. This study introduces a novel metric: functional connectivity density mapping (FCDM) using advanced multiband functional MRI (fMRI). Specifically, FCDM enables simultaneous evaluation of the local and global functional connectivity, that is very suitable to assess functional abnormalities caused by RHI exposure on the developing brain. To fully evaluate brain function and neurophysiological status, we will combine FCDM with CBF measured using a 3D pseudo-continuous arterial spin labeling (pCASL) technique. To characterize potential microstructural damage, we will apply advanced multi-shell diffusion tensor imaging (DTI). Moreover, the quantification of recurring head impacts during routine CS seasons will be assessed using a state-of-art head impact monitoring mouthguard (IMM) system. The novel biomechanical cumulative metric based on the magnitude and frequency of head impact during each season will be employed. This prospective longitudinal study will include athletes in two age groups (middle school and high school) of two highly popular CS (football and soccer) in comparison to demographic closely matched noncontact sports (NCS) players. Each subject will be assessed four times: immediately before and after each of two consecutive practice/game seasons.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000394',\n", " 'title': 'Imaging Effects of Head Impact Exposure During Contact Sport',\n", " 'pi': 'Yang Wang, PhD',\n", " 'fundingAmount': 624373.0},\n", " {'abstract': 'iTAKL: Imaging Telemetry And Kinematic modeLing in youth football\\r\\nThis project will relate information about head motion during a hit in youth football to neurocognitive and imaging data to determine the effects of subconcussive impacts, and the true incidence of cognitive and objective imaging changes. We are obtaining MRI, MEG, cognitive measures, and detailed head impact data from sensors embedded within the helmets of the players. The long term benefit of the research will be to allow equipment designers, researchers, and clinicians to better prevent, mitigate, identify and treat injuries to help make youth league football a safer activity for millions of children.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000238',\n", " 'title': 'Imaging Telemetry And Kinematic modeLing in youth football (iTAKL-youth)',\n", " 'pi': 'Joseph A Maldijan, MD',\n", " 'fundingAmount': 646495.0},\n", " {'abstract': 'This prospective, observational study addresses the overarching hypothesis that brain dysfunction and structural injury are present at one month post- sports concussion (SC) in asymptomatic high school athletes who have been cleared by a licensed health provider (LHP) for return to play (RTP). We hypothesize that a biomarker measured from serum on the day of recruitment is prognostic of recovery by one month post-SC. High school athletes will be recruited within three days post-SC (n=24) from consecutive referrals to Memorial Hermann Sports Medicine Clinic in Houston. A comparison group of 24 high school athletes with orthopedic injury (OI) will also be recruited. Weekly assessment via telephone of post-concussion symptoms will identify athletes who are asymptomatic by one month and cleared for RTP. At one month post-injury both groups will return to clinic for neurobehavioral assessment, magnetic resonance imaging (MRI), diffusion tensor imaging (DTI) and resting state functional magnetic resonance imaging to measure functional connectivity (FC) of brain regions. Data analysis will test between-group differences in integrity of white matter tracts (DTI) and FC of brain regions. Biomarker levels will be analyzed in relation to brain imaging and neurobehavioral recovery at one month in SC group.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000228',\n", " 'title': 'Imaging and Biomarkers in Adolescents Cleared for Return to Play After Concussion',\n", " 'pi': 'Harvey Levin, PhD',\n", " 'fundingAmount': 193724.0},\n", " {'abstract': \"Project Summary/Abstract The effects of repetitive neurotrauma on women's health are almost entirely unknown. This study will examine the neurobiological, cognitive, and psychological effects of repetitive mild traumatic brain injuries (rMTBIs) in women who are subjected to intimate partner violence (IPV). IPV is violence perpetrated by a current or former spouse, partner, significant other, boyfriend, or girlfriend, and it is the most common form of violence against women. Globally, nearly 1 in 3 women over the age of 15 have experienced IPV, and several reports have shown that women subjected to IPV experience rMTBIs at alarmingly high rates. In one sample of 99 women, approximately half indicated a history of repetitive IPV-related TBIs, and these injuries were related to measures of both cognition and psychological health. It is believed by many, that the sequelae of these rMTBIs (e.g., cognitive difficulties) likely contribute to the challenges women experience in trying to escape an already complex and dangerous abusive situation. IPV-related rMTBI is a critical but unappreciated public health epidemic. Although there have been a number of calls for research on this topic, very few studies exist. Only our two published studies have used neuroimaging to examine the association between rMTBIs and markers of neurotrauma in women who have experienced IPV. Therefore, in a sample of women who have previously sustained IPV, we will collect resting state functional magnetic resonance imaging (MRI) and diffusion MRI data to assess functional and microstructural connectivity abnormalities, as well as magnetic resonance spectroscopy data and blood samples to test for altered levels of relevant neurometabolites and proteins. We will also collect cognitive, psychological, and post-concussion symptom measures to relate to these neurobiological measures. A better understanding of rMTBIs and their association with neurobiological abnormalities, cognition, and psychological health in women subjected to IPV will enable more efficacious care and treatment, and ultimately improve health outcomes for this highly underserved and often misunderstood population.\",\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000421',\n", " 'title': 'Impact of intimate partner violence-related mild traumatic brain injuries on neural, cognitive, and psychological health of women',\n", " 'pi': 'Eve M Valera, PhD',\n", " 'fundingAmount': 604239.0},\n", " {'abstract': 'We propose to improve cognitive difficulties in individuals with chronic TBI through training of strategies to accomplish complex real-life tasks. The interventions will be remotely delivered via virtual reality (VR) technology. The VR-technology allows the interventionist to simulate real-life tasks in an environment that allows careful modulation of task difficulty and collection of quantitative performance metrics. Remote deployment will make the intervention more accessible to individual who are resistant to clinical appointments or for whom transportation or work constraints render in-office visits impractical. If successful, we will be able to provide a set of tools to help an underserved group of wounded warriors. Improvements in daily life abilities will also likely impact the family lives of the individuals we are able to reach, as better daily life goal management, task performance, and task scheduling will have a positive impact for spouses, caregivers, and families of our military.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000386',\n", " 'title': 'Improving Cognitive and Functional Deficits after TBI Using Virtual Technology: Core Study',\n", " 'pi': 'Daniel C Krawczyk, PhD',\n", " 'fundingAmount': 2681400.0},\n", " {'abstract': 'We propose to improve cognitive difficulties in individuals with chronic TBI through training of strategies to accomplish complex real-life tasks. The interventions will be remotely delivered via virtual reality (VR) technology. The VR-technology allows the interventionist to simulate real-life tasks in an environment that allows careful modulation of task difficulty and collection of quantitative performance metrics. Remote deployment will make the intervention more accessible to individual who are resistant to clinical appointments or for whom transportation or work constraints render in-office visits impractical. If successful, we will be able to provide a set of tools to help an underserved group of wounded warriors. Improvements in daily life abilities will also likely impact the family lives of the individuals we are able to reach, as better daily life goal management, task performance, and task scheduling will have a positive impact for spouses, caregivers, and families of our military.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000362',\n", " 'title': 'Improving Cognitive and Functional Deficits after TBI Using Virtual Technology: Pilot Study',\n", " 'pi': 'Daniel Krawczyk',\n", " 'fundingAmount': 2681400.0},\n", " {'abstract': 'Background: Since 1989, the Traumatic Brain Injury (TBI) Model System (TBIMS) Program has enrolled over 12,000 adults with moderate to severe TBI in a National Database (NDB) and collected longitudinal follow-up data at 1, 2, 5, 10, 15, 20, and 25 years post injury. The Federal Interagency TBI Research (FITBIR) Informatics System has been established to accelerate TBI research by operationalizing precise definitions of common data elements (CDEs) selected for consistent use in TBI research, and to serve as a repository for housing CDEs and other variables collected across the many TBI research studies.\\r\\n\\r\\nObjective: The ultimate objective of this project is to incorporate data from the TBIMS NDB into FITBIR for easy access and linking to other TBI studies by the TBI research community.\\r\\n\\r\\nSpecific Aims: The specific aims of this proposed one year project are to evaluate: 1) the compatibility of the data sharing policies and procedures between the TBIMS and FITBIR, 2) the exact crosswalk between the TBIMS NDB and the TBI CDEs implemented by FITBIR, 3) the degree to which TBIMS variables can be converted to FITBIR CDEs, aliases, and new data elements, and these variables formatted in existing published or new FITBIR data forms, 4) the feasibility of downloading a de-identified version of the current TBIMS NDB to FITBIR, 5) the feasibility of adding the FITBIR Global Unique Indentifier (GUID) over time as new and existing patients are contacted for data collection, and 6) the feasibility of prospectively collecting more CDEs that are not currently variables in the TBIMS NDB by a sample of current TBI Model Systems.\\r\\n\\r\\nStudy Design: Project aims 1 and 2 will be accomplished by staff at the TBIMS National Data and Statistical Center (TBINDSC) reviewing policy documents and variable definitions established by both TBIMS and FITBIR; aims 3 and 4 will involve TBINDSC staff following and implementing the detailed protocols for preparing and submitting data to FITBIR; and aims 5 and 6 will require the TBINDSC staff managing the consent and data collection process at the TBIMS Centers to test implementation of the GUID and new CDEs.\\r\\n\\r\\nRelevance: The TBIMS NDB is the oldest and largest longitudinal TBI database with valuable information describing the natural course of TBI recovery and the trajectories of long-term outcomes. Incorporating these data into FITBIR would expedite its access by the broader TBI research community for research planning and comparative purposes, thereby facilitating the mission of FITBIR to accelerate TBI research.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000255',\n", " 'title': 'Integrating Traumatic Brain Injury Model Systems Data into the Federal Interagency Traumatic Brain Injury Research Informatics System',\n", " 'pi': 'Cynthia Harrison-Felix',\n", " 'fundingAmount': 259100.0},\n", " {'abstract': 'Long-Term Impact of Military-Relevant Brain Injury Consortium -Chronic Effect of Neurotrauma Consortium',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000392',\n", " 'title': 'LIMBIC-CENC Prospective Longitudinal Study',\n", " 'pi': 'William Walker',\n", " 'fundingAmount': 37175000.0},\n", " {'abstract': 'The proposed project, \\\\\"Neuropathology of CTE and Late Effects of TBI: Toward In-Vivo Diagnostics\\\\\" is a multi- center and multi-disciplinary study designed to dramatically increase our understanding of chronic traumatic encephalopathy (CTE) and other late effects of traumatic brain injury (TBI). TBI is a major public health concern in the US, as the current prevalence of TBI in the US is unprecedented. Some TBI survivors experience particularly poor outcomes as they age; these include accelerated cognitive and health decline, dementia, and in some cases, CTE. CTE is thought to be a tauopathy but has been described only in convenience samples of people with repetitive head trauma. CTE is incompletely described in individuals with mild, moderate and severe TBI. The population incidence and prevalence, risk factors, and causal role of multifocal tauopathy on associated symptoms are unknown. Overlapping clinical features, postmortem pathologies and patterns of involvement exist in TBI, CTE, and Alzheimer\\'s disease pose challenges to accurate diagnosis. Premortem diagnosis of CTE is currently impossible. The neuropathological consequences of single mild or moderate-severe TBI and its relationship with CTE and known dementias are unclear. The proposed project will leverage extensive resources from an ongoing population-based prospective cohort study of brain aging (Adult Changes in Thought; ACT, n=2,305) which includes excellent medical, behavioral, and genetic characterization of a cohort (20% of whom have a history of mild-moderate TBI) in addition to state-of-the-art neuropathology workup upon death. Neuropathological study of TBI effects can begin immediately in the existing ACT autopsy sample (n=489, 20% with TBI exposure). Additional cohorts of TBI- exposed individuals will come from the Brain Injury Research Center at Mount Sinai (n=150 individuals with moderate-severe TBI), the University of Texas Southwestern (n=50 retired boxers with repetitive TBI exposure), and the National Football League (n=76 retired players with repetitive TBI exposure). All participants in the proposed study (ACT and other sites) will undergo uniform harmonized neurobehavioral assessment (chosen to maximize correspondence with existing large-scale TBI and dementia studies), MRI scan, and genomic analysis. Those individuals who expire during the course of the study will undergo ex-vivo neuroimaging and extensive neuropathological exam using state-of-the-art techniques (such as Histelide) designed to quantify tau and A? in whole brain specimens. Only by examining postmortem pathology in a sample of individuals with varying levels of TBI exposure who are well characterized during life (as proposed herein) can postmortem pathology facilitate identification of in-vivo biomarkers that can act as diagnostic tools. This project represents the most systematic and scientifically rigorous effort to date to develop a more complete understanding of the long-term clinical and neuropathological sequelae of single and multiple TBI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000235',\n", " 'title': 'Late Effects of Traumatic Brain Injury (LE-TBI)',\n", " 'pi': \"Kristen Dams-O'Connor, PhD\",\n", " 'fundingAmount': 5005700.0},\n", " {'abstract': 'The apoE-lipoproteins complexes transport lipids throughout the body, including the brain. The brain is unable to effectively synthesize omega-3 and omega-6 PUFA, which in large part, have to be transported into the brain from blood. The literature suggests that these PUFA play a critical role in promoting neuronal repair and controlling the inflammatory milieu after TBI. Our preliminary data already provide compelling evidence that blood levels of PUFA containing lipids are altered in subjects with TBI in an APOE genotype dependent manner. While PL make up a large proportion of the blood lipid pool, there are other highly abundant lipids, such as CE and TG and mitochondrial specific lipids, such as acylcarnitine that also contain these omega-3 and omega-6 PUFA. A number of these lipids are packaged in lipoprotein-apoE complexes and once they reach the BBB, they are reprocessed for delivery into the brain via specific transporters (i.e. CD36, fatty acid translocase etc.). As such, it is possible that an examination of omega-3 and omega-6 PUFA within plasma lipid classes along with APOE genotype could provide an indirect estimate of their impact on the brain after TBI. These studies will provide critical information on whether omega-3 and omega-6 PUFA lipids could provide an objective diagnosis of mild TBI. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000378',\n", " 'title': 'Lipidomics for Identifying APOE4-Associated Biomarkers of AD-Related Cognitive Decline in TBI Patients',\n", " 'pi': 'Laila Abdullah',\n", " 'fundingAmount': 80000.0},\n", " {'abstract': 'Management of intracranial hypertension (ICH) in patients with severe traumatic brain injury (TBI) is crucial to their survival and optimal recovery. The evidence-based Guidelines for the Management of Severe Traumatic Brain Injury, 3rd Edition recommends use of intracranial pressure (ICP) monitors to assess ICH and know when and how to intervene. Unfortunately in most areas of the world there is no access to ICP monitor technology. This means that most people with severe TBI are treated without use of ICP monitoring. There are no guidelines and no literature on how to treat severe TBI without use of ICP monitors.\\r\\n\\r\\nThe objective of this project is to create guidelines for the treatment of severe TBI in the absence of ICP monitoring and test them. We propose to derive these guidelines by working with a team of clinicians that practice in austere environments in low-to-middle income countries (LMICs) and routinely make decisions based either on a treatment protocol, their clinical experience, or both. We will use a new, systematic and innovative technology and process to accomplish consensus for the guidelines among the clinicians. We will implement the Consensus-Based Guidelines (CBG) in resource-poor centers, some of which have prior exposure to less well developed ad hoc protocols for treatment of TBI, and others that do not have prior exposure. We will test the influence of the CBG on outcomes of severe TBI in a before/after design in these two sets of centers. In the first two years, patients will be treated according to the ad hoc protocol or according to individual clinician best judgment. Then the Guidelines will be developed, all sites will be trained in their use, and they will be used to guide treatment in all sites for the next 2 years. .We will evaluate the effect of using an ad hoc protocol by comparing outcomes between the two sets of centers before the Guidelines are developed. In each set of centers we will evaluate the effect of using the consensus-based guideline protocol compared to either no protocol or the ad hoc protocol by comparing the outcomes in the first and second periods. Finally, we will evaluate how much more the consensus-based protocol effects outcome than the ad hoc protocol by comparing the difference from the first to the second period between the two sets of sites In accomplishing the study objectives, we will create and test a guideline for the treatment of severe TBI that could be used globally to improve outcomes for these patients. We will validate in LMICs a new, systematic and innovative technology and process to accomplish consensus that was derived in an HIC. Finally, we will train personnel in centers new to research in how to conduct high-quality scientific studies, and will extend the training for the personnel with whom we have been working, solidifying previous capacity-building efforts, and initiating new efforts\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000247',\n", " 'title': 'Managing Severe TBI without ICP Monitoring-Guidelines Development and Testing (CBG Study)',\n", " 'pi': 'Randall Chesnut, MD, FCCM',\n", " 'fundingAmount': 543354.0},\n", " {'abstract': 'The purpose of the study is to examine the behavioral, physiologic, and neural response of human subjects to photoreceptor directed light stimulation. The eye is composed of several different light sensitive cells (rods, cones, intrinsically photosensitive retinal ganglion cells - ipRGCs). These different cell types are used both for visual perception, as well a non-visual functions of the eye (control of pupil size, the sense of uncomfortable brightness of light, and circadian rhythm). These functions may be altered in some disease states. Using a device that presents modulations of spectra of light under digital control, subjects will view the stimulus while making responses to perceptual questions, having their pupil size monitored with an infrared camera, or undergoing functional MRI brain imaging. Additionally we will collect genetic material from participants in order to determine the effect of genetic variation on the OPN4 molecule. These studies will be conducted in a normal control population, and patient populations with disorders hypothesized to interact with photoreceptor subtypes (patients with migraine headaches, concussion, and retinal disease).',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000322',\n", " 'title': 'Melanopsin specific contributions to photophobia in brain trauma',\n", " 'pi': 'Geoffrey Aguirre, M.D., Ph.D',\n", " 'fundingAmount': 1438150.0},\n", " {'abstract': \"Traumatic brain injury (TBI) is a risk factor for Alzheimer's disease (AD), the most common neurodegenerative disease and a major public health problem. The mechanistic link between TBI and AD is not clear, and there is a long latency between TBI and AD, during which individuals are largely asymptomatic. The clinician's ultimate goal is to define interventions to reduce the risk of AD associated with TBI, but this will require definition of biomarkers of disease activity, especially during the prolonged latent period between the TBI and onset of dementia. While a variety of candidate biomarkers exist, the recent discovery of extracellular microRNAs in cerebrospinal fluid represents an opportunity to rapidly define candidate biomarkers of TBI and TBI-associated neurodegeneration.\",\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000333',\n", " 'title': \"MicroRNA in cerebral spinal fluid as biomarkers of Alzheimer's disease risk after brain injury\",\n", " 'pi': 'Joseph Quinn',\n", " 'fundingAmount': 670803.0},\n", " {'abstract': 'This is a single center, prospective, observational study that will collect continuous Intracranial Pressure (ICP) monitoring data and serum biomarker samples on 25 patients with severe traumatic brain injuries. Other Standard of care information will be collected from the EMR including GOS-E scores.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000387',\n", " 'title': 'Microvascular Barrier Biomarkers to Predict ICP Therapeutic Intensity after Severe TBI (Phase I)',\n", " 'pi': 'Charles Cox, MD',\n", " 'fundingAmount': 2846530.0},\n", " {'abstract': 'Background: Mild traumatic brain injury (mTBI) affects ~18,000 US military personnel each year (DVBIC, 2019). As many as 5,400 of these personnel experience complex mTBI involving vestibular, cognitive, somatosensory, and/or autonomic dysregulation. If untreated, complex mTBI can result in chronic symptoms/impairment, and limited operational capabilities and duty restrictions (Belanger et al., 2011; Kontos et al., 2013). Interventions that target the involved domains in complex mTBI can improve symptoms, reduce impairment, and accelerate return to activity or duty (RTA/D) (Kontos et al., 2018). Although symptom specific interventions are commonly used by military medical personnel for complex mTBI, there are no well-designed studies looking at the effectiveness of these targeted treatments. We propose a multisite randomized controlled trial (RCT) of a targeted multidomain intervention for complex mTBI in military-aged civilians from the University of Pittsburgh/UPMC Sports Concussion Program (UPitt) and Inova Concussion Clinic (Inova). In so doing, the current proposal will address the â\\x80\\x9coptimization of treatment strategy based on patient classification to improve management of patients with mTBIâ\\x80\\x9d focus area of FY19/20 PH/TBIRP CTRR-CTA. The study will also â\\x80\\x9cdetermine indicators of successful recoveryâ\\x80\\x9d using comprehensive clinical outcomes and â\\x80\\x9ccorrelate (these outcomes with) brain functionâ\\x80\\x9d using a cost-effective, portable optical imaging tool- functional near infrared spectroscopy (fNIRS)- that has been shown to measure changes in brain activation during cognitive tasks and vestibular provocation (Hoppes et al., 2018; Kontos et al., 2014). ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000425',\n", " 'title': 'Multisite Randomized Controlled Trial of Pargeted Multidomain (T-MD) Interventions for Complex mTBI',\n", " 'pi': 'Anthony P Kontos',\n", " 'fundingAmount': 3155620.0},\n", " {'abstract': 'Numerous Veterans and civilians have seizures, which can be epileptic or nonepileptic in nature. Epileptic seizures are caused by abnormal brain cell firing. Nonepileptic seizures appear similar to epileptic seizures, but are associated with traumatic experiences and underlying psychological stressors. Both types of seizure are common and disabling, and many patients with seizures do not have adequate control resulting in loss of quality of life.\\r\\n\\r\\nIn this proposed 3-site study ( Providence, RI and Birmingham, AL), which are epilepsy centers with expertise both in epilepsy and psychogenic nonepileptic seizures (PNES), we will enroll 88 patients with video-EEG confirmed PNES and 88 with confirmed post-traumatic epilepsy (PTE) and will obtain functional neuroimaging before and after they receive a behavioral treatment - Cognitive Behavioral Therapy for Seizures. The functional neuroimaging studies in these 176 Veterans will be compared to 88 Veterans with traumatic brain injury without seizures to test the hypothesis that the faulty processing of emotions and stress in patients with PNES/PTE and abnormal brain connectivity have unique signals in patients with seizures compared to Veterans without seizures and that the neuroimaging signatures can be modified using behavioral intervention.\\r\\n\\r\\nImpact: This grant application for the first study investigating mechanisms of PNES and PTE will provide increased understanding of neural circuitry in PTE and PNES, which can inform PTE and PNES treatments and could change clinical neurologic and psychiatric practice for PTE and PNES.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000398',\n", " 'title': 'Neuroimaging Biomarker For Seizures',\n", " 'pi': 'William C LaFrance',\n", " 'fundingAmount': 3687750.0},\n", " {'abstract': 'Background: Care of moderate to severe combat-related traumatic brain injury (TBI) continues to pose enormous challenges sometimes compounded by the need to provide prolonged field care (PFC). TBI in the presence of other injuries requiring prolonged damage control resuscitation (pDCR) provides additional challenges. The austere, resource-constrained combat environment and lack of readily available diagnostic capabilities often lead to delayed recognition of the severity of TBIs, resulting in exacerbated damage and increased TBI-related disabilities. Cerebrovascular autoregulation (CAR) and intracranial pressure (ICP) monitoring has been used in cases of civilian TBI-related injuries to optimize cerebral perfusion pressure and blood flow to prevent secondary injury. However, technologies currently available to monitor CAR and ICP require invasive techniques and a high level of experience, while providing intermittent readings, making them impractical and unavailable in PFC and pDCR settings. Robust methods of noninvasive monitoring of CAR and ICP would allow for early application by combat medics, first responders, emergency departments, surgeons, and critical care staff. Improvement in screening and monitoring methods will provide a significant advantage and will equip combat medics with the tools necessary for earlier detection of life-threatening TBI and informed decisions regarding patient management. The proposed project aims to utilize ocular bioimpedance and ultrasound in a novel manner to assess CAR and ICP, utilizing the eye as a window to the brain.\\r\\n\\r\\nHypothesis: We hypothesize that ocular bioimpedance will track changes in cerebral blood volume and predict CAR impairment in a noninvasive and continuous manner, while ultrasound-assessment of ONSD using automated image analysis will enable an accurate noninvasive estimation of ICP.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000380',\n", " 'title': 'Novel Noninvasive Methods of Intracranial Pressure Assessment: Seeing the Brain Through the Eyes',\n", " 'pi': 'Hakam Tiba',\n", " 'fundingAmount': 1480170.0},\n", " {'abstract': 'In the US, there are more than four sports-related traumatic brain injuries every minute. Sports-related\\r\\nconcussion (SRC) in youth has received heightened attention due to emerging evidence that SRCs can affect\\r\\nacademics, behavior, and neurocognitive processes, such as working memory, concentration, processing\\r\\nspeed, and eye and motor function. A recent Institute of Medicine report on SRCs in youth revealed how little is\\r\\nknown about concussion in the young brain, and called for urgent attention to determine the incidence of SRCs\\r\\nin boys and girls by sport and demographic; research to identify unbiased, sensitive prognostic and diagnostic\\r\\nmetrics/markers; longitudinal studies to determine outcomes; and to delineate age- and sex-related\\r\\nbiomechanical determinants of injury risk. This innovative hypothesis-driven Bioengineering Research Grant\\r\\nwill generate objective diagnostic tools for use in concussion (Aim 1), new technologies to translate human\\r\\noutcome metrics to animals to provide a human-like platform to develop and test injury treatments in the future\\r\\n(Aim 2), and new knowledge regarding high-risk sports settings for youth (Aim 3) that will drive safety\\r\\nequipment design. The most innovative feature of the study is the integration across Aims to use BOTH male\\r\\nand female high school students and piglets in a deliberately parallel study design to determine optimal SRC\\r\\nassessments and identify mechanistic relationships between sex, loading conditions, and SRC symptoms. The\\r\\nintegration of human and animal studies which employ similar neuro-functional assessments leverages the\\r\\nstrengths of each approach: human studies ensure the study of biofidelic physiologic processes, and animal\\r\\nstudies allow application of specific loading conditions and outcomes not easily measured in living humans,\\r\\nsuch as neuropathology. Extensive pilot data establish feasibility and sample sizes in all Aims. In Aim 1 an\\r\\nunbiased numerical assessment suite for SRC will be developed and independently validated to establish\\r\\n≥95% sensitivity, and determine if these metrics are predictive of days-to-clearance for sports. Because the\\r\\nAim 1 objective metrics are nonverbal and effort-independent, they have been ?translated? to animals and\\r\\nreveal human-like physical, cognitive, and sleep symptoms of SRC in animals after rapid controlled head\\r\\nrotations. In Aim 2, single head rotations and multiple sub-concussive rotations are computationally scaled\\r\\nfrom teens to an immature large animal model of mild TBI, to identify the effects of sex and load frequency,\\r\\nmagnitude and direction on neuro-function, biomarkers and neuropathology. Aim 2 will identify biomechanical\\r\\nsettings of greatest risk for the young brain. The biomechanical insights from pigs in Aim 2 are translated to\\r\\nteens in Aim 3, where head impact sensors are used to quantify biomechanical load exposure by sport and sex,\\r\\nand the relationships between load exposure and neuro-functional metrics. The proposed studies in animals\\r\\nand humans will have broad impact ? by reducing the healthcare burden of SRC, enhancing accurate and\\r\\nobjective diagnosis, and identifying gender-specific prevention and intervention strategies.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000360',\n", " 'title': 'Objective Translational Multi-domain Early Concussion Assessment',\n", " 'pi': 'Susan Margulies',\n", " 'fundingAmount': 1038760.0},\n", " {'abstract': 'Objective and Rationale: Determining readiness for duty after concussion is essential for the safety of soldiers and their units. Currently, these decisions are primarily based on how soldiers feel and through the testing of their sensation, movement or thought processes, or physical tests of balance that may not reflect the types of activities that are common for service members. Recent progress in using wearable sensors that can be worn during daily activities now allow more accurate measurements of service membersâ\\x80\\x99 motions. Our long-term objective is to improve service membersâ\\x80\\x99 readiness for combat and quality of life by improving testing and treatment after concussion.\\r\\nWhat types of patients will it help and how will it help them? Over 305,000 service members have sustained a concussion over the last 16 years, and over 1 million civilians sustain concussions annually. This study seeks to improve the accuracy of diagnosing post-concussion movement problems and to provide better tests to determine when service members may be cleared to return to duty. To do this, we will use body worn sensors to test if the measurement of complex turning activities performed at the same time as thinking about something else (cognition) are better tests to measure improvement following treatment and as tools to determine if a service member is ready to return to duty. Based on previous research, we believe that measuring turning while thinking about something else will be better than the currently used tests in people after concussion because it more accurately reflects the demands of everyday function. We believe that this testing will be better at detecting problems than if sensation, balance, movement, and thinking were tested alone. In service members with concussion, lasting problems, even when seemingly mild, can have severe consequences. The ability to move under fire and to react with balance and skilled movements are critical components for the service memberâ\\x80\\x99s, and their unitâ\\x80\\x99s survival. Additionally, the unitâ\\x80\\x99s mission readiness depends on the health of every service member; withholding a service member from duty requires convincing evidence that they pose a risk to themselves or their unit.\\r\\nWhat are the potential clinical applications? To test our belief that turning measures will improve our ability to make accurate clinical decisions about concussion and return to duty, we will recruit participants with concussion symptoms that are have not gone away, healthy civilian subjects, and healthy active duty soldiers. As a final test, we will recruit soldiers referred to military rehabilitation centers for balance treatment following concussion. By performing this study at varied sites around the United States, we will improve the usefulness of measures of turning in both civilian and individuals on active military duty. The large number of people tested at the 6 sites will allow for the findings to be adopted into military and civilian concussion treatment settings and will benefit clinicians and patients through more accurate testing of symptoms.\\r\\nWhat is the projected time line? To achieve the objectives outlined in this study, we have planned to take 4 years to test the number of people that we hope to recruit.\\r\\nWhat is the likely contribution of the proposed research project to advance the field of complex mTBI? This project will advance the field of complex concussion by documenting that tests using sensors worn on the body will improve our ability to diagnose movement problems after concussion and improve the ability to evaluate improvement after rehabilitation. We will make our findings easily available to the public so other centers can also adopt the testing we find is most useful for return to duty assessment following concussion.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000390',\n", " 'title': 'Objective dual-task turning measures for return-to-duty assessments',\n", " 'pi': 'Laurie King',\n", " 'fundingAmount': 1669210.0},\n", " {'abstract': 'We conducted this observational prospective cohort study at two large level 1 pediatric trauma centers in the U.S. This study was the first to report the use of the Functional Status Scale (FSS) in children with TBI. PEDALFAST also supported the development and validation of computational tools (phenotypes) to identify neurosurgical and critical care events in databases containing information about children with TBI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000395',\n", " 'title': 'PEDiatric vALidation oF vAriableS in TBI (PEDALFAST)',\n", " 'pi': 'Tellen Bennett',\n", " 'fundingAmount': 700827.0},\n", " {'abstract': 'Blast injuries are deemed signature wounds of recent wars; 12%-23% of returning Service members report traumatic brain injury (TBI), the majority mild TBI (mTBI). Of military personnel exposed to explosions, up to 77% sustain permanent hearing loss and 60%-75% report tinnitus. Patients with blast-related TBI are at least 2.5 times more likely to sustain tinnitus than patients with non-blast TBI. Despite the high prevalence of tinnitus, it remains a subjective syndrome that is not well characterized and for which there is no definitive treatment. This application makes use of the applied (human) TBI-related research Congressionally Directed Medical Research Programs request for proposals to focus upon the area of hearing loss/dysfunction and tinnitus, with the prime goal being to better understand underlying neural mechanisms of tinnitus.Objective/Hypotheses: As a primary objective of the study, we propose to obtain Department of Veterans Affairs (VA) and Department of Defense (DoD) audiology exam data, administer (via telephone and internet) an interview and questionnaires (Objective 1). We hypothesize that: (1.1) deployment-related TBI will increase likelihood of post-deployment hearing loss, defined as a \\\\\"notch\\\\\" at 6000 Hz; (1.2) hearing loss will increase as a function of injury etiology (i.e., blast vs. non-blast) (Aim 1); and (2.1) deployment-related TBI (versus no TBI) will be associated with greater tinnitus symptom severity controlling for relevant variables (i.e., prior noise exposure, hearing loss, and post-traumatic stress disorder [PTSD] status); (2.2) current tinnitus severity will vary as a function of injury etiology (Aim 2). As a second objective, we propose to invite four groups of participants to San Diego for comprehensive assessments including Magnetoencephalogram (MEG) scans to better understand underlying brain mechanisms (Objective 2). We hypothesize that: (3.1) resting-state MEG activity from individuals with blast-related tinnitus will show hyper-activity in beta (15-30 Hz) and gamma (30-80 Hz) bands from the auditory cortices in superior temporal gyri (STG), but hypo-activity from ventro-medial as well as dorso-lateral pre-frontal cortex (vmPFC and dlPFC) when compared with asymptomatic control subjects, suggesting local disinhibition at the auditory cortex and lack of top-down inhibition from pre-frontal cortex (PFC); (3.2) compared to asymptomatic controls, individuals with tinnitus and no hearing loss will show distorted tonotopic organization in the auditory cortices related to the tone of their tinnitus to MEG steady-state sound stimuli and abnormal responses to MEG paired-click sound stimuli; (3.3) MEG slow-wave generation (suggesting TBI) from vmPFC and dlPFC areas will correlate with MEG measures of disinhibition in tinnitus in these regions. Hypo-activity in high frequency bands from vmPFC will also correlate with PTSD symptoms; (3.4) Abnormal MEG resting-state signals and evoked responses from auditory cortices in STG as well as PFC will correlate with tinnitus symptom scores, behavioral deficits, and audiology data including tinnitus pitch, severity matching, and tinnitus masking scores (Aim 3).',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000374',\n", " 'title': 'Patterns of Tinnitus and Hearing Loss Secondary to Blast Injury',\n", " 'pi': 'Dewleen G Baker',\n", " 'fundingAmount': 1494770.0},\n", " {'abstract': 'Given the numbers of deployed military personnel and post-9/11 Veterans with TBI, as well as civilian populations with TBI, there is an urgent need to understand the biological substrates associated with cognitive dysfunction, Early Onset Dementia (EOD), and other relevant conditions (e.g. depression/PTSD), that may moderate cognitive deficits after TBI. The FY17/18 PH/TBIRP CTRRâ\\x80\\x93CRA seeks research on mechanisms of conditions that inform potential interventions relevant to TBI rehabilitation and the mission of the JPC-8/CRMRP. Consistent with the goals and priorities of this funding mechanism, the overarching goal of this proposal is to assess TBI-related EOD, and cognitive impairments using a biomarker (genetics/proteomics) defined evaluation reflecting hypothesized mechanisms of cognitive impairment (hypodopaminergia/ inflammation) which are relevant to developing rehabilitation interventions aimed at prevention, mitigation, and recovery from deficits.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000397',\n", " 'title': 'Personal Biology and Comorbidity Impact on Post-TBI Cognitive Dysfunction and Neurodegenerative Disease',\n", " 'pi': 'Amy Wagner',\n", " 'fundingAmount': 2000000.0},\n", " {'abstract': 'Mild traumatic brain injury (TBI) is a common medical condition that occurs when a head injury causes someone to lose consciousness, feel dazed or confused, or be unable to remember events occurring immediately after the injury. While most individuals with mild TBI recover within weeks or months, some individuals with mild TBI report chronic symptoms such as difficulty with cognitive skills like attention, learning, or memory, along with other symptoms such as irritability or headache. Previous studies, including those conducted by our scientific team, have shown that cognitive rehabilitation can help patients with persistent symptoms after mild TBI return to full duty, work, school, and other important life activities. Specifically, cognitive rehabilitation can provide lasting improvements in thinking abilities, functional capacity, post-concussive symptoms, and quality of life after mild TBI. However, effective interventions are still out of reach for many service members and Veterans with TBI. For patients who have returned to duty, employment, or education, scheduling up to 60 hours of treatment (a typical treatment schedule in many settings) may not be feasible. Additionally, some patients may live in areas where it is burdensome to make numerous visits to a medical center. In response to these needs, our team has created a new treatment, Personalized Augmented Cognitive Training (PACT). PACT compresses treatment into six hours of once-weekly personalized, one-on-one training by selecting treatment modules based on patient needs and prioritiesâ\\x80\\x94substantially reducing the total amount of time required to complete treatment. PACT can be offered either in-person (in clinic) or via home-based video telemedicine (i.e., Skype), depending upon patientsâ\\x80\\x99 preferences. Additionally, PACT includes training and encouragement for service members and Veterans to make self-directed use of mobile apps that train cognitive skills and strategies. The primary goal of this study is to evaluate whether PACT is effective at improving cognition, symptoms, and functional outcomes among military service members and Veterans with a history of mild TBI. We also seek to learn more about factors that can enhance or interfere with treatment, such as number of previous TBIs, presence of post-traumatic stress; and choice of in-person vs. video telemedicine delivery of care.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000404',\n", " 'title': 'Personalized, Augmented Cognitive Training (PACT) for Service Members and Veterans with a History of TBI',\n", " 'pi': 'Elizabeth Twamley',\n", " 'fundingAmount': 1997020.0},\n", " {'abstract': 'The long-term goal is to implement a clinically feasible military relevant task that can aid clinicians in RTD decisions following concussion. The overall objective is to assess the performance-based POWAR-TOTAL, building on standardized scoring and procedures from the Assessment of Military Multitask Performance (AMMP) study. This test will improve clinical feasibility over AMMP tactical agility tasks by requiring less space and time while using less expensive smartphone technology as instrumentation. The POWAR-TOTAL incorporates the most sensitive and provocative aspects of multiple AMMP tasks. The central hypothesis is that POWAR-TOTAL will be sensitive enough to identify clinically significant movement differences using a combination of Principal Component Analysis, Fast Fourier Transform and Support Vector Machine analysis that can occur in real time. This approach is reliable and valid, as previous studies with laboratory equipment found the such analysis differentiated those with injury from those without at >.80.Pilot data using our smartphone accelerometer and application further supports our hypothesis. The rationale for our project is to validate the POWAR-TOTAL in a manner that allows for portability, refining a RTD test that can be used to provide immediate feedback to clinicians and SMs alike.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000379',\n", " 'title': 'Portable Warrior Test of Tactical Agility: POWAR-TOTAL',\n", " 'pi': 'Karen McCulloch',\n", " 'fundingAmount': 745139.0},\n", " {'abstract': 'The clinical foundation of this study is based on the importance of cerebral hemodynamics in the diagnosis and management of TBI. Deficits in cerebral hemodynamics following a severe TBI are well established and recently have been shown to be affected in mild TBI as well. Recent research interest in mild TBI or concussion driven by both increased military and civilian awareness and has focused on non-invasive assessments of cerebral hemodynamics including specific sequences of MRI (functional MRI (fMRI), arterial spin labeling (ASL)), single photon emission computed tomography (SPECT), PET, and perfusion CT.\\r\\n\\r\\nStudies have supported the use of TCD in the ER and pre-hospital setting for prognosis / detection of deterioration of all severities of TBI. For mild and moderate TBI in the ED, both Jaffres et al. (Jaffres et al., 2005) and Bouzat et al.(Bouzat et al., 2011) investigated the use traditional TCD features for prognostic purposes. Jaffres showed that PI was able to broadly differentiate patients who had deteriorated from those who did not. Bouzat later confirmed these results and reported 89% overall accuracy in identifying patients who would deteriorate.\\r\\n\\r\\nDespite these positive results for TBI, recommendations by DoD, established clinical use (reimbursement, guidelines, etc.), and technical advantages (portable, non-invasive, and inexpensive) TCD has not gained widespread adoption because of specific limitations. These limitations include the requirement of an expert technician and limited data utilization. Neural Analytics is developing a platform that addresses these limitations and extends the use of traditional TCD ultrasound.\\r\\n\\r\\nThis project will compare the diagnostic prediction capability of a transcranial Doppler ultrasound (TCD) based machine learning analysis platform to CT imaging of subjects with moderate and severe TBI. Additionally, the feasibility to collect TCD data using an automated headset platform for military use will be demonstrated.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000400',\n", " 'title': 'Precision Intracranial Bleed Triage and Monitoring (CT+)',\n", " 'pi': 'Robert Hamilton',\n", " 'fundingAmount': 4438320.0},\n", " {'abstract': 'Purpose: Traumatic brain injury (TBI) and posttraumatic stress disorder (PTSD) are linked to worsened physical and mental health, functional impairment, and greater healthcare utilization. TBI is a point of injury diagnosis, but Post Concussive Syndrome (PCS) is analogous to the more persistent PTSD. Current treatments are often ineffective, and many afflicted military service members (SMs) never return to duty. Upon return from deployment, many SMs experience an initial honeymoon period during which symptoms are limited in number and scope, but this is frequently followed by a sharp increase in symptoms within months. Identification of independent predictors of PTSD and PCS upon return from deployment could facilitate early intervention to prevent disability. We therefore recruited a cohort of service members from across the nation, broadly representative of the military, and performed a comprehensive baseline assessment, including demographics, neuropsychological assessment, genetic and neuroendocrine assays, brain imaging and synchronization, vestibular, olfactory, and psychophysiologic measures, of SMs within 2 months post- deployment. Subsequent follow-up evaluations at 3, 6, and 12 months assessed for the interim development of PTSD, depression or PCS.\\r\\nResearch Design: A prospective cohort study involving 81 healthy combat veterans recruited within 2 months after return from Iraq or Afghanistan, with serial evaluations to assess for development of PTSD, depression or PCS, to then determine the baseline factors most strongly predictive of these outcomes. \\r\\nMethodology/Technical Approach: Questionnaires, imaging, serum catecholamine assays, and baseline physiologic measures were repeated 3, 6, and 12 months after the baseline assessment. Of 103 screened participants, 85 were enrolled, but 4 were therefore excluded because they already met criteria for PTSD, resulting in a cohort of 81. A total of 69 participants completed at least one follow up assessment, including 54 at 3 months, 39 at 6 months, and 57 at 12 months. Cumulatively, we identified an outcome of interest in seven participants: 5 with PTSD, 1 with depress and 1 with PCS. We are now continuing with serial univariate and multivariate analyses to identify the baseline measures most strongly associated with subsequent outcomes of interest.\\r\\nResults: We identified significant associations between PTSD symptoms at baseline and psychophysiologic responses to stressful stimuli. We also documented fMRI evidence that those with more PTSD symptoms had to exert greater control to stay on task in the face of emotional distractors. Using a nested case-control analysis, we found differences in fractional anisotropy in a key brain area in participants with combat TBI, suggesting a potential mechanism for subsequent symptoms of PCS and functional impairment. Finally, we also found preliminary evidence that heart rate variability may predict subsequent PTSD. \\r\\nConclusions: Analyses are still in progress to document the most robust predictors of neurocognitive impairment after combat, but our preliminary analyses identify a number of promising factors that may help us to risk stratify service members after deployment\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000254',\n", " 'title': 'Predictors of PTSD and Post Concussive Syndrome in OIF/OEF Veterans (CNRM)',\n", " 'pi': 'MIchael Roy',\n", " 'fundingAmount': 264453.0},\n", " {'abstract': 'The majority of mild TBI patients report self-described sensory dysfunction and yet they often pass standard eye and hearing exams. Further, the 80% of TBI patients diagnosed as mild TBI appear normal on a standard CT or MRI scan. There is an inherent variability of trauma; no trauma cases are exactly alike. This variability in combination with the lack of apparent damage in mild TBI patients has made diagnosis of these patients challenging. The lack of an objective, quantitative clinical metric for these changes in sensory function also prevents the initiation of clinical trials. Furthermore, it highlights the lack of understanding of the underlying cause of sensory dysfunction. Without an understanding of mechanism, rational therapies cannot be developed. The goals of this study are to identify sensitive, objective, quantitative tests to serve as diagnostics, to identify outcome measures for sensory dysfunction in TBI patients, and to better understand the physiological basis of sensory dysfunction. We propose that by assessing TBI patients in a Level 1 Trauma Center, two Veterans Administration Hospitals, and a military base housing a satellite of the National Intrepid Center of Excellence, we will recruit sufficient numbers of subjects to definitively identify assessments that are sensitive and specific enough to diagnose sensory dysfunction in complex TBI patients. We hypothesize that combining objective structural and functional assessments in the same subjects is more likely to overcome the inherent variability of trauma and yield useful diagnostic metrics than would each test separately. Thus, we propose that a combination of assessments, including a single metric that indexes integrative sensory abilities, and utilization of new, sensitive algorithms may be required for accurate diagnosis.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000372',\n", " 'title': 'Quantitative Evaluation of Visual and Auditory Dysfunction and Multi-Sensory Integration in Complex TBI Patients',\n", " 'pi': 'Tonia Rex, Ph.D.',\n", " 'fundingAmount': 4000000.0},\n", " {'abstract': \"Mild traumatic brain injury (MTBI) also known as concussion is a major public health problem with close to 1.5 million cases a year that can result in long-term complications including Post-Concussive Syndrome and Chronic Traumatic Encephalopathy. Concerns such as these have brought MTBI to public attention. There is evidence from our group and others that even a single concussive episode can cause long-term changes in the brain that can be visualized by Magnetic Resonance Imaging (MRI).\\r\\nBrain iron is highly regulated and has been shown to be abnormal after traumatic brain injury in both animal\\r\\nand human studies. Though iron is essential for a number of normal cellular processes, it is also implicated in a number of neurodegenerative disorders as causing toxicity to the brain via the production of oxygen free radicals. Abnormal iron in the brain associated with traumatic brain injury may be a link between trauma and a host of neurodegenerative conditions which have been associated with trauma, including Chronic Traumatic Encephalopathy and Alzheimer's Disease. We propose to use MRI, including a novel technique called Magnetic Field Correlation, to quantify regional brain iron in vivo after a single concussive episode and to follow changes in brain iron over time. This application has a translational focus and we will study the relationship between brain iron and long-term changes in brain structure as well as the predictive value of brain iron in determining functional changes in the brain and clinical outcome. Identifying and understanding secondary injury such as toxicity from abnormal brain iron is a critical next step in the study of MTBI. Secondary injury cascades can potentially be slowed or stopped and, as such, are excellent potential targets for future development of therapy. The primary long-term objective\\r\\nof this application is to examine the role of brain iron in MTBI using MRI. If successful, this work would open up avenues for potential treatment.\",\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000226',\n", " 'title': 'Quantitative MRI and 1H MRS in Traumatic Brain Injury',\n", " 'pi': 'Yvonne Lui, MD',\n", " 'fundingAmount': 588506.0},\n", " {'abstract': 'A prospective, single-blind, four-group multi-center randomized controlled trial (RCT) of targeted rehabilitation exercises for vestibular symptoms and impairments (T-REV) in civilians with mild traumatic brain injury (mTBI) will be conducted at the University of Pittsburgh Medical Center Sports Medicine Concussion Program (UPitt). The four treatment groups will consist of the factorial combinations of low (30%) and high (70%) intensity of exercise crossed with low (12-18 min, 1x/day) and high (12-18 min, 2x/day) frequency. A total of 125 participants at the University of Pittsburgh, aged 18-50 years will be enrolled across years 1-4, with approximately 125 participants completing the whole study. After potential participants with mTBI are screened for the vestibular clinical profile, using domain-specific tests and measures, and enrolled into the study, they will complete primary and secondary outcome measures and receive a home exercise program that a) targets their individual deficits, and b) is of the appropriate intensity and frequency for their randomly assigned treatment group. Participants will return for in-clinic visits once per week to receive treatment and progress their exercises.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000406',\n", " 'title': 'Randomized Controlled Trial of Precision Vestibular Treatment in Military Personnel with mTBI',\n", " 'pi': 'Anthony P Kontos',\n", " 'fundingAmount': 2207390.0},\n", " {'abstract': 'Objectives: Control of balance requires complex integration of sensory and motor systems. In the clinic or in the field, balance measurement is often over-simplified, preventing balance deficits from being identified and treated after mTBI. Our central hypothesis is that chronic balance deficits after mTBI result from impairments in central sensorimotor integration that may be helped by rehabilitation. There are two objectives of this proposal; the first objective is to characterize balance deficits in people with mTBI. The second objective is to use a novel ABF device to improve measures central sensorimotor integration and balance control. Plan: The proposed 4-year study has two parts: 1) Cross-sectional study (Aim I: Balance Assessment) to identify and characterize maladaptive balance control strategies after mTBI compared to healthy controls and 2) Interventional randomized pilot study (Aim II: Balance Rehabilitation) using a novel ABF rehabilitation technique to ameliorate maladaptive balance control strategies after TBI. Subjects in Aim II will be a subset from Aim I and studies will occur simultaneously. Methods: I) Balance Assessment: To characterize balance deficits in people with mTBI who have chronic, non-resolving balance deficits compared to healthy control subjects without a history of mTBI. We hypothesize that a) objective measures of central sensorimotor integration, static and dynamic balance will better distinguish people with mTBI from control subjects than clinical measures, b) a subset of people with mTBI will have abnormal CSMI test measures, even without peripheral vestibular or ocular motor deficits c) the relationship between poorer static/dynamic balance performance and mTBI is regulated/mediated by CSMI. We will test 130 subjects between the ages of 21 and 50; 65 with chronic (> 3 months) mTBI and non-resolving balance deficits and 65 healthy age and gender matched control subjects without a history of mTBI. We will obtain objective measures of static and dynamic balance using wearable inertial sensors and determine how these measures relate to central sensorimotor integration. We will also obtain laboratory measures of peripheral vestibular function and ocular motor function to help classify people and to consider as potential covariates in rehabilitation efficacy. II) Balance Rehabilitation: To determine the efficacy of a novel, ABF balance rehabilitation program to improve central sensorimotor integration, static and dynamic balance, and functional activity in patients with chronic mTBI. We hypothesize that a) CSMI scores will improve with rehabilitation and ABF will increase the improvement of CSMI scores beyond the standard of care, b) ABF intervention will improve objective summary measures of balance and c) people with central sensorimotor integration impairment will show sustained improvement in CSMI scores and balance after rehabilitation. We will randomize 40 subjects between the ages of 18 and 60; 65 with chronic (> 3 months) mTBI and non-resolving balance deficits from Aim I who have abnormal CSMI into either the ABF rehabilitation group or the standard of care group. People will be tested before and after a 6-week intervention period and again 6 week later to determine long-term changes. Normal/abnormal vestibular and ocular motor function will be used as covariates to determine if peripheral deficits affect the efficacy of ABF rehabilitation.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000318',\n", " 'title': 'Rehabilitation of Central Sensory Impairments for Balance in mTBI',\n", " 'pi': 'Laurie King',\n", " 'fundingAmount': 1993520.0},\n", " {'abstract': 'Traumatic brain injury (TBI) in athletes is a major and increasingly recognized public health problem. The presumed pathologic basis of the injury is multifocal microstructural traumatic axonal injury (TAI), which can be detected in vivo using diffusion tensor MRI (DTI). These structural changes have both short-term and long-term cognitive consequences. Our preliminary studies show that amateur soccer players do head the ball frequently, up to > 5,000 per year, and those who head more than 1,000- 1,500 times per year are at increased risk for structural (TAI) and functional (poorer cognitive performance) changes. Heading exposes the brain to repeated low-level (\\\\\"subconcussive\\\\\") trauma. It is known that multiple head injuries in close succession are associated with worse outcomes. Additional work is needed to define exposure-response relationships for soccer heading, the time course for the onset and recovery from these structural and functional effects and particularly vulnerable populations. Herein, we use 3 integrated study designs to determine the influence of heading on brain structure and function. In a cross-sectional study (Aim 1), we assess the relationship of heading over the previous year to structural (TAI) and functional (cognition and post-concussion symptoms (PCS)) measures in a large sample (n=400) of amateur soccer players. To assess causality, we propose a longitudinal study to investigate the incremental effects of heading on changes in TAI, cognition and PCS over 2 years of follow-up (Aim 2). To assess the short-term relationship between heading and day-to-day variability in cognitive function and PCS as well as the predictive value of intensive measurement, we will assess heading, cognition and PCS on a daily basis for 14 days every 3 months using a hand-held device in a substudy of 100 players. We will also assess a number of potential modifiers of the association between heading and brain structure and function (e.g., Apolipoprotein E4 genotype). ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000220',\n", " 'title': 'Soccer heading: potential for brain injury and opportunities for its mitigation',\n", " 'pi': 'Michael Lipton, MD',\n", " 'fundingAmount': 690106.0},\n", " {'abstract': 'Evidence-based management of youth sports-related concussion (SRC) is limited by the lack of age-appropriate evaluation methods with validity for assessing recovery of brain physiology. The overall goal of this project is to evaluate the utility of a novel, clinically-relevant measure of somatosensory information processing (SSIP) as a biomarker for youth SRC and recovery from SRC with relevance for evaluating the neurologic basis of SRC and recovery from SRC. The SSIP testing battery makes use of inexpensive, portable technology to deliver vibrotactile stimuli to the fingertips and does not require baseline data, making it readily applicable for widespread use in schools and on sidelines. The aims of this project are to 1) evaluate the sensitivity of SSIP to youth SRC and recovery from SRC and 2) to assess the neurological basis of SSIP in youth with SRC through magnetic resonance spectroscopy (MRS) evaluation of GABA and glutamate in sensorimotor cortex. We will evaluate 25 youth aged 13-17 years with SRC within 1 week post-injury and again 2-3 weeks post-injury; youth who remain symptomatic from SRC at the second visit will return for a third visit after they have achieved clinically recovery. We will compare SSIP and MRS GABA and glutamate in youth with SRC within 1 week post-injury to that of age- and gender-matched peer athletes with no history of concussion and will evaluate for correlation of SSIP with MRS GABA and glutamate. We will evaluate changes in SSIP and MRS in association with clinical recovery from SRC versus persisting symptoms from SRC. Lastly, we will evaluate whether alterations in SSIP or MRS GABA or glutamate persist even after clinical recovery from SRC, as this may represent a marker for predicting short-term outcome from subsequent SRC and/or emergence of late concussion-related deficits (such as chronic traumatic encephalopathy). This project will determine the utility of further work using this novel methodology in youth SRC.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000251',\n", " 'title': 'Somatosensory processing -- assessing youth sport-related concussion and recovery',\n", " 'pi': 'Stacy Suskauer',\n", " 'fundingAmount': 202094.0},\n", " {'abstract': \"It is estimated that up to 320,000 service members in OEF/OIF have sustained some form of traumatic brain injury. The lack of an objective measurement tool for evaluation and monitoring of a suspected mild traumatic brain injury (mTBI) is of great concern to the military. Accurate diagnosis of an acute mTBI should involve detailed head injury history documentation and an assessment of a range of domains, including motor deficits. Assessments of motor functioning can detect neurophysiological impairments which may negatively impact the military personnel's ability to function in full military capacity. The NeuroCom Sensory Organization Test (SOT) is the current gold standard for assessing mTBI-related motor impairments; however, the equipment?s size and logistical footprint makes it impractical for field deployment. An objective and clinically valid, yet field deployable assessment of motor functioning would greatly assist military medical personnel with return to duty (RTD) decisions. The AccWalker smartphone app taps into accelerometry and orientation data in order to assess an individual's neuromotor functioning by focusing on movement variability. Clinical research shows increased movement variability emerges in motor tasks after a neurological insult. This is likely due to reduced capacity of the central nervous system (CNS) to control movement. Thus, variability in motor tasks such as walking, has been used to identify neurological impairment from mTBI. Gait tasks have been used to identify motor impairment following mTBI, however, a large overground space or a treadmill is needed to properly assess gait variability. In pursuit of a simple motor task that encompasses a movement variability profile comparable to gait behavior, we adopted a stepping-in-place task. Gait and stepping-in-place exhibit similar variability characteristics, making the stepping-in-place task a proxy for gait behavior. Therefore, the study will seek to assess the use of the AccWalker smartphone app during a stepping-in-place task as a means of screening for mTBI-related motor impairments.\",\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000324',\n", " 'title': 'TBI Assessment of Readiness using a Gait Evaluation Test (TARGET): Development of a Portable mTBI Screening Device',\n", " 'pi': 'Christopher Rhea',\n", " 'fundingAmount': 959639.0},\n", " {'abstract': 'The Traumatic Brain Injury Endpoints Development (TED) Initiative is a 5-year, Department of Defenseâ\\x80\\x93funded project that is working toward the ultimate goal of developing better designed clinical trials, leading to more precise diagnosis, and effective treatments for traumatic brain injury (TBI). These subjects are the Friend Controls for the TRACK-TBI U01 study.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000384',\n", " 'title': 'TBI Endpoints Development (TED)',\n", " 'pi': 'Geoffrey Manley',\n", " 'fundingAmount': 17109800.0},\n", " {'abstract': 'The purpose of this multi-site study is to evaluate the efficacy of a high omega-3/low omega-6 dietary intervention (the H3-L6 Diet) vs. a Control Diet in reducing headache pain and improving function in soldiers, veterans and military healthcare beneficiaries with post-traumatic headache (PTH). In addition, the study will examine the effects of the diet interventions on anti-nociceptive and pro-nociceptive lipid mediators derived from omega-3 and omega-6 fatty acids.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000359',\n", " 'title': 'Targeted Alteration in omega-3 and omega-6 fatty acids for post-traumatic headache (Nutrition for PTH)',\n", " 'pi': 'Kimbra Kenney',\n", " 'fundingAmount': 3252790.0},\n", " {'abstract': 'TEAM-TBI is a research study that brings together TBI patients, advanced evaluation methods, and world class experts in a multi-faceted study to address the heterogeneity of TBI and the effects a variety of self-help strategies might have on TBI outcomes. The study involves a comprehensive 3-4 day intake evaluation, followed by a variety of remotely performed tasks during a 1-6 month follow-up period. These tasks are individualized to each participant based on intake evaluations and reviewed by investigators specialized in each trajectory (i.e. cognitive therapy, vestibular therapy, sleep therapy, etc.). Participants are monitored during the remote portion via telemonitoring and telemedicine modalities, and return after approximately 6 months for a follow-up to their initial assessment.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000321',\n", " 'title': 'Targeted Evaluation, Action, and Monitoring of Traumatic Brain Injury (TEAM-TBI)',\n", " 'pi': 'David O Okonkwo, MD, PhD',\n", " 'fundingAmount': 4272440.0},\n", " {'abstract': \"Studies suggest an increased risk of Alzheimer's disease (AD) and chronic traumatic encephalopathy (CTE) after traumatic brain injury (TBI). Greater understanding of the chronic effects of TBI may lead to new therapies. This proposal will add a TBI cohort, tau PET imaging and 7T-MRI to the Australian Imaging Biomarkers and Lifestyle - Veterans study (AIBL-VETS) of post traumatic stress disorder and neurodegeneration. AIBL researchers have an outstanding international record in the development of tau and amyloid PET imaging.\",\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000358',\n", " 'title': 'Tau and beta-amyloid deposition, micro hemorrhage and brain function after traumatic brain injury in war veterans.',\n", " 'pi': 'Christopher Rowe',\n", " 'fundingAmount': 738421.0},\n", " {'abstract': 'Objectives: The primary objective of the Telephone Delivery of Cognitively Augmented Behavioral Activation (Tele-CABA) intervention with Veterans who have a history of traumatic brain injury (TBI) is to reduce their negative cognitive and psychiatric health outcomes and promote personal resilience. The long-term objective of this study is to develop an accessible and acceptable intervention that can be broadly disseminated to address the complex rehabilitation needs within this population of Veterans.\\r\\n\\r\\nPlan: This study capitalizes on the resources and scientific and clinical expertise available at the VA Portland Health Care System (VAPORHCS) Neuropsychology Clinic and the VA Rehabilitation Research &\\r\\nDevelopment (RR&D) funded National Center for Rehabilitative Auditory Research (NCRAR). Participants will be Veterans and Service members with a history of TBI enrolled for health services at any VA medical center\\r\\nor satellite program. A total of 192 participants will be enrolled. Participants will be randomly assigned to either the treatment (Tele-CABA) or a usual-care control group (UC).\\r\\n\\r\\nMethods: Participants randomly assigned to the Tele-CABA group will receive the manualized intervention delivered by telephone over the course of 10 weekly, 60-minute sessions. Participants in the UC group will continue to receive their regular medical, psychiatric, and psychotherapeutic care. All participants will undergo evaluation at baseline, post-treatment, and 6-months following the completion of treatment. At baseline, participants will complete a diagnostic TBI interview, self-report questionnaires measuring cognitive and psychiatric symptom severity including the Neurobehavioral Symptom Inventory (NSI) and a brief cognitive screening battery. Self-report questionnaires and cognitive testing will be repeated at post-treatment and\\r\\nfollow-up. We will evaluate the following primary outcomes: cognitive symptoms, psychiatric distress symptoms, utility of compensatory strategies, self-efficacy, adaptive functioning, quality of life, and treatment satisfaction.\\r\\n\\r\\nRelevance to VAâ\\x80\\x99s Mission: TBI is a significant cause of disability with long-term physical, cognitive, and mental health consequences. Interventions designed to address the complex needs of Veterans with TBI are necessary to improve recovery and community reintegration. Few interventions exist, and even fewer provide access for Veterans who are unwilling or unable to obtain services in urban outpatient settings. Once established, the Tele-CABA intervention could be disseminated nationally and provided during deployments to active duty Service members and Veterans, resulting in more immediate care. Data from this study will be contributed to the Federal Interagency Traumatic Brain Injury Research (FITBIR) informatics system to support ongoing comparative research on TBI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000391',\n", " 'title': 'Telephone Delivery of Cognitively Augmented Behavioral Activation (Tele-CABA) for Veterans',\n", " 'pi': 'Megan Callahan',\n", " 'fundingAmount': 1434080.0},\n", " {'abstract': 'Objective: The proposed project is designed to examine the epidemiology of epilepsy and mild traumatic brain injury (mTBI) in Post-9/11 Veterans using available data from the Departments of Defense (DoD) and Veterans Affairs (VA), and primary data collection. Research Plan: Comprehensive evaluation of epilepsy in Military and Veteran populations should: 1) incorporate both DoD and VA data in a longitudinal record, if possible; 2) include primary data collection including lifetime history of TBI and patient reported outcomes for a sample of the population; and 3) include imaging and neuropsychological evaluations for a small subset of the sample for whom lifetime TBI status is known. Methods: In Aim 1, we will identify a cohort of all Post-9/11 Veterans who receive VA Care (2 or more years 2002-2015), obtain VA and DoD health care system data for that cohort, and identify epilepsy and TBI over the longitudinal data record. Using those data we will examine the relationship between TBI severity (with emphasis on mTBI) and epilepsy. From that cohort we will select a sub-sample of Veterans based on mTBI and epilepsy status, conduct telephone interviews to identify lifetime TBI exposure (including mechanisms of exposure), seizure history and functional status related to work, and physical, mental health and social functioning. We will use these data in Aim 2 to determine if deployment related mTBI exposure is associated with epilepsy after controlling for greatest lifetime TBI severity, and if blast-related TBI (BR-TBI)/multiple mTBI are associated with increased odds of epilepsy compared to non- BR-TBI. In Aim 3, we will compare self-reported work, physical, mental health and social functional status in a stratified random sample of veterans with epilepsy to controls without epilepsy. For the final aspect of the study we will enroll 200 individuals who were surveyed and who are interested in participating in the Chronic Effects of Neurotrauma Consortium (CENC) Longitudinal study where they will undergo magnetic resonance imaging, neuropsychological testing, collection of blood for later biomarker analysis and other clinical evaluations. Clinical Relevance: Together these aims address the DoD Epilepsy Research Program, Idea Development Award (ERP-IDA) focus area of epilepsy epidemiology using a comprehensive approach that ranges from population-based surveillance using existing data, to a case-control approach that more carefully characterizes epilepsy cases and controls to evaluate patient reported outcomes that have been identified by our patient advisory board as being relevant, to a comprehensive longitudinal evaluation that uses the power of cutting-edge neuroimaging (and eventually biomarker/genomic data developed through CENC) that may provide insights into post-traumatic epilepsy (PTE) etiology and ultimately identify specific aspects of mTBI (and other risk factors) that will allow early identification of those at greatest risk of PTE.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000361',\n", " 'title': 'The Epidemiology of Epilepsy and Traumatic Brain Injury',\n", " 'pi': 'Mary Jo Pugh, PhD, RN',\n", " 'fundingAmount': 2199190.0},\n", " {'abstract': '\\tInflammation has been implicated as an important player in both traumatic brain injury (TBI) and Alzheimerâ\\x80\\x99s disease (AD). TBI has been described as a risk factor for AD. Our group and others have described an inflammation related gene, TREM2 as an important player in AD pathology. Genetic variants in inflammation related genes, such as TREM2 and APOE, are strongly associated with AD suggesting the inflammation may be influenced at the DNA level. Our group has preliminary data that suggests that alteration of DNA by methylation of both APOE and TREM2 is associated with AD. Since methylation of DNA can change with exposure to brain injury and since methylation of DNA from blood may be an easily accessible biomarker of poor outcome after TBI, remaining critical questions include: Is TBI associated with altered methylation of inflammation related genes, such as TREM2 and APOE? Do active fighters have change in TREM2 methylation? For example, is there a methylation change present in fighter DNA when comparing the first visit to the second visit (after one year), or compared to age-matched controls? Is a methylation change in the active fighters also present in retired fighters and AD? Alternatively, since the retired fighters have a longer history of TBI, are their TREM2 methylation levels higher than active fighters? Or are high methylation levels in a different genetic location for active fighters compared to AD or retired fighters, such as in the TREM2 3â\\x80\\x99UTR compared to the promoter? Furthermore, is this epigenetic profile associated with specific genetic variants or traits, such as gene expression, biomarkers, hippocampal volume, or cognitive tests, that is similar to AD? We have developed the following hypothesis to address these questions. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000415',\n", " 'title': 'The Genetics and Epigenetics of Inflammation in Traumatic Brain Injury',\n", " 'pi': 'Lynn Bekris',\n", " 'fundingAmount': 782302.0},\n", " {'abstract': 'This investigation will implement a novel evaluation of electroencephalogram (EEG) recordings and standard clinical assessments in high school football athletes to evaluate concussive and sub-concussive impacts. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000217',\n", " 'title': 'The Impact of Concussive and Sub-Concussive Blows on Brain Network Activity',\n", " 'pi': 'Steven Broglio, PhD',\n", " 'fundingAmount': 434957.0},\n", " {'abstract': 'There is no question that the vulnerabilities of the developing brain and the potential for recovery are unique, or that pediatric mild traumatic brain injury (pmTBI) represents a major public health concern with ≈400,000 new cases annually. Although the neurobehavioral symptoms of pmTBI are well-documented in the first days to weeks post-injury, few well-designed studies have examined the long-term consequences of injury. Even less is known about the neuropathology underlying the expression of post-concussive symptoms (PCS) and the impact on clinical outcomes. Thus, clinicians currently do not understand how children typically recover in the first year of injury from either a clinical or neurophysiologic perspective. The current application addresses this critical knowledge gap by collecting longitudinal (1 week, 4 months and 1 year post-injury) neuroimaging and clinical data on a large cohort of pmTBI patients (N = 150) and healthy controls (N = 125). Our preliminary data suggests diffuse white matter injuries, hemodynamic abnormalities in deep gray matter, and signs of cortical atrophy at 4 months post-injury in a relatively small sample. Consistent with animal models, these data indicate that multiple imaging measures at multiple time-points are needed to understand the dynamic effects of pmTBI on neurophysiology and underlying contributory factors (e.g., cerebral blood flow, cerebral vascular reactivity). The current study will extend these findings to the early chronic and chronic injury stages, determine how these diffuse injuries relate to clinical outcomes, and determine the individual ?recovery time-courses? of selected biomarkers. Ratings of PCS are collected from both child and parent in conjunction with computerized cognitive testing, quality of life measures, and assessments of pre-morbid functioning. A multi-shell high angular resolution diffusion imaging sequence provides unique information on potential underlying mechanisms of action (water fractions). Functional activity is measured during a spatial attention task and through connectivity analyses. Additional quantitative measurements of resting cerebral blood flow and cerebral vascular reactivity will disambiguate hemodynamic from neuronal dysfunction. These independent measures will also provide critical information on how the vasculature in deep gray matter structures is affected by trauma, providing mechanisms of target engagement for future therapeutic trials. Growth curve modeling provides preliminary analyses of different recovery trajectories (fully versus partially recovered) for both clinical and imaging data. The public health significance of the current application is multifold. First, late childhood and adolescence constitutes a critical time for brain development, and persistent neurobehavioral symptoms following pmTBI can interfere with subsequent academic achievements and interpersonal relationships for years post-injury. Second, developing objective biomarkers that track injury progression will aid in diagnosis of injury severity and provide an empirical foundation for determining when it is truly safe for children to return to learn/physical activity. Finally, understanding the mechanisms of injury represents a critical first step for developing novel therapies that target neuropathology (i.e. target engagement) rather than symptom mitigation, the current approach for all pmTBI therapies.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000339',\n", " 'title': 'The Impact of Diffuse Mild Brain Injury on Clinical Outcomes in Children',\n", " 'pi': 'Andrew Mayer',\n", " 'fundingAmount': 890249.0},\n", " {'abstract': 'Background: Retrospective studies suggest that traumatic brain injury (TBI) increases the risk of Alzheimerâ\\x80\\x99s disease (AD) four-fold. This has not been supported by recent PET imaging studies including our previous work in Vietnam War veterans. PET scanning to measure the proteins Amyloid and Tau are the key predictors of future AD. It is these abnormal protein deposits that define AD. However, PET TBI studies have had small cohorts and have not used the latest generation of more sensitive imaging biomarkers. \\r\\nHypothesis: That individuals with traumatic brain injury (TBI) have a higher prevalence of AD related pathology and neurodegeneration compared to age matched controls. \\r\\nStudy Design: We will use the latest generation of PET imaging and 7 Tesla MRI to measure AD pathology. We will study 150 elderly TBI subjects and 100 age-matched controls. In addition, psychological testing will be carried out such that the imaging results can be tested for correlation with clinical endpoints\\r\\nRelevance: This data would inform the need for future care of veterans and the general population with TBI and identify those at high risk of AD who may benefit from early intervention trials. \\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000420',\n", " 'title': 'The Prevalence of AD Pathology After Traumatic Brain Injury in Veterans and Civilians: A Biomarker Study of Beta-Amyloid and Tau',\n", " 'pi': 'Christopher Rowe',\n", " 'fundingAmount': 545160.0},\n", " {'abstract': 'Recent studies have demonstrated that following mild traumatic brain injury (mTBI), Soldiers often experience declines in postural stability under single- and dual-task conditions. Similarly, oculomotor and visual impairments are prevalent following mTBI; however, the primary care clinic environment often lacks technology of sufficient resolution and sophistication to accurately detect the subtle abnormalities associated with mTBI-related visual dysfunction. The lack of scalable and adoptable approaches to the objective quantification of postural stability visual function represent fundamental gaps in the detection, assessment, and management of military mTBI and potentially prolongs and complicates the return-to-duty process. The proposed project will address these fundamental diagnostic and treatment gaps. Specifically, our existing validated mobile device assessment of balance and vision will be leveraged to develop \\\\\"mobile devices to test balance that can be administered by corpsman-level medical personnel\\\\\" and provide \\\\\"diagnostic methods\\\\\" for the mitigation and treatment of visual dysfunction associated with mTBI that are specifically designed for the unique demands of a military population. Our initial studies and experience clearly indicate this technology is scalable across a large health system and is effectively utilized by all members of the providers including athletic trainers, pediatricians, neurologists, sports medicine physicians, physical therapists, and occupational therapists to ensure continuity of care from injury to return to learn/play. The results from this project will provide the military with a scalable, reliable, affordable, and accurate solution to evaluating postural stability and visual function to aid in optimizing care and return-to-duty.Hypotheses: The fundamental hypotheses being tested are: (1) effective and informative dual-task paradigms can be developed using a mobile device to characterize motor (postural stability) and cognitive (executive function) simultaneously and (2) a mobile device can be used to characterize visual dysfunction that has the potential to aid in the diagnosis and treatment of mTBI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000317',\n", " 'title': 'The Quantification of Visual Function and Postural Stability Under Single- and Dual-Task Conditions Using Mobile Technology',\n", " 'pi': 'Jay Alberts',\n", " 'fundingAmount': 1499990.0},\n", " {'abstract': 'This is a prospective observational study to assess biomarkers that may\\r\\nbe related to clinical outcomes in patients with traumatic injury. Target populations include patients admitted with Traumatic Brain Injury (TBI), TBI plus polytrauma, TBI plus burn injury, and burn injury alone.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000410',\n", " 'title': 'The UCD-DGMC TBI Neural Network-Precision Medicine Paradigm for Complex Trauma',\n", " 'pi': 'Tina Palmieri',\n", " 'fundingAmount': 4158310.0},\n", " {'abstract': 'Vestibular impairment and symptoms are prevalent following mild traumatic brain injury (mTBI) (Hoffer et al., 2010) and may play a role in prolonged recovery (Lau et al., 2011; Sheedy et al., 2009). Researchers have indicated that ocular motor dysfunction and symptoms are common among personnel exposed to blast mTBI (Capo?Aponte et al., 2012). In fact, researchers have suggested that vestibular and ocular motor outcomes such as VOR and vestibulo?spinal reflex (VSR) may be useful in identifying the effects of blast from blunt mTBI (Hoffer et al., 2009). There are currently no brief, clinical screening tools to identify vestibular/ocular motor impairment and symptoms in military personnel following mTBI. Our research team recently developed the Vestibular/Ocular Motor Screening (VOMS) tool to screen for vestibular/ocular motor impairment and symptoms following mTBI (Mucha et al., 2014). Our preliminary research indicates that VOMS? a 5?min clinical screening tool that can be deployed by corpsman?level (i.e., Special Operation Combat Medics [SOCM], Special Forces Medical Sergeants [18D]) medical personnel with minimal training and materials? was nearly 90% accurate in identifying patients with mTBI from healthy controls (Mucha et al., 2014). These preliminary findings suggest that VOMS may augment current clinical screening tools such as the MACE? used by the U.S. Military. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000338',\n", " 'title': 'The use of VOMS tool with military personnel to track mTBI recovery and RTD status',\n", " 'pi': 'Anthony P Kontos',\n", " 'fundingAmount': 1354050.0},\n", " {'abstract': \"Our proposed work targets at least two of the main thrust areas of the military. The first focus area is Psychological Health and Resilience, specifically their emphasis on â\\x80\\x9c... the development and validation of effective evidenced-based screening and assessment strategies, as well as treatment and rehabilitation interventions that reduce the negative impact of behavioral health disorders and concussion/mild traumatic brain injury.â\\x80\\x9d Here we propose further refinement of a 'functional tissue pulsatility imaging (fTPI)' modality to assay aberrant brain function. Successful completion of our work on fTPI should provide to the military a device for use in the field to help assess the vulnerability of their soldiers to further head injury as well as for tracking the treatment of soldiers with mTBI/concussion. The second focus area is the Combat Casualty Care Research Program (CCCRP), specifically their emphasis on identification and development of medical devices for assessing, triaging and monitoring during early intervention in life-threatening battle injuries, here head trauma. Consistent with the mission of CCCRP we seek to refine and finalize our promising diagnostic methodology for observing aberrant brain structure via structural tissue pulsatility imaging (sTPI) with an eye on military constraints, specifically, its field-portable nature. Successful completion of our work on sTPI should â\\x80\\x9c... improve basic and advanced life support for severely injured persons as well as monitoring, sustainment, and management of severely injured casualties during episodes of delayed or protracted evacuation.\",\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000388',\n", " 'title': 'Towards a Miniature Ultrasound Device for Imaging TBI under PFC Scenarios.',\n", " 'pi': 'Pierre D Mourad, PhD',\n", " 'fundingAmount': 2816900.0},\n", " {'abstract': 'Some 2.8 million Americans seek medical attention for traumatic brain injury (TBI) annually, resulting in\\r\\nestimated annual costs of over $75 billion. Older adults have the highest and fastest rising rate of TBI of any\\r\\nother age-group, with 1 in 50 adults age â\\x89Â¥75y seeking medical attention for TBI in 2013. Older adults with TBI\\r\\nexperience higher mortality, slower recovery, worse outcomes, and may be at especially high risk for post-TBI\\r\\ndementia. There are few evidence-based guidelines for management, no tools to provide patients and families\\r\\nwith reliable estimates of prognosis, and few proven treatments. Progress has been limited by: 1. systematic\\r\\nexclusion of older disabled patients from most prior prospective TBI studies, and 2. lack of age-appropriate TBI\\r\\nresearch tools. The overall objective is to launch a 2-site prospective geriatric TBI cohort study that will directly\\r\\naddress these barriers by applying state-of-the-art geriatric research methods to the field of TBI to improve\\r\\nrepresentation of older patients in TBI research, and to develop a novel approach to measuring age appropriate\\r\\nTBI predictors, outcomes, blood-based biomarkers, and neuropathology. The approach rests on 2\\r\\nfoundational concepts: 1. Geriatric TBI is different from TBI in younger patients and will require a targeted age appropriate\\r\\napproach. 2. Baseline health status â\\x80\\x93 including comorbidities/polypharmacy, physical frailty,\\r\\nfunctional status, and brain structure â\\x80\\x93 is recognized as a key predictor of outcome in the field of geriatrics but\\r\\nis not systematically measured in TBI research. The central hypothesis is that pre-injury health will be\\r\\nextremely heterogeneous in geriatric TBI and will be a key predictor of outcome in this population. An\\r\\noutstanding team of experts in TBI and aging research will achieve these Aims: Aim 1: Assemble a prospective\\r\\ncohort of patients age â\\x89Â¥65y presenting to the Emergency Department â\\x89¤72h after TBI who underwent CT. Enroll\\r\\n270 TBI patient/study-partner dyads and 90 controls; perform baseline assessments and blood draws, and\\r\\nassess longitudinal outcomes at 2wk, 3mo, 6mo (primary endpoint) and 12mo; offer enrollment in a brain\\r\\ndonation program. Aim 2: Develop and validate optimized geriatric TBI predictor and outcome assessments:\\r\\n2a: Systematically measure apolipoprotein E allele and pre-injury comorbidities/polypharmacy, physical frailty,\\r\\nand multi-domain functional status via detailed patient and study partner interviews using validated geriatric\\r\\ninstruments and assess association of these predictors with outcome after TBI. 2b: Describe the natural history\\r\\nof geriatric TBI using validated TBI and geriatric outcomes and then use data-driven analytics to identify the\\r\\nmost parsimonious set of measures for longitudinal outcome assessment in this population. 2c (exploratory):\\r\\nMeasure pre-injury brain structure (atrophy/white matter disease of uninjured brain visualized on baseline CT)\\r\\nand explore association with outcome after TBI. Aim 3: Identify age-appropriate diagnostic and prognostic\\r\\nblood-based biomarkers. This work will directly inform design of large-scale age-appropriate geriatric TBI\\r\\nclinical trials that are urgently needed to improve care and outcomes in this vulnerable population.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000433',\n", " 'title': 'Transforming Research And Clinical Knowledge in Geriatric Traumatic Brain Injury (TRACK-GERI)',\n", " 'pi': 'Raquel C Gardner, MD',\n", " 'fundingAmount': 646349.0},\n", " {'abstract': 'Effective treatment of traumatic brain injury (TBI) remains one of the great unmet needs of wounded warriors and in public health. Traumatic brain injury has impacted over 360,000 warriors in OIF and OEF and will likely exceed half a million before US withdrawals are complete. Each year in the US, at least 1.7 million people suffer TBI; an estimated 3.2 to 5.3 million people live with the long-term physical, cognitive, and psychological health disabilities of TBI. The NIH funded the Transforming Research and Clinical Knowledge in Traumatic Brain Injury study (TRACK TBI, U01NS086090, PI: G. Manley) to accelerate clinical research in TBI. TRACK-TBI recruited over 3,000 subjects and created a large, high quality TBI database that collected clinical, imaging, biomarker and outcome data.\\r\\n\\r\\nThis study expanded the scope of TRACK-TBI, the parent study, delivering on three core missions that harmonized TRACK-TBI resources and infrastructure with DOD-funded initiatives : 1) advancing diagnostic neuroimaging by applying 3T structural MRI followed by High Definition Fiber Tracking (HDFT) in 600 subjects (this Phase 2 MRI replaced the DTI sequence with HDFT sequences); 2) creation of a Biospecimen Repository of blood and DNA samples to validate proteomic and genetic biomarkers of TBI from 3000 subjects; and 3) foundation of a Bioinformatics Core necessary for validating neuroimaging, proteomic and genetic biomarkers of TBI. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000411',\n", " 'title': 'Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) - High Definition Fiber Tracking Neuroimaging, Biospecimen, and Data Informatics Repositories',\n", " 'pi': 'David Okonkwo, MD, PhD',\n", " 'fundingAmount': 4534300.0},\n", " {'abstract': 'Effective treatment of traumatic brain injury (TBI) remains one of the greatest unmet needs in public health. Each year in the US, at least 1.7 million people suffer TBI; an estimated 3.2 to 5.3 million people live with the long-term physical, cognitive, and psychological health disabilities of TBI, with annual direct and indirect costs estimated at over $60 billion. The unique public-private partnership of investigators, philanthropy, and industry leaders brought together in the multicenter Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) proposal share a mission to accelerate clinical research in TBI. The goal is to create a large, high quality TBI database that integrates clinical, imaging, proteomic, genomic, and outcome biomarkers, and provides analytic tools and resources to establish more precise methods for TBI diagnosis and prognosis, improve outcome assessment, and compare the effectiveness and costs of tests, treatments, and services. The investigators hypothesize that this approach will permit better characterization and stratification of patients, allowing meaningful comparisons of treatments and outcomes, and thereby improving the next generation of clinical trials.\\r\\nSpecific Aim 1. To create a widely accessible, comprehensive TBI Information Commons that integrates clinical, imaging, proteomic, genomic, and outcome biomarkers from subjects across the age and injury spectra, and provides analytic tools and resources to support TBI research. \\r\\nSpecific Aim 2. To validate imaging, proteomic, and genetic biomarkers that will improve classification of TBI, permit appropriate choice and stratification of patients for clinical trials, and contribute to the development of a new taxonomy for TBI. \\r\\nSpecific Aim 3. To evaluate a flexible outcome assessment battery comprised of a broad range of TBI common data elements that enables assessment of multiple outcome domains across all phases of recovery and at all levels of TBI severity. \\r\\nSpecific Aim 4. To determine which tests, treatments, and services are effective and appropriate for which TBI patients, and use this evidence to recommend practices that offer the best value. \\r\\nThe project will directly impact public health by creating an open-access Information Commons populated with robust Common Data Elements that will make international research collaboration a reality. Detailed clinical data on 3,000 subjects (11 sites) across the injury spectrum, along with CT/MRI imaging, blood biospecimens, and detailed outcomes, will be collected and analyzed, permitting the identification/validation of biomarkers, and identification of structural abnormalities that may be predictive of outcomes, making strides toward a new taxonomy for TBI. The infrastructure of integrated databases and imaging and biosample repositories will create a high quality, legacy database for current and future generations of international researchers. \\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000267',\n", " 'title': 'Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) - Adult',\n", " 'pi': 'Geoffrey Manley, MD, PhD',\n", " 'fundingAmount': 3435920.0},\n", " {'abstract': 'Effective treatment of traumatic brain injury (TBI) remains one of the greatest unmet needs in public health. Each year in the US, at least 1.7 million people suffer TBI; an estimated 3.2 to 5.3 million people live with the long-term physical, cognitive, and psychological health disabilities of TBI, with annual direct and indirect costs estimated at over $60 billion. The unique public-private partnership of investigators, philanthropy, and industry leaders brought together in the multicenter Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) proposal share a mission to accelerate clinical research in TBI. The goal is to create a large, high quality TBI database that integrates clinical, imaging, proteomic, genomic, and outcome biomarkers, and provides analytic tools and resources to establish more precise methods for TBI diagnosis and prognosis, improve outcome assessment, and compare the effectiveness and costs of tests, treatments, and services. The investigators hypothesize that this approach will permit better characterization and stratification of patients, allowing meaningful comparisons of treatments and outcomes, and thereby improving the next generation of clinical trials. Specific Aim 1. To create a widely accessible, comprehensive TBI Information Commons that integrates clinical, imaging, proteomic, genomic, and outcome biomarkers from subjects across the age and injury spectra, and provides analytic tools and resources to support TBI research. Specific Aim 2. To validate imaging, proteomic, and genetic biomarkers that will improve classification of TBI, permit appropriate choice and stratification of patients for clinical trials, and contribute to the development of a new taxonomy for TBI. Specific Aim 3. To evaluate a flexible outcome assessment battery comprised of a broad range of TBI common data elements that enables assessment of multiple outcome domains across all phases of recovery and at all levels of TBI severity. Specific Aim 4. To determine which tests, treatments, and services are effective and appropriate for which TBI patients, and use this evidence to recommend practices that offer the best value. The project will directly impact public health by creating an open-access Information Commons populated with robust Common Data Elements that will make international research collaboration a reality. Detailed clinical data on 3,000 subjects (11 sites) across the injury spectrum, along with CT/MRI imaging, blood biospecimens, and detailed outcomes, will be collected and analyzed, permitting the identification/validation of biomarkers, and identification of structural abnormalities that may be predictive of outcomes, making strides toward a new taxonomy for TBI. The infrastructure of integrated databases and imaging and biosample repositories will create a high quality, legacy database for current and future generations of international researchers.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000409',\n", " 'title': 'Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) - Pediatric',\n", " 'pi': 'Geoffrey Manley, MD, PhD',\n", " 'fundingAmount': 3735920.0},\n", " {'abstract': 'The global aim of this proposal is to test and refine Common Data Elements (CDEs), neuroimaging standards, and best practices for genetics and proteomics in Traumatic Brain Injury (TBI) studies. Testing and validating of TBI-CDEs will be performed in a multi-center prospective observational study with 3 TBI Centers (San Francisco General Hospital (SFGH), University of Pittsburgh Medical Center (UPMC), University Medical Center Brackenridge (UMCB) and a TBI Rehabilitation Center (Mount Sinai Rehabilitation Center (MSMC)). The investigators will create and expand existing data repositories for patient demographics, neuromaging, plasma biomarkers, genetics, and multivariate outcomes thereby providing researchers and clinicians with the infrastructure to establish multidisciplinary, multicenter research networks and improve clinical research in the TBI field. Grant ## NS069409_01, NS069409_02.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000246',\n", " 'title': 'Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot',\n", " 'pi': 'Geoffrey Manley, MD, PhD',\n", " 'fundingAmount': 4285900.0},\n", " {'abstract': 'This is a prospective study involving longitudinal imaging and behavioral data on TBI patients ranging from GCS 3-15. Imaging and behavioral data was obtained at four time points (within 10 days of injury, 1 month, 6 months, and 18 months following injury. There is a FMRTBI subset study (FITBIR-STUDY0000315) associated with this prospective study.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000314',\n", " 'title': 'Traumatic Brain Injury Data for FITBIR Informatics system: Maryland MagNeTS Prospective Dataset',\n", " 'pi': 'Rao Gullapalli, PhD, MBA',\n", " 'fundingAmount': 153500.0},\n", " {'abstract': 'This interdisciplinary proposal addresses two TBI-related focus areas of the FY14/15 CRMRP NSRRA: (1) Applied research to identify pain biomarkers and their utility; and (2) Studies to determine optimal patient populations for various modalities of pain management. The proposal is aligned with the focus on evaluation of diagnostic techniques for clinical guidance, and emerging approaches and technologies. Determining the utility of brain Magnetic Resonance Spectroscopy (MRS) biomarkers of pain phenotypes will provide a foundation for mechanisms-based treatments (e.g., topiramate or gabapentin for pain dependent on glutamatergic dysfunction). The proposed study addresses the problem of chronic pain and its management after TBI by testing the utility of brain MRS as biomarkers of clinical pain phenotypes based upon pain symptoms, somatosensory and neuropsychological assessments. The long-term goal of the proposed research is to facilitate translational research and to move towards more effective mechanisms-based therapies for persistent pain after TBI. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000341',\n", " 'title': 'Utility of MRS brain biomarkers of pain phenotypes after TBI',\n", " 'pi': 'Eva Widerstrom-Noga, PhD, DDS',\n", " 'fundingAmount': 1496340.0},\n", " {'abstract': 'Football head injuries involve significant forces and can result in mild to severe traumatic brain injuries. While this has received increasing attention at the professional and collegiate levels, there is less data available for the millions of participants in high school leagues (14-18 years old) during this time of rapid brain development. The purpose of this study is to relate information about cumulative head impact exposure over a season of high school football with neurocognitive and neuroimaging data to determine the effects of sub-concussive impacts on the brain. All elements of this study focus on the objective to increase understanding of pediatric mild Traumatic Brain Injury (mTBI) and prospectively collect biomechanical, imaging, functional, and computational modeling data on a scale never before attempted in adolescents involved in contact sports. This project integrates neuroinformatics work and the computational modeling techniques developed by Drs. Whitlow, Maldjian and Stitzel at Wake Forest University Health Sciences.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000316',\n", " 'title': 'iTAKL:Imaging Telemetry And Kinematic modeLing in youth football-High School (iTAKL-high school)',\n", " 'pi': 'Joel D Stitzel, PhD',\n", " 'fundingAmount': 655855.0},\n", " {'abstract': 'Spreading depolarizations (SD) are a cytotoxic dysfunction of cerebral gray matter and a dominant pathophysiologic process in peri-lesion cortex of many severe TBI patients who undergo emergency surgery. We hypothesize that intensive care management of patients based on the occurrence of SDs, as measured by electrocorticography (ECoG), may reduce secondary injury and improve outcomes. We will conduct a randomized Phase 2 feasibility trial that uses real-time SD monitoring to guide implementation of a tier-based protocol of intensive care therapies aimed at SD suppression. The specific aims are to: (1) determine the feasibility of real-time SD monitoring to guide intensive care management of severe TBI, and (2) determine the effect of SD-guided vs. standard care management to reduce secondary brain insults in severe TBI. We aim to enroll approximately 72 patients who require neurological surgery for emergency treatment of TBI at 3 study sites. ECoG data will be monitored continuously in real-time for the occurrence of SDs during intensive care. When SDs are observed, these patients will be randomized 1:1 to either standard (control) or SD-guided care. In the standard care arm, treatment will follow local and national guidelines with blinding to further ECoG results. In the SD-guided arm, treatment will follow a tiered-based protocol with escalation and de-escalation based on efficacy to suppress further SD pathology. Treatments will include use of ketamine sedation and adjusted targets for plasma glucose, cerebral perfusion pressure, temperature, and PaCO2. For Aim 1, we will assess the accuracy of real-time SD scoring and compliance with protocol tier assignment and therapy implementation. For Aim 2, we will compare the burden of SD pathology, other measures of cerebral physiology (intracranial and cerebral perfusion pressures, and brain oxygenation), and medical complications between the two study arms. We expect to demonstrate the feasibility of targeted, personalized treatment of a neuronal mechanism of secondary injury based on real-time measurements. The efficacy of specific therapies to suppress SDs may inform neurocritical care guidelines and generalize to application in more widespread patient groups. Results could lead directly to larger-scale trials.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000429',\n", " 'title': 'Improving Neurotrauma by Depolarization Inhibition with Combination Therapy (INDICT): a Phase 2 Randomized Trial',\n", " 'pi': 'Jed Hartings',\n", " 'fundingAmount': 4427500.0},\n", " {'abstract': 'TBD',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000443',\n", " 'title': 'Characterizing Potential Chronic Brain Health Effects of Concussion and Repetitive Head Impact Exposure: The CARE-SALTOS Integrated (CSI) Study',\n", " 'pi': 'Thomas McAllister',\n", " 'fundingAmount': 25250000.0},\n", " {'abstract': 'In the general population, posttraumatic epilepsy (PTE) accounts for 5% of all epilepsy cases and 20% of symptomatic epilepsy. This number is understandably higher in the military population where almost 50% of TBI victims, who sustain penetrating head injuries. PTE has a unique feature in which seizures begin late after TBI. In approximately 80% of cases, epilepsy develops within 2 years, but the risk can extend for over 10 years post TBI. This project will study how PTE develops, which will reveal a new understanding of the brain network abnormalities associated with PTE. It will contribute new knowledges on the mechanism of PTE development from the perspective of brain network dysfunction. Although, studies have identified risk factors associated with PTE, which include but not limited to severity of initial TBI, length of posttraumatic amnesia, presence of intracranial hemorrhage, penetrating head injuries, depressed skull fractures, retention of metal fragments, location of lesion(s), cerebral contusions, age, and comorbid chronic alcoholism, none of these studies have identified any biomarkers that can reliably predict the development of PTE in TBI patients. This is partially because the mechanism of PTE development is not well understood, which makes the prevention and treatment of PTE challenging. Recent discoveries have suggested that epilepsy is a disease of brain network that facilitate the spreading and sustaining of seizures.Advanced Magnetic resonance imaging (MRI) techniques including diffusion tensor imaging (DTI) and resting state functional MRI (rsfMRI) offer noninvasive means to study the changes of brain network architecture associated PTE. DTI measures structural connectivity relating to white matter tracks in the brain, whereas rsfMRI infers functional connectivity by measuring the correlation of the blood flow patterns between two brain regions. By using these two MRI techniques, this research will reveal the abnormalities of structural and functional brain connectivity in PTE patients. We will then obtain the brain connectivity network parameters in TBI patients to study the evolution of these the connectivity during the recovery phase of TBI. Later, we will compare the different of these parameters between the group who develops PTE and the group who does not. Finally, we will use mathematical models to evaluate whether a subset of the abnormal brain network parameters can predict the development of PTE.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000423',\n", " 'title': 'Evaluation of the impact of cerebral contusions on brain network dysfunction and epileptogenesis among patients with moderate to severe traumatic brain injury',\n", " 'pi': 'Hai Sun',\n", " 'fundingAmount': 721641.0},\n", " {'abstract': 'In this study, we focus on validating a clinical automated instrument, the Ocular Photosensitivity Analyzer (OPA), to quantify an important sequela of traumatic brain injury (TBI), visual photosensitivity (i.e. photophobia). Additionally, we will also assess the effect of various light filtering eyewear with the OPA to investigate whether specific wavelengths of light have significant impact on the management of visual photosensitivity in TBI subjects. Study questionnaires will be administered in conjunction with OPA testing to better understand the complex interactions between visual photosensitivity and other TBI associated sequela (dry eye, ocular pain). We will measure VPT in healthy and TBI subjects via the OPA at Visit #1 (baseline) and Visit #2 (1 month) (both with and without light filtering eyewear, in random order) and correlate VPT to the study questionnaires. Ninety-two study participants have been recruited, screened, enrolled, and completed Visit #1 as well as eighty-eight of those study participants have completed Visit #2.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000462',\n", " 'title': 'Automated Assessment of Visual Photosensitivity in Traumatic Brain Injury',\n", " 'pi': 'Anat Galor, MD, MSPH',\n", " 'fundingAmount': 399100.0},\n", " {'abstract': 'Traumatic brain injury (TBI) represents a large public health burden for civilians, service members and Veterans. Particularly concerning are the chronic symptoms of TBI, which include emotional problems (depression, anxiety, post-traumatic stress disorder), physical problems (sleep and pain), and problems with cognitive functioning. These problems prevent most TBI survivors from returning to a normal life with their families and at work. Currently there are very few treatments for the chronic symptoms of TBI. As a result, a growing number of medical providers and patients are considering medical cannabis (MC) to treat chronic symptoms related to TBI. MC is now legal in New Mexico as well as 32 additional US states. Our and otherâ\\x80\\x99s research suggest that cannabis use may be 4-9 times higher in younger Veterans with a history of trauma relative to the general population. Although there is anecdotal evidence that MC is effective for treating emotional problems as well as pain and sleep disorders, recent systematic reviews have concluded that the actual scientific evidence for MC has not been established. This is primarily because it is illegal to do studies to examine the effects of cannabis on health-related disorders in a careful and controlled fashion. While there are certain ways to do this research with federal funding (using cannabis strains from the government), this type of research has very low validity and does not generalize to the types of cannabis products that are regularly used in state-regulated markets. Moreover, TBI results in complex pathophysiological processes that involve slow but steady changes to brain function, brain vasculature, and the structure of the brain. These processes have been shown to go on for many years post-injury. Therefore, even if cannabis products were relatively safe for healthy individuals to consume, it does not mean that they would be safe for TBI survivors to consume. The primary objectives of the current study are therefore to determine if MC has potential therapeutic or adverse effects on TBI-related symptoms (emotional, physical and cognitive) as well as overall brain health. Symptoms are measured using standard clinical tests, whereas brain health is measured using advanced brain scans and blood-based biomarkers. Based on our preliminary data in chronic TBI survivors, we predict that TBI will not have any therapeutic effects on emotional or physical symptoms, and will have detrimental effects on cognition and overall brain health. Regardless of a positive or a negative outcome, the current study will help Veterans with chronic TBI symptoms who are considering the use of MC to treat their symptoms. It will also inform doctors, clinicians and other researchers about the potential therapeutic and adverse effects of MC on TBI pathophysiology.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000446',\n", " 'title': 'A Prospective Observational Study on Therapeutic and Adverse Effects of Medical Cannabis for Chronic Traumatic Brain Injury',\n", " 'pi': 'Andrew R Mayer',\n", " 'fundingAmount': 1499920.0},\n", " {'abstract': 'Concussion and primary mitochondrial disease (PMD), both conditions with substantial public health burden and long-term consequences for youth and young adults, are conditions of bioenergetic dysfunction. Our primary challenge is the lack of clinically feasible physiological tests of bioenergetics to diagnose these deficits and monitor them over time for PMD and through recovery for concussion. In addition, the lack of objective assessments prevents the development of effective concussion treatment strategies as clear therapeutic targets remain ill-defined. Further elucidating the link between bioenergetics and autonomic nervous system (ANS) function provides an opportunity to address this challenge; ANS dysfunction in these conditions represents a rational target for assessment via clinically feasible approaches including pupillometry, exercise testing, and cerebral oxygenation measurement via functional near infrared spectroscopy (fNIRS). The metabolic mismatch that occurs after concussion is fundamentally a mitochondrial bioenergetic problem with characteristics similar to PMD. Investigating the nature and time course of bioenergetic dysfunction across clinical conditions, from both the perspective of a common injury, where deficits develop and recover, as well as an inborn genetic disorder, as in PMD, where the bioenergetic state is more fixed, provides a robust means to enhance our understanding of these mechanisms and their physiological manifestations. ANS dysfunction can be quantified using pupillometry, exercise testing and cerebral oxygenation determination using fNIRS, which represent objective measures that a) are clinically feasible with great diagnostic and prognostic potential, as well as b) serve as methods for monitoring treatment and determining physiological recovery. We will be the first to examine the utility of multi-modal clinical translational technology for the detection of ANS dysfunction in the diagnosis, prognosis and determination of recovery after concussion and the clinical relevance of these measures to PMD. We capitalize on advanced technology in fNIRS and pupillometry, as well as the simplicity of an exercise step test, to quantify specific physiological ANS deficits and provide insight into the underlying metabolic mitochondrial pathologies. This innovative approach will provide the most robust, comprehensive, multi-dimensional phenotypic characterization of ANS function in concussion to date and accelerate the identification of targets for treatment of both concussion and PMD. Furthering our understanding of the bioenergetic dysfunction underlying both concussion and PMD has the potential to have far-reaching impact on military health. As a signature injury of modern warfare, concussion is a condition which, among military personnel, is essential to identify early with accurate and objective diagnostics in order to implement timely removal from the far-forward setting to prevent further secondary injury. Having quantitative measures that prognose recovery is critical to identify those who need removal from the active front to a medical setting for further testing and treatment and those who can remain awaiting rapid recovery. This study will advance our ability to use measures of the ANS for these purposes, as well as an objective means of determining readiness to return to duty safely. Looking beyond concussion, understanding the ANS manifestations of PMD will further the identification of rational treatments for other conditions with mitochondrial dysfunction and may provide insight into potential performance enhancing measures for other end organs such as skeletal muscle where mitochondrial function is critical. Clinical trials to study such treatments using these quantitative outcome measures would result in advances that could have important implications for endurance among military servicemen and women and would represent a potential paradigm shift in terms of improving performance. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000445',\n", " 'title': 'Development and Clinical Validation of Noninvasive Diagnostics for Mitochondrial Disease',\n", " 'pi': 'Marni Falk',\n", " 'fundingAmount': 11855600.0},\n", " {'abstract': 'This is a subset of the Prospective Maryland MagNeTS (FITBIR-STUDY0000314). This is prospective study involving imaging and behavioral data on mild TBI patients ranging from GCS 13-15. Participants completed task based fMRI using the N-back working memory paradigm at variable cognitive loads. Imaging and behavioral data was obtained at a single time point (approximately 1 month following injury). ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000315',\n", " 'title': 'Traumatic Brain Injury Data for FITBIR Informatics system: Maryland MagNeTS Dataset - FMRI TBI Subset',\n", " 'pi': 'Chandler Sours, PhD',\n", " 'fundingAmount': 153500.0},\n", " {'abstract': 'Headaches following combat-related mild traumatic brain injury (mTBI) are common, can be refractory to standard therapies, and may persist and worsen to become a debilitating chronic pain syndrome. The purpose of the proposed study is to evaluate the centrally acting alpha-1 adrenoreceptor antagonist drug prazosin as a prophylactic treatment for chronic post-traumatic headache (PTHA). The impetus for this study comes from a large open-label case series in Iraq and Afghanistan Veterans with mTBI and post-traumatic headaches and data from a placebo-controlled trial evaluating use of prazosin for post-traumatic stress disorder (PTSD) in Iraq and Afghanistan active duty Service members that found beneficial effect of prazosin for decreasing the frequency and severity of headaches, in addition to decreasing PTSD-related symptoms and improving the quality of sleep.Study Objectives, Specific Aims, and Hypotheses: The objectives of this proposed study are to evaluate the efficacy and safety of prazosin as a prophylactic medical treatment for persistent PTHA. These objectives will be accomplished by conducting a randomized placebo-controlled double blind trial of prazosin vs. placebo in 160 Iraq/Afghanistan active duty Service members and Veterans with persistent PTHAs.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000367',\n", " 'title': 'Prazosin for Prophylaxis of Chronic Post-Traumatic Headaches in OEF/OIF/OND Service Members and Veterans with Mild TBI',\n", " 'pi': 'Murray Raskind',\n", " 'fundingAmount': 3942870.0},\n", " {'abstract': \"The proposed study aims to explore why acute pain turns, in some patients, into chronic pain, and to develop tools for prediction of this transition. Based on the clinical and psychological assessment along with psychophysical and neurophysiological assessment of pain perception, with the analysis of connectivity between several brain centers relevant for pain processing, together with pain genetics, we expect to develop a tool, that will predict, for the individual patient with acute pain inflicted by a whiplash injury, what are the chances for him/her to go into chronic pain situation. Further, by knowing the dysfunctions of pain processing that a patient has, it will be possible to offer the treatment of highest chances to succeed. For example, we know that patients whose pain inhibition capacity is less efficient will benefit more from analgesic agents that augment this capacity. We foresee several lines of coupling between dysfunctions at baseline and appropriate remedies for their repair. We also expect that the results of this study will be applicable, at small additional effort, to other pain syndromes, since brain's pain processing bears similar, though not identical, principles for the various painful body parts and pain syndromes. \\r\\n\\r\\nOur specific aims are to evaluate, in the setup of acute whiplash injury, the risk of transition to chronic pain based on each of the following testing domains: (i) Psychophysical and neurophysiological data describing facilitatory and inhibitory modulation capacity of the patient. (ii) Psychological data describing patient's behavior such as catastrophyzing, post-traumatic stress, pain sensitivity and aspects of personality. (iii) Structural and functional neuro-imaging data describing brain anatomy and function, where we assess resting state MRI activity, grey matter properties using T1 weighted imaging, and white matter properties using diffusion tensor imaging. (iv) Genetic data describing the genetic epidemiology based on GWAS (whole genome assessment) of every patient for the examination of genetic variants associated with transition to chronic pain, and (v) individual case data related to age, gender, education, socioeconomic parameters and personal medical history, as well as features of the specific injury. Overall, we aim to construct a composite scoring system, based on the most relevant of the above mentioned parameters, yielding the highest relative predictive value in identifying acute pain patients who have higher risk for chronification.\\r\\n\",\n", " 'status': 'Private',\n", " 'id': 'FITBIR-STUDY0000327',\n", " 'title': 'Why does acute post whiplash injury pain transform into chronic pain? ',\n", " 'pi': 'David Yarnitsky'},\n", " {'abstract': \"Although Traumatic Brain Injury (TBI) has been associated with 1) cognitive impairment, 2) the clinical diagnosis of Alzheimer's Disease (AD), and 3) AD-related neuropathology, all are vulnerable to measurement error, and none are both necessary to and sufficient for the dementia of AD (DAD). Before the field can advance to biomarker selection and treatment, dementia and Mild Cognitive Impairment (MCI) in the setting of TBI must both be more precisely defined. Objective/Hypothesis: We will construct a latent variable (i.e., TBI) for dementia case-finding in existing data collected by the Texas Alzheimer's Research and Care Consortium (TARCC) (n = 2,000). We will then use a TBI composite to diagnose the baseline dementia status of a cohort of veteran TBI cases (n = 100) and confirm those diagnoses relative to the consensus opinions of expert clinicians. We will then identify the serum protein biomarkers of TBI. This will confirm whether or not the dementia status of TBI cases is associated with the same serum biomarkers as is the dementia associated with clinical AD in older persons, or perhaps identify new biomarkers that may be specific to TBI. Finally, we will localize the structural and functional brain changes related to TBI-related dementia severity. We expect TBI to be associated specifically with the structure and function of the Default Mode Network (DMN), as we have previously demonstrated by another d homolog in AD. Rationale: Cognitive impairment is widely held to be the hallmark of dementia. However, three conditions are necessary (Royall et al., 2007): 1) There must be acquired cognitive impairment(s). 2) There must the functional disability. 3) The disability must be related to the cognitive impairment(s) that are observed. This implies that the essential feature(s) of dementing processes can be resolved to the cognitive correlates of functional status. Establishing the bio-markers of these correlates opens the way towards an empirical and quantifiable foundation for dementia's prediction, diagnosis, evaluation and treatment. This can be accomplished via construction of a latent variable (i.e., for dementia) in a Structural Equation Model (SEM) framework. \",\n", " 'status': 'Private',\n", " 'id': 'FITBIR-STUDY0000312',\n", " 'title': 'A Latent Variable Phenotype for the Dementia Diagnosis and Biomarker Selection in TBI',\n", " 'pi': 'Don Royall'},\n", " {'abstract': 'The BrainPort device is an FDA approved, non-surgical, visual prosthetic device intended for individuals who have a diagnosis of light perception or no light perception. The BrainPort V100 does not rely on duration or cause for blindness in order to be an effective aid. Visual information is captured by a digital camera and transmitted to the top surface of the tongue via electrotactile stimulation patterns. Users have control over the strength of the stimulation and camera settings using a handheld controller. The user learns to interpret the tactile stimulation as representative of visual and spatial information in their environment. With training, BrainPort users are able to detect the size, shape, location, and motion of objects in their environment. Previous research evaluating the safety and efficacy of the BrainPort device excluded the participation of individuals blinded by cortical injury (i.e. traumatic brain injury). In addition to extending access of the BrainPort device to individuals blinded by traumatic injury, the proposed research will also be used to collect user feedback and evaluation of the design of our next generation of the device, the BrainPort V200, in addition to our training techniques. The data collected in the proposed research will provide support for the BrainPort device to be introduced into current rehabilitation plans for individuals blinded by traumatic injury.',\n", " 'status': 'Private',\n", " 'id': 'FITBIR-STUDY0000275',\n", " 'title': 'A Study to Evaluate the BrainPort V200 Device in Individuals Blinded by Traumatic Injury',\n", " 'pi': 'Patricia Grant'},\n", " {'abstract': 'Athletes are at a higher-than-normal risk for sustaining forceful impacts to the head, which sometimes yield mild traumatic brain injury (concussion). As a result, there has been a growing interest in methods and devices that can aid in traditional clinical measures by accurately assessing the extent of concussion-related symptoms as well as their resolution over time. In line with this goal, this study examines and compares the efficacy of two neurocognitive assessment tools, DANA and imPACT. Using both devices, pre-season baseline data were collected on 237 college athletes. A subset of these athletes sustained a sport-related concussion and were then matched to a normal (non-concussed) control and administered DANA and imPACT at the acute phase (within 24 hours of concussion) and at 8, 15 and 45 days post-concussion. The collected data will be used to examine test-retest reliability, prediction of recovery time course, and subclinical sensitivity to lingering symptoms among athletes cleared to return to play. The findings of this study will result in an increased understanding of the role of neurocognitive assessment tools in aiding and informing clinical decision making.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000244',\n", " 'title': 'An Independent, Prospective, Head to Head Study of the Reliability and Validity of Neurocognitive Test Batteries for the Assessment of Mild Traumatic Brain Injury',\n", " 'pi': 'Corinna Lathan'},\n", " {'abstract': 'This prospective clinical study has been funded by the Congressionally Directed Medical Research Programs (CDMRP) to address military research gap areas associated to mild traumatic brain injury (mTBI) including: 1) screening, evaluation and diagnosis; and 2) diagnostic methods and biomarkers.?? In mTBI, there is a need for an objective and quantitative testing system that can be performed at the site of injury, longitudinally track the natural history of the condition, and provide reproducible quantitative comparisons. This study will define the visual and oculomotor testing battery (i.e., objective biomarkers) required to identify Warfighters in the acute setting whom are suspected of sustaining an mTBI. The ultimate endpoint will be accomplished through the completion of two specific aims based on quantifiable metrics and acquisition planning. Specifically, the proposed study aims will: 1) Quantitatively assess subjects?? visual functions data on n = 200 controls and n = 200 subjects with a diagnosis of acute phase (?? 72 hrs) mTBI; 2) Evaluate the sensitivity and specificity of the Neuro-Ophthalmic Device (NODe) acute mTBI test battery.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000326',\n", " 'title': 'Automated Comprehensive Evaluation of Mild Traumatic Brain Injury Visual Dysfunction',\n", " 'pi': 'Jose E Capo-Aponte'},\n", " {'abstract': 'Background:\\r\\n\\r\\n- A person who has a traumatic brain injury (TBI) -- also called concussion -- can have serious and long-lasting effects. Doctors who treat TBI need more information about how the brain changes over time in people with TBI and how well a person recovers from it. To make existing TBI treatments more effective and develop new ones, researchers want to look more closely at how TBI affects people both physically and psychologically.\\r\\n\\r\\nObjectives:\\r\\n\\r\\n- To collect medical information from people with recent traumatic brain injury and compare this information to that of healthy volunteers and of persons who have had injuries to other parts of their bodies besides their heads (such as broken bones, orthopedic injuries, after surgery).\\r\\n\\r\\nEligibility:\\r\\n\\r\\n3 groups of people between the ages of 18 and 70 years will be asked to take part.\\r\\n\\r\\nPersons who have had a traumatic brain injury (or concussion ) within the past 30 days, OR\\r\\nPersons who are healthy and have never had a traumatic brain injury, OR\\r\\nPersons who have had an injury within the past 30 days to a part of their body other than the head (such as a broken bone, orthopedic injury, surgery)\\r\\nDesign:\\r\\n\\r\\nThis study requires two outpatient visits each lasting 1 1/2 days. The 2 visits will be about 30 days apart. Persons with TBI and non-TBI injuries must have their first visit within 30 days of their injury.\\r\\nScreening: Participants will be screened with a medical history, physical examination, blood tests and electrocradiogram (ECG a routine heart test).\\r\\n\\r\\nThe research will involve:\\r\\n\\r\\na.Giving blood samples (no more than 75 ml each visit).\\r\\nb.Having tests of memory, attention, concentration, and thinking (neuropsychological testing).\\r\\nc.Having imaging studies of the head including magnetic resonance imaging (MRI) and positron emission tomography (PET) scans.\\r\\n\\r\\nPersons with TBI will have the same tests at Visit 1 and 2. Healthy controls and persons with non-TBI injuries will have the same tests at Visit 1 as listed above. But, at Visit 2, they will not have brain MRIs or PETs.\\r\\n\\r\\nNo treatments will be provided as part of this research protocol.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000272',\n", " 'title': 'Biomarkers-Driven Development of Experiemental Therapeutics for Traumatic Brain Injury (CNRM)',\n", " 'pi': 'Jessica Gill'},\n", " {'abstract': 'The Brain Injury and Mechanisms of Action of Hyperbaric Oxygen for Persistent Post-Concussive Symptoms after Mild Traumatic Brain Injury (mTBI) (BIMA) study, sponsored by the Department of Defense, is a randomized double-blinded, sham-controlled clinical trial that has a longer duration of follow-up and more comprehensive assessment battery compared to recent HBO2 studies. BIMA randomized 71 participants from September 2012 to May 2014. Randomized military personnel received hyperbaric oxygen (HBO2) at 1.5 atmospheres absolute (ATA) or sham chamber sessions at 1.2 ATA, air, for 60 minutes daily for 40 sessions. Outcomes include neuropsychological, neuroimaging, neurological, vestibular, autonomic function, electroencephalography, and visual systems evaluated at baseline, immediately following intervention at 13 weeks and six months with self-reported symptom and quality of life questionnaires at 12 months, 24 months and 36 months.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000363',\n", " 'title': 'Brain injury and mechanisms of action of hyperbaric oxygen for persistent post-concussive symptoms after mild traumatic brain injury (BIMA)',\n", " 'pi': 'Lindell Weaver, MD'},\n", " {'abstract': 'The purpose of this prospective, longitudinal cohort study is to improve the ability to predict posttraumatic stress disorder (PTSD) in service members who have sustained mild traumatic brain injury (TBI). Service members who have sustained impact-induced and blast-induced mild TBI, and for comparison purposes, those who have sustained a trauma-related injury but no TBI (non-TBI), will be assessed over six months to see who develops PTSD, and if there are similarities among those who do. This information would allow development and application of interventions to target vulnerable individuals, with the goal being the prevention of PTSD.\\r\\nMeasures of brain structure (MRI/DTI/SWI) and function (event-related potentials and neurocognitive testing) will be evaluated at baseline to identify potential markers of risk for PTSD. Outcome will be evaluated three and six months after the baseline assessment using psychiatric interviews (Clinician Administered PTSD Scale [CAPS] and the Structured Clinical Interview for DSM-IV [SCID]), as well as measures of post-concussion symptoms, overall health status (including headache), emotional distress, and perceived quality of life. The full brain assessment battery will be re-administered after six months to explore the course of changes in brain structure and function associated with mild TBI. Whereas the effects on brain structure and function of impact-induced TBI have been described, blast-induced TBI is a relatively new injury with largely unknown immediate and long-term effects. Thus, a secondary aim of this study is to characterize brain changes following mild TBI as a function of impact- versus blast induced trauma.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000304',\n", " 'title': 'CNRM Repository: PREDICTING OUTCOME AFTER MILD TBI: BRAIN INDICES OF STRUCTURE AND FUNCTION (CNRM)',\n", " 'pi': 'Connie Duncan'},\n", " {'abstract': 'Many Service members (SM) experience executive dysfunction associated with mild traumatic brain injury symptom complex (mTBI-sc), for which they receive cognitive rehabilitation. Cognitive rehabilitation (CR) for executive dysfunction often involves metacognitive strategy instruction (MSI) to help patients self-regulate their behavior though a goal management process - identifying a goal, anticipating performance problems, generating possible solutions, self-monitoring performance during the activity, recognizing maladaptive task strategies, stopping and then modifying real-time task behavior by choosing an alternate strategy. MSI alone often does not result in improved daily functioning because it requires conscious cognitive oversight to employ (which is difficult for people with executive dysfunction) and it presumes that simply establishing goals propels goal-directed action, when for many people, this is not so. Social psychologists report that people who set implementation intentions (if-then statements that link specific situational cues with specific goal actions) are more likely to perform goal actions than those who only set goal intentions. Implementation intentions are believed to be effective because they enable people to switch from conscious-effortful reflective action control to automatic, reflexive action control associated with selected situational cues. A team of researchers from the Courage Kenny Research Center (CKRC), Traumatic Brain Injury Center at Fort Campbell, KY (TBIC-FC), and Neurofunctional Research and Consulting has developed a brief CR intervention to teach SM with mTBI-sc to set implementation intentions called ACTION (AutomatiC iniTiation of IntentiONs) sequence training. The purpose of this pilot study to evaluate: 1) the practicality of instructional methods used to teach SM with mTBI-sc to perform the ACTION sequence and 2) the efficacy of ACTION sequence training in achieving personal goals and performance on a task that challenges executive function using a small randomized controlled trial. If the results are positive, a larger study would be conducted to determine the impact of ACTION sequence training on SM performance on military-relevant tasks and goals.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000277',\n", " 'title': 'Cognitive rehabilitation: ACTION training for soldiers with executive dysfunction',\n", " 'pi': 'Mary Radomski'},\n", " {'abstract': 'Activity-related concussion is a growing epidemic particularly in collegiate athletes. The cumulative effective of multiple concussions necessitates that return-to-activity testing post-concussion are both appropriate and sensitive in determining the readiness of the individual to return to the field. Postural stability has been shown to be a good indicator of recovery following a concussive episode. The Balance Error Scoring System (BESS) is the most widely used clinical assessment of postural stability with post-concussion athletes, yet it lacks adequate quantitative metrics needed to detect subtle changes in stability. The Virtual Environment Traumatic brain injury (TBI) Screen (VETS) device is a new assessment tool that can potentially be used to measure postural stability in healthy and neurologically impaired individuals. The VETS is a variation of our previously approved (closed) IRB approved protocol (20839) for validation of our Therawii (Portable, Instrumented Postural Stability System). The VETS uses a large wide screen TV to display a virtual reality scene to the subject. Two hundred healthy adults will participate in this study. Subjects will perform standing postural tasks using the VETS, clinical examination and neurocognitive tests. The purpose of this study is to validate the use of the VETS as a measure of postural control for assessing an individual?s readiness to return to sport or activity.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000237',\n", " 'title': 'Development and Validation of the Virtual Environment TBI Screen (VETS) for Postural Control Testing',\n", " 'pi': 'Geoffrey Wright'},\n", " {'abstract': 'The Development of normative datasets for assessments used in patients with post concussive symptoms due to mild traumatic brain injury (NORMAL) study, sponsored by the Department of Defense, is a non-intervention study of normal, healthy, non-brain injured civilians and military participants (active or inactive). Participants in the study participated in a battery of outcome assessments at defined test internvals to replicate the assessment battery used in a program of studies investigating the safety of HBO2 in participants with post-concussive symptoms following mild TBI. The study includes comprehensive assessments to obtain robust neuropsychological, physiological, and neuroimaging data. Additionally, the research attempted to identify potential confounding variables in evaluating and treating mild TBI. An initial evaluation of the test-retest variability of these assessments in healthy normal participants may help differentiate meaningful clinical changes within the mild TBI population from expected changes in a normal study population. Also, normal values for some aspects of the brain imaging are not yet known. Neuroimaging (magnetic resonance imaging and computed tomography angiography) was assessed in participants at baseline and 6 months. Neurological function and electroencephalography (EEG) was assessed at baseline only. All other in-person outcome measures were assessed in participants at baseline, at 13 weeks, and 6 months.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000364',\n", " 'title': 'Development of normative datasets for assessments used in patients with post concussive symptoms due to mild traumatic brain injury (NORMAL)',\n", " 'pi': 'Lindell Weaver, MD'},\n", " {'abstract': 'Many people who have traumatic brain injury (TBI) have low levels of physical fitness. Low physical fitness causes severe fatigue that reduces the ability to perform routine daily activities, and may also cause increased depression, anxiety, or sadness. Aerobic exercise, such as treadmill walking or running, improves physical fitness in most people and may also decrease fatigue and improve mood. However, more information is needed to determine if exercise improves these conditions in people who have TBI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000205',\n", " 'title': 'Effect of Aerobic Exercise Training on Cardiorespiratory Function in Patients with TBI (CNRM)',\n", " 'pi': 'Leighton Chan'},\n", " {'abstract': 'Importance: There is limited information about the effect of erythropoietin or a high transfusion threshold in traumatic brain injury (TBI).\\r\\n\\r\\nObjective: To compare the effects of erythropoietin and two transfusion thresholds (7 and 10 g/dl) on neurological recovery after TBI. \\r\\n\\r\\nDesign: Randomized trial using a factorial design to test: i.) whether erythropoietin would fail to improve favorable outcomes by 20%, and ii.) whether a transfusion threshold of >10 g/dl would increase favorable outcomes without increasing complications.\\r\\n\\r\\nSetting: Neurosurgical intensive care units of two Houston level 1 trauma centers\\r\\n\\r\\nParticipants: Between May 2006 and August 2012, 200 patients with closed head injury who were unable to follow commands were enrolled within 6 hours of injury; 102 patients received erythropoetin and 98 received placebo. Erythropoetin or placebo was initially dosed daily for 3 days and then weekly for 2 more weeks (n=74) and then the 24h and 48h doses were dropped for the remainder (n=126). Ninety-nine and 101 patients were assigned to the 7g/dl and 10g/dl transfusion thresholds.\\r\\n\\r\\nIntervention: Intravenous erythropoietin 500 IU/kg or saline per dose. Transfusion threshold maintained with packed red blood cell transfusion.\\r\\n\\r\\nMain Outcome: Glasgow Outcome Scale dichotomized as favorable (good recovery and moderate disability) and unfavorable (severe disability, vegetative, or dead) at 6 months post-injury.\\r\\n\\r\\nResults: There was no erythropoeitin-transfusion threshold interaction. Compared to placebo (favorable outcome rate: 34/89 [38.2%]; 95%CI=28.2-49.1%), both erythropoetin groups were futile (first dosing regimen: 17/35 [48.6%]; 95%CI=31.4-66.0%, p=0.13, and second dosing regimen: 17/57 [29.8%]; 95%CI=18.4-43.4%, p<0.001). Favorable outcome rates were 37/87 (42.5%) and 31/94 (33.0%) in the 7 and 10 g/dl threshold groups (95%CI for the difference = -0.05 to 0.25, p=0.28). There was a higher incidence of thromboembolic events in the 10 g/dl threshold group (22/101 [21.8%] vs. 8/99 [8.1%], p=0.009). \\r\\n\\r\\nConclusions and Relevance: In patients with closed head injury, neither the administration of erythropoietin nor maintaining hemoglobin concentration > 10 g/dl resulted in improved neurological outcome at 6 months and the 10 g/dl threshold was associated with a higher incidence of adverse events.. These findings do not support either approach in this setting.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000249',\n", " 'title': 'Effects of Erythropoietin on Cerebral Vascular Dysfunction and Anemia in Traumatic Brain Injury',\n", " 'pi': 'Claudia Robertson, MD'},\n", " {'abstract': 'Background:\\r\\n\\r\\nTraumatic brain injury may have a range of effects, from severe and permanent disability to more subtle functional and cognitive deficits that often go undetected during initial treatment. To improve treatments and therapies and to provide a uniform quality of care, more research is needed into different treatments for traumatic brain injury.\\r\\nExercise has been shown to improve movement and balance in people with strokes, cerebral palsy, and other conditions that affect the brain, and can improve symptoms of memory problems or depression. Bright light therapy has also been shown to improve mood in people with depression. Researchers are interested in studying problems with movement, balance, thinking, and mood in people with traumatic brain injury. By comparing the effects of exercise and bright light exposure on brain function, new treatments may be developed for acute traumatic brain injury.\\r\\nObjectives:\\r\\n\\r\\n- To compare the effects of exercise and bright light therapy on the brain function of individuals with traumatic brain injury.\\r\\n\\r\\nEligibility:\\r\\n\\r\\n- Individuals between 18 and 44 years of age who either have been diagnosed with traumatic brain injury or are healthy volunteers.\\r\\n\\r\\nDesign:\\r\\n\\r\\n?Individuals with traumatic brain injury will have four outpatient evaluation visits at the clinical center, a 3-month home exercise program, and a 3-month bright light exposure program at home. Healthy volunteers will have one evaluation visit at the clinical center.\\r\\nAt the first study visit, all participants will have a full physical examination and medical history. Individuals with traumatic brain injury will also have an eye exam to determine if it is safe for them to receive light therapy.\\r\\nAll participants will have the following initial tests:\\r\\nTests of walking and movement, including monitoring by a physical therapist; tests to record joint movement and evaluate muscle function; tests that combine movement, thinking, and speaking; and balance and reaction time tests.\\r\\nMagnetic resonance imaging scans\\r\\nTests of thinking and mood, including questionnaires, computerized tests, and simple action tests.\\r\\nParticipants with traumatic brain injury will have separate 3-month sessions of exercise and bright light therapy, with additional evaluation visits between each 3-month session and at the end of the study. Between the 3-month sessions, participants will have 1 month with no intervention.\\r\\nExercise sessions will involve regular workouts on an elliptical machine for 30 minutes for 5 days a week, and bright light therapy sessions will involve sitting in front of a light box for 30 minutes for 5 days a week. Participants will keep a journal to monitor the effects of the therapy.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000271',\n", " 'title': 'Effects of Rapid-Resisted Exercise on Ambulatory Adults with Traumatic Brain Injury (CNRM)',\n", " 'pi': 'Diane Damiano'},\n", " {'abstract': 'Phase 1 of this project (USAMRDC W81XWH-18-C-0157) was focused on building the automated/electronic NPC capability (eNPC). This protocol is for Phase 2, in which the CI multimodal brain function biomarker will be extended (Algorithm Development) with the inclusion of an automated ocular function measurement (AOFM), to expand the capability in the characterization of concussion. The study will also expand the range of applicability of the CI to ages 13-50 years old. Phase 2 will also include norming of eNPC across the age range. Phase 3 of the project will validate the algorithms developed in Phase 2, using the same protocol.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000402',\n", " 'title': 'Evaluation and Validation of a Multimodal Brain Function Biomarker with NPC',\n", " 'pi': 'Leslie Prichep'},\n", " {'abstract': 'Abstract',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000399',\n", " 'title': 'Fighter Biomarker Study',\n", " 'pi': 'Bruce T Lamb'},\n", " {'abstract': 'Computer models of brain biomechanics are needed to understand traumatic brain injury (TBI) and develop methods for prevention, but current computer models have not been fully validated. We have developed and applied MR tagging and MR elastography (MRE) methods to measure 2D brain motion and mechanical properties of the brain. In this renewal project we will extend our methods to 3D, and transition the results into computer models. We will acquire high-resolution 3D experimental data on brain deformation in human subjects to address basic questions on the biomechanics of TBI and to accelerate development of validated, reliable computer models. ',\n", " 'status': 'Private',\n", " 'id': 'FITBIR-STUDY0000216',\n", " 'title': 'In vivo measurement of brain biomechanics',\n", " 'pi': 'Philip Bayly'},\n", " {'abstract': 'LeVon',\n", " 'status': 'Private',\n", " 'id': 'FITBIR-STUDY0000370',\n", " 'title': 'LeVon Greer',\n", " 'pi': 'LeVon Greer'},\n", " {'abstract': \"The purpose of the current proposal is to identify the mechanisms responsible for generating photophobia, or abnormal light sensitivity, in patients who have suffered mild traumatic injury to the brain (or 'concussion'). Current estimates indicate that this painful condition persists in about 60 % of those who suffered from blast-related concussion and 30% of those who suffered non-blast-related concussive injuries. For those who are experiencing photophobia, it can have a debilitating effect in everyday life. Even normal levels of light can be intensely painful. Depending on the level of photophobia, patients are forced to restrict their activities to many indoor situations or use sunglasses or other aids to reduce the light entering their eyes even when in moderate outdoor lighting. Photophobia is often linked to incessant headaches, insomnia, and irritability. Whether a single of multiple mechanisms cause these disparate symptoms is unknown. To our best knowledge, no cure has been developed for photophobia to date, as the underlying cause(s) have not been understood. Thus, an effective cure or permanent symptomatic relief will be an invaluable help to those that suffer from photophobia. We expect that there will be substantial long-term beneficial effects from treatments based on the output of our studies to identify the mechanism of photophobia. We hypothesize that one of two mechanisms ? independently or jointly - are primarily responsible for the symptoms of photophobia. The first mechanism we propose to test is that a special type of retinal cells, the melanopsin-containing retinal ganglion cells (mRGCs), which project to the brainstem, and/or their pathway, are damaged in TBI. These cells respond to very specific wavelengths of light, so by careful choice of stimuli we can selectively activate their pathway. The second mechanism, which we will investigate is the tissue swelling from concussive injury that develops in core brain structures, such as the brainstem. To investigate these two mechanisms, we propose to test two groups of subjects who have experienced concussion; one group with photophobia or light-induced pain symptoms, the second group without these symptoms. We will use a suite of visual diagnostic techniques to determine the differences between these two groups. Finding systematic differences between these two groups will help us to define the mechanisms associated with photophobia. 1. We will measure electrical activity of the eye to determine if there is functional damage to the retina and its mRGCs by electroretinography (ERG); 2. We will record electrical activity from the scalp to determine if different cortical areas are affected by changes in mRGC function using high-density electroencephalography (EEG); 3. We will record changes in the blood oxygenation-level dependent signal in MRI scans of the brain to determine changes in core brain function (functional MRI); 4. We will measure the volume and shape of deep brain structures to determine if there are changes due to tissue swelling using the structural MRI technique of tensor-based morphometry (TBM).\",\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000365',\n", " 'title': 'Mechanisms of Photophobia in Mild Traumatic Brain Injury in Human Subjects: Therapeutic Implications',\n", " 'pi': 'Lora Likova, Ph.D.'},\n", " {'abstract': 'This study is an observational study of mild TBI patients with serial outcome assessments, MRI imaging, EEG, and MEG studies.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000350',\n", " 'title': 'Mission Connect Mild TBI Research Consortium',\n", " 'pi': 'Claudia Robertson, MD'},\n", " {'abstract': 'This work advances the assessment of oculomotor, vestibular and reaction time (OVRT) responses following a concussion event, with the goal of deriving a scoring system for those responses. We began the investigation by analyzing high school students and successfully identifying those who had experienced concussion. Over the course of the first year, we upgraded VEST software and finalized the mTBI protocol, developed and applied to IRB and HRPO for two testing sites, expanded our pool of concussion subjects, expanded the variables we analyze, applying a variety of statistical methods. Also, we had a pre-submission meeting with FDA to map out a path to clearance. During the second and third years we collected patients and subjects data. To date we have data from more than 98 patient (each patient was tested 3 times: average 3, 7 and 14 days after event) and more that 250 control subjects. We analyzed the first 50 patients and 100 controls and confirmed that OVRT testing on an I-Portal? device can successfully separate concussed subjects from non-concussed.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000308',\n", " 'title': 'NKI Concussion Score',\n", " 'pi': 'Alex Kiderman'},\n", " {'abstract': 'Recent advances in medical science, as well as growing public awareness of the potentially disabling effects of concussions in athletes and in combat veterans, have highlighted the growing need for effective methods for diagnosing and quantifying the effects of acute mild TBI (mTBI). Brain imaging techniques can be useful in identifying large scale changes in global functional connectivity and temporal incoherence (fMRI, MEG, EEG), white matter integrity (DTI), and some neurotransmitter concentration changes (MRS), but the current standard of care for evaluating concussion using imagery is a CT or MRI of the brain, both of which are useful in identifying gross morphological changes but cannot rule out mTBI. Additionally, these imaging methodologies, even when successful in detecting mTBI, are costly, relatively slow and impractical to make available to a wide spectrum of users. Clinical neurological examinations are relatively insensitive to subtle changes which may be associated with mTBI. Neuropsychological testing may be effective in characterizing changes in neurocognitive functioning following mTBI but is vulnerable to potential biases arising from suboptimal effort and individual differences in baseline performance. Similarly, self-report of post-concussive symptoms is subject to potential under- or over-reporting, and lacks specificity, as many symptoms of post-concussion syndrome are prevalent in individuals with no history of TBI. To address this problem, we developed a novel approach to sensory testing, and to enable this approach we designed and fabricated a new device, which is a low cost portable computer peripheral that enables high resolution tactile sensory testing. Design and validation of the methods was based on non-human primate neurophysiological studies, and because of the high degree of correlation between the evoked cortical activity in those studies, and the metrics obtained from subsequent human sensory perceptual studies, the measures are referred to as cortical metrics. The system designed to deliver these tests does not require significant training to administer, and individual tests or protocols can be delivered rapidly (1-3 minutes per test). A number of these tests non-invasively deliver tactile illusions to the skin, which in healthy CNS conditions, causes subjects to perform worse on sensory assessment tasks. Subjects or patients with some type of neurological insult typically perform better than healthy controls on these illusory tasks, and utilizing a battery of protocols and a combinatorial mathematical approach, our pilot data demonstrates a 99% confidence level for differentiating concussed vs. non-concussed individuals. This application proposes to establish solid proof-of-concept that the methodology can be used as a reliable indicator of CNS health status for differentiating concussed vs. non-concussed individuals and to further optimize the method. The overall long term goal of the work is to develop standardized measures of CNS health that can be utilized to compliment the assessments currently used for concussion/TBI in both clinical and sports training center environments.',\n", " 'status': 'Private',\n", " 'id': 'FITBIR-STUDY0000223',\n", " 'title': 'Neurosensory Assessments of Concussion',\n", " 'pi': 'Mark Tommerdahl'},\n", " {'abstract': 'The purpose of this study is to develop and pilot test methods for the assessment of cognitive and oculomotor performance using integrated eye tracking & electroencephalography (EEG) monitoring technologies within both static (â\\x80\\x9cFusion Rapid Clinical Assessmentâ\\x80\\x9d [Fusion-RC]) and dynamic military/operational (â\\x80\\x9cFusion Immersive Virtual Reality Environmentâ\\x80\\x9d [Fusion-VR]) environments. A total of 70 active duty military members between the ages of 18-45 years old will be recruited for this study. Subjects will be classified into two groups: healthy controls, or mild traumatic brain injury (mTBI). By linking Fusion-RC metrics (cognitive and oculomotor impairment and EEG signatures) to military/operational skills measured by Fusion-VR, this project will provide A) validation of Fusion-RC for rehabilitation treatment planning and return-to-duty decision making; and B) improved understanding of the functional and military/operational significance of cognitive and oculomotor impairments associated with mTBI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000405',\n", " 'title': 'Objective Multimodal Assessment of Cognitive and Sensorimotor Function after Mild TBI in Static and Dynamic Environments',\n", " 'pi': 'Pinata Sessoms'},\n", " {'abstract': 'The effectiveness of autologous BMMNC in 2 doses will be compared to placebo control for the treatment of severe TBI in children. The primary outcome measure is structural preservation of GM, WM volume by DT-MRI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000219',\n", " 'title': 'Phase 2 Pediatric Autologous BMMNC for Severe TBI',\n", " 'pi': 'Charles J Cox'},\n", " {'abstract': 'The ProTECT study will determine if intravenous (IV) progesterone (started within 4 hours of injury and given for a total of 96 hours), is more effective than placebo for treating victims of moderate to severe acute traumatic brain injury.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000248',\n", " 'title': 'Progesterone for the Treatment of Traumatic Brain Injury (ProTECT III)',\n", " 'pi': 'David Wright'},\n", " {'abstract': 'The rapid detection, diagnosis, and treatment of Traumatic Brain Injury (TBI) at the point-of-care presents an ongoing capability gap. A soldier may sustain a TBI, but due to deployment and combat factors, access to appropriate diagnostic care at the time and location of the event may be impeded or impossible. TBI is also a major health issue in the civilian population with over 1.5 million persons experiencing a TBI annually in the USA. About 50,000 patients die from TBI, and another 500,000 are hospitalized. Many researchers are now exploring blood-based RNA and proteins as potential biomarkers for TBI. Increased baseline serum levels of S100B, GFAP, NSE and tau have all been associated with a poor TBI prognosis. To this end, the University of California at San Diego (UCSD), Naval Medical Center San Diego (NMCSD), the Defense and Veterans Brain Injury Center (DVBIC), and Raytheon are proposing a rapid, economical approach for the detection of TBI. This approach leverages an enabling new device and technology to allow the low-cost isolation of circulating cell free (ccf) RNA and proteins, and detection and identification of the specific RNA biomarkers for diagnosis and monitoring of TBI. Recent research has revealed that organ trauma promotes the appearance of both ccf-DNA and ccf-RNA in the form of nanoparticulates and exosomes which are released into the blood stream. Significantly, ccf-RNA which has a high potential for containing both organ specific and trauma related RNA biomarkers can be used to identify the traumatized organ from which it originates. Presently, UCSD is refining a novel method, called High Conductance Dielectrophoresis (HC-DEP), based on a microelectrode array device that rapidly processes blood samples to localize and concentrate even trace amounts of ccf-RNA and ccf-DNA. Therefore, highly sensitive detection of trauma to the specifically identifiable organ can now be achieved and monitored in a short time at low cost.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000368',\n", " 'title': 'Rapid Isolation and Detection of RNA Biomarkers for TBI Diagnostics',\n", " 'pi': 'Michael J Heller, Ph.D.'},\n", " {'abstract': 'Repetitive brain trauma is associated with a progressive neurological deterioration, originally termed\\r\\ndementia pugilistica, and more recently, chronic traumatic encephalopathy (CTE). Most instances of CTE\\r\\noccur in association with the play of collision sports, such as American football and boxing, but CTE has\\r\\nalso been reported blast injuries from improvised explosive devices, physical abuse, poorly controlled\\r\\nepilepsy, and head-banging behaviors (Corsellis et al., 1973; Geddes et al., 1999; McKee et al., 2009,\\r\\n2013; Omalu et al., 2005). Symptoms of CTE include behavioral and mood changes that may begin in\\r\\nearly middle age. Short-term memory loss, executive dysfunction, cognitive impairment and dementia are\\r\\ncommon symptoms in later life with more advanced disease. Like many other neurodegenerative\\r\\ndiseases, CTE is diagnosed with certainty only by neuropathological examination of brain tissue.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000319',\n", " 'title': 'Tauopathy Consensus Study of Pathology Images',\n", " 'pi': 'Ann McKee'},\n", " {'abstract': 'This is a retrospective study involving limited imaging data on TBI patients with GCS ranging from 3-15 who received MR imaging as part of standard of care. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000313',\n", " 'title': 'Traumatic Brain Injury Data for FITBIR Informatics system: Maryland Retrospective Dataset',\n", " 'pi': 'Rao Gullapalli, PhD, MBA'},\n", " {'abstract': 'This is a randomized, blinded, Bayesian CRM dose-escalation placebo-controlled study designed to treat severe, acute traumatic brain injury (TBI) in adult patients with an IV infusion of autologous bone marrow mononuclear cells (BMMNC). Study subjects will be consecutive admissions of adults with severe TBI meeting inclusion/exclusion criteria. Adults, ages 18-55 years, hospitalized at Memorial Hermann Hospital for severe TBI (Glasgow Coma Score 3-8) will be screened for eligibility regardless of gender, race and ethnicity, according to the selection criteria. The eligibility criteria will be used by project personnel in reviewing medical charts of prospective patients. Patients will be randomized to receive a single IV infusion of BMMNs (6 x 106 or 9 x 106) or placebo. After undergoing the bone marrow harvest or sham harvest procedure, the subject will receive the IV infusion of either the BMMNCs or placebo. Subjects will be monitored per standard of care for TBI and safety data collected throughout the harvest/infusion procedures. Safety data will be collected daily through post-infusion day 14, at hospital discharge, and at the 1 and 6 month follow-up study visits, or more frequently if infusion related adverse events are suspected. Cerebrospinal fluid (if available), and plasma will be collected for pro and anti-inflammatory cytokines and chemokine?s, the biomarker ceruloplasmin, and CSF ratios of albumin following consent (baseline), and every twelve hours (+/- 2 hours) post-infusion for 3 days, once on post-infusion days 4 and 5, and at the 1 and 6 month follow-up study visits. A spleen ultrasound will be obtained following consent and on post-infusion days 1-7, and at all follow-up visits. A brain 3T-MRI will be performed when clinically stable (approximately 7-14 days post-injury, ICP monitor out), and at the 1 and 6 month follow-up study visits. Safety assessments will be conducted at the 1 and 6 month follow-up visits and includes physical and neurological exams, functional outcome assessments, and a CBC and CMP. The per-protocol population comprises those patients who complete the treatment originally allocated. For the primary analyses, all subjects receiving autologous BMMNC will be in the treatment group (regardless of dose; secondary analyses will include dose as a covariate). Baseline variables between groups will be examined for clinically significant differences that may have occurred by chance given the small sample size. Primary and secondary outcomes will be analyzed using general linear mixed models (GLMMs). We will examine all variables to determine the best fitting distribution (ie, Normal, Gamma) and examine residuals from each model to ensure reasonable adherence to model assumptions. We will evaluate the comparability of the two groups on key demographic variables and will adjust for them if necessary (e.g., age). For all neuroimaging outcomes, we will use a GLMM with group (treatment, placebo), time of assessment (initial, 1 and 6 months) and stratifying variable GCS as covariates and a random effect for subject to adjust for within subject correlation. Dependent variables will be 1) the volume of whole brain gray matter, white matter, and CSF; 2) FA of core white matter pathways (corpus callosum, arcuate/superior longitudinal fasciculus), and 3) MD of gray matter in frontal and temporal cortical regions. Each dependent variable will be evaluated separately. We will examine group differences in functional and neuropsychological outcomes using the global test procedure recommended by Bagiella et al (Bagiella, 2010), which allows analysis of multiple outcome measures in the assessment of intervention effects while controlling Type I error and maximizing power.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000369',\n", " 'title': 'Treatment of Adult Severe Traumatic Brain Injury Using Autologous Bone Marrow Mononuclear Cells',\n", " 'pi': 'Charles S Cox, Jr'},\n", " {'abstract': 'Background: Epidemiological studies linking traumatic brain injury (TBI) and Alzheimer?s disease and related conditions (ADRC: including Parkinson?s disease, Lewy Body dementia, Frontotemporal dementia, and amyotrophic lateral sclerosis) have yielded conflicting results. These discrepant findings reflect methodological variation in defining TBI, classifying injury severity, and studying clinical cohorts not representative of the broader population. The epidemiology of TBI in military and civilian populations is dominated by the least severe injuries, exposing the greatest number of individuals to potential risk for developing ADRC, yet most previous analysis studying the connection between TBI and ADRC do not include this category of injury severity. The most accurate and reliable study design to determine whether the occurrence of TBI increases risk for the development of ADRC is to identify incident TBI events by medical record review within a defined population and classify each by injury severity, identify matched referents within that same population, and follow both cohorts over time to observe incidence rates of ADRC. Hypothesis: We hypothesize that individuals in the population with a confirmed TBI will not be at increased risk of developing ADRC compared to age- and sex-matched referents without a TBI, after controlling for non-head injuries.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000331',\n", " 'title': \"Understanding the Connection Between Traumatic Brain Injury and Alzheimer's Disease: A Population-Based Medical Record Review Analysis\",\n", " 'pi': 'Allen W Brown'},\n", " {'abstract': 'The purpose of this study is to evaluate the impact of a traumatic brain injury on vision and characterize and measure possible visual deficits following a traumatic brain injury. A second component of the study investigates mechanisms of recovery of visual deficits following traumatic brain injury. We aim to characterize and measure visual deficits following TBI, as correlated with injury location and severity. This knowledge will then be helpful in developing specific and individualized rehabilitation programs when patients are faced with visual deficits.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000280',\n", " 'title': 'Visual Deficits in Traumatic Brain Injury',\n", " 'pi': 'Reza Farivar'},\n", " {'abstract': 'Based on a critical need to better monitor and measure the immediate and accumulated effects of impacts to a Soldier?s head, the proposed environmental impact sensor evaluation project is in response to a US Army Rapid Innovation Fund Broad Agency Announcement. This project seeks to utilize a commercial impact monitoring system and evaluate its potential to meet military needs in an operational and training environment. The technique of measuring, processing, and reporting descriptive parameters of head impact events has been established by X2 BioSystems, Inc. of Seattle, Washington. Beginning its work on Micro-Electro-Mechanical Systems (MEMs) based sensor capture and characterization of head impact dynamics in 2007, X2 has developed a six axis head impact monitoring system, capable of capturing high speed head impact events in three axes of linear acceleration and three axes of angular acceleration. This six axis approach allows for calculation of the true head impact acceleration function at the target center of mass, interior to the head. The X2 system is a platform for building head impact exposure profiles per individual subject and for a population of monitored subjects. In Phase I, year one, of the project, the commercial off the shelf (COTS) system will be evaluated to determine its strengths and weaknesses and its relevance in a military training environment. The evaluation will include a minimum of 40 Soldiers outfitted with the current xPatch. The second year, Phase II, will build on the lessons learned from the smaller scale testing and an improved ?xPatch Mil? sensor package will be developed with the improvements and customization made for a military optimized system. It is planned to include 400 Soldiers during this phase of the evaluation to insure adequate impact events are captured and to determine its utility in a larger scale system wide deployment. The subject population will include male and female Soldiers in rigorous military training environments.',\n", " 'status': 'Private',\n", " 'id': 'FITBIR-STUDY0000356',\n", " 'title': 'Xpatch Impact Dosimeter for the Solider',\n", " 'pi': 'Theresa L DiFato'},\n", " {'abstract': 'Traumatic brain injury (TBI) is a global concern that precipitates a diverse set of health consequences. TBI is a major concern in forensic populations -- an issue recently highlighted by calls for research by national public health institutions. Indeed, upwards of 60% of inmates have a history of TBI, a rate seven times higher than the general population (8.5%). TBI is a criminogenic risk factor and even mild TBI increases the rates of risk-taking behavior, substance use, and future offending. Over the last decade our team has been continuously funded by NIH to collect detailed clinical and neuroimaging protocols from over 4000 incarcerated men and women. We utilize a unique pair of twin mobile MRI units that are deployed directly on the secure grounds of forensic facilities, making it possible to conduct this research. Our dataset includes multimodal neuroimaging protocols, thorough clinical assessment, neuropsychological evaluations, and histories of TBI. All\\r\\nof our n>4000 offenders have consented to participate in longitudinal follow-up studies. For this project, we will commence a longitudinal study on n=300 individuals aged 35+, examining variables that will differentiate trajectories associated with cognitive impairments. We will also leverage advanced neuroimaging tools developed by our team to provide brain-based measures of cognitive decline and imaging-based classification tools for identifying brain injuries and comorbid conditions (i.e., substance abuse, psychopathy scores, depression, etc.). We will also examine how the brain injury profiles and comorbid conditions change over time. The availability of these unique resources to examine this highly underserved population makes this an exciting project with the potential to break new ground in our understanding of individual risk needs and divergent outcomes in TBI and neurodegenerative disease.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000452',\n", " 'title': 'A longitudinal study of traumatic brain injury in a high-risk population',\n", " 'pi': 'Kent Kiehl'},\n", " {'abstract': 'Objective: Several inter-related pathomechanisms are responsible for seizure progression following a traumatic brain injury (TBI), which can involve TBI gliosis, blood-brain barrier (BBB) disruption, inflammation, loss of neurons and glia, axonal and dendritic plasticity. The extent to which these heterogenous pathological changes are epileptogenic, or simply related to the brain injury is poorly understood. Recent advances in longitudinal analysis, methods for longitudinal patient experience data, neuroimaging, and biomarker analyses for epileptogenesis have yet to be combined, but together, could provide a means to accurately map the causative links between TBI and epilepsy, and help predict who will have treatment resistant epilepsy and better/worse health trajectories. We propose to integrate multimodal imaging, clinical, experience, and biomarker data within a longitudinal study of patient outcomes. We will gather and analyze data from Veterans with epilepsy and match psychogenic nonepileptic seizures [PNES] and no seizure controls on TBI status in order to construct and evaluate a predictive model of the emergence and outcomes of post-traumatic epilepsy (PTE).\\r\\n\\r\\nResearch Design: This multimodal perspective on Veteranâ\\x80\\x99s health offers opportunities for biomarkers and imaging measures to mutually enhance each otherâ\\x80\\x99s diagnostic precision and trajectory prediction. Using these diverse data and bioinformatics tools, we can better inform the development of personalized treatment approaches to decrease PTE risk among Veterans and reduce morbidity. Our overarching hypotheses are that 1) there will be trajectories of health for Veterans with epilepsy phenotypes (PTE, non-traumatic epilepsy [NTE], treatment resistant epilepsy [TRE]) that can be distinguished from matched Veterans with PNES and no seizure controls (NSC; no epilepsy/PNES); 2) trajectories will be associated with change in blood-based biomarkers, neuroimaging findings, and baseline to chronic assessments; and 3) biomarker/neuroimaging findings will vary by epilepsy phenotype and will differ from matched Veterans with PNES and NSC).\\r\\n\\r\\nMethodology: This prospective study will use machine learning methods on diverse data to identify health trajectories and correlates associated with epilepsy phenotypes (PTE, NTE, TRE). We will conduct a prospective study with a longitudinal cohort developed over the course of an existing PTE study. We will recruit individuals who previously agreed to be re-contacted for future research, and individuals with definite and probable PNES from another ongoing Epilepsy Research Program funded study. First, we will invite individuals with PTE and NTE. Once individuals agree to participate and take a short survey, we will identify matched controls (age, sex, TBI) from the same survey respondent pool, and matched PNES cases from the PNES cohort. We will invite 50 Veterans from each of the following six groups (PTE, NTE, PNES+TBI, PNES-no TBI, NSC+TBI, NSC-no TBI) to VA Salt Lake City to undergo clinical evaluation (epilepsy only), neuropsychological testing, neuroimaging, and blood draw for biomarker analysis. We will also obtain pre-deployment serum samples for those individuals from the DoD serum repository. We will use recurrent neural network analyses to develop health trajectories, and multivariate regression on integrated data from the three studies to identify the features most strongly correlated with PTE and persistent seizure outcomes.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000454',\n", " 'title': 'Military Injuries Understanding post-Traumatic Epilepsy: Bioinformatics with big data to examine multi-modal PTE biomarkers',\n", " 'pi': 'Mary Jo Pugh'},\n", " {'abstract': 'The purpose of this study is to improve the medical management of patients with severe traumatic brain injury. This study involves the application of computerized predictions that we have developed to be able to act earlier and prevent ongoing brain damage. All medical interventions will be part of standard of care in the management of severe traumatic brain injury. However, their application is guided by our prediction algorithms with the goal of preventing future injuries instead of waiting for them to happen before treating them.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000461',\n", " 'title': 'Prediction and Prevention of Intracranial Hypertension and Tissue Hypoxia in Severe Traumatic Brain Injury',\n", " 'pi': 'Christos Lazaridis'},\n", " {'abstract': 'The goal of the Translational Research Center for TBI and Stress Disorders (TRACTS) Data Repository is to promote multidisciplinary research that will lead to innovations in the diagnosis and treatment of the complex issues presented by the growing population of veterans who suffer the consequences of mild traumatic brain injuries occurring in the context of severe stress-related emotional disorders. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000455',\n", " 'title': 'Translational Research Center for Traumatic Brain Injury and Stress Disorders: Data Repository',\n", " 'pi': 'William Milberg'},\n", " {'abstract': 'Throughout the course of the wars in Iraq and Afghanistan, more than 250,000 service members sustained traumatic brain injuries, mostly characterized as mild traumatic brain injuries (mTBI) or concussions. While most with mTBI recover over days to weeks, a significant percentage continue to experience post-concussive symptoms such as headaches, cognitive difficulties, and dizziness for months to years. As a result, treatment of post-concussive symptoms after mTBI is of significant importance in the Department of Defense and Veterans healthcare systems. Several studies have shown that cognitive rehabilitation can be effective for individuals with mTBI, including Service Members and Veterans with post concussive symptoms. Cognitive rehabilitation is a type of treatment in which patients work with a therapist to improve everyday memory and thinking skills and develop strategies to reduce the impact of cognitive difficulties in their everyday lives. While these treatments have great potential benefits, protocols studied to date are time intensive, requiring up to 60 hours of treatment. These time demands are impractical for many Service Members and Veterans, and place a time-burden on clinics providing the treatment. The current study proposes to identify key ingredients of an evidence-based cognitive rehabilitation protocol to develop a streamlined version that is feasible and acceptable to Service Members and Veterans. This briefer protocol will increase the number of Service Members and Veterans who can access treatment. To accomplish this goal the investigators will first spend six months analyzing manualized treatments from a successful cognitive rehabilitation intervention developed for Service Members. The investigators will analyze manuals using a framework developed to identify active ingredients in rehabilitation. Based on those results the investigators will develop a manualized streamlined treatment protocol, which the investigators will deliver to 25 Service Members and 50 Veterans over 18 months in person or via telehealth. The investigators will determine feasibility and acceptability of this intervention, and collect preliminary efficacy data. The project addresses access to therapy services and enhanced treatment compliance, a key barrier to participation in cognitive rehabilitation by Veterans and Service Members with TBI. Additionally, although this study focuses on Service Members and Veterans with mTBI, the investigators expect that this streamlined intervention can also be translated to civilian populations with mTBI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000466',\n", " 'title': 'Implementation of a Brief Cognitive Rehabilitation Intervention to Enhance Efficiency of Service Delivery for Service Members and Veterans with mTBI: core-SCORE',\n", " 'pi': 'Blessen Eapen'}]" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "output = query.json()\n", "output" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Get Study Information for One Study. \n", "#### Example FITBIR-STUDY0000267 " ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Enter Study PrefixFITBIR-STUDY0000267\n" ] } ], "source": [ "#get study prefix from title\n", "url =\"https://\" + BRICSInstance + \"/gateway/query-api/study?prefixedId=\"\n", "header = {\n", " 'accept': 'application/json',\n", " 'Content-type': 'application/json',\n", " 'Authorization':'Bearer ' + token \n", "}\n", "\n", "StudyPrefixID = input(\"Enter Study Prefix\")\n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query = requests.get(url + StudyPrefixID,headers = header)\n", "query" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "[{'abstract': 'Effective treatment of traumatic brain injury (TBI) remains one of the greatest unmet needs in public health. Each year in the US, at least 1.7 million people suffer TBI; an estimated 3.2 to 5.3 million people live with the long-term physical, cognitive, and psychological health disabilities of TBI, with annual direct and indirect costs estimated at over $60 billion. The unique public-private partnership of investigators, philanthropy, and industry leaders brought together in the multicenter Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) proposal share a mission to accelerate clinical research in TBI. The goal is to create a large, high quality TBI database that integrates clinical, imaging, proteomic, genomic, and outcome biomarkers, and provides analytic tools and resources to establish more precise methods for TBI diagnosis and prognosis, improve outcome assessment, and compare the effectiveness and costs of tests, treatments, and services. The investigators hypothesize that this approach will permit better characterization and stratification of patients, allowing meaningful comparisons of treatments and outcomes, and thereby improving the next generation of clinical trials.\\r\\nSpecific Aim 1. To create a widely accessible, comprehensive TBI Information Commons that integrates clinical, imaging, proteomic, genomic, and outcome biomarkers from subjects across the age and injury spectra, and provides analytic tools and resources to support TBI research. \\r\\nSpecific Aim 2. To validate imaging, proteomic, and genetic biomarkers that will improve classification of TBI, permit appropriate choice and stratification of patients for clinical trials, and contribute to the development of a new taxonomy for TBI. \\r\\nSpecific Aim 3. To evaluate a flexible outcome assessment battery comprised of a broad range of TBI common data elements that enables assessment of multiple outcome domains across all phases of recovery and at all levels of TBI severity. \\r\\nSpecific Aim 4. To determine which tests, treatments, and services are effective and appropriate for which TBI patients, and use this evidence to recommend practices that offer the best value. \\r\\nThe project will directly impact public health by creating an open-access Information Commons populated with robust Common Data Elements that will make international research collaboration a reality. Detailed clinical data on 3,000 subjects (11 sites) across the injury spectrum, along with CT/MRI imaging, blood biospecimens, and detailed outcomes, will be collected and analyzed, permitting the identification/validation of biomarkers, and identification of structural abnormalities that may be predictive of outcomes, making strides toward a new taxonomy for TBI. The infrastructure of integrated databases and imaging and biosample repositories will create a high quality, legacy database for current and future generations of international researchers. \\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000267',\n", " 'title': 'Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) - Adult',\n", " 'pi': 'Geoffrey Manley, MD, PhD',\n", " 'fundingAmount': 3435920.0}]" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "studyinfo = query.json()\n", "studyinfo" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## GET ALL STUDIES ASSOCIATED WITH A FORM STRUCTURE\n", "### Returns all the studies that have data submitted to the form structure\n", "#### Example Form: [GCS](https://fitbir.nih.gov/dictionary/publicData/dataStructureAction!view.action?dataStructureName=GCS&publicArea=true&style.key=fitbir-style) from FITBIR
\n", "Search additional FITBIR Forms Here: https://fitbir.nih.gov/content/data-dictionary#form-structures
\n", "See Swagger UI: https://fitbir.nih.gov/gateway/query-api/swagger-ui/index.html#/study/getStudyByFormName for more information regarding this endpoint" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "GCS\n" ] } ], "source": [ "url = \"https://\" + BRICSInstance + \"/gateway/query-api/study/form?formName=\"\n", "header = {\n", " 'accept': 'application/json',\n", " 'Content-type': 'application/json',\n", " 'Authorization':'Bearer ' + token \n", "}\n", "\n", "formstructureshortname = input()" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query = requests.get(url + formstructureshortname,headers=header)\n", "query" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Output Format: JSON\n", "The user will receive the following information in JSON format:\n", "1. Study Status\n", "2. Study ID\n", "3. Study Title\n", "4. Study Abstract" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[{'form': 'GCS',\n", " 'studies': [{'abstract': 'Activity-related concussion is a growing epidemic particularly in collegiate athletes. The cumulative effective of multiple concussions necessitates that return-to-activity testing post-concussion are both appropriate and sensitive in determining the readiness of the individual to return to the field. Postural stability has been shown to be a good indicator of recovery following a concussive episode. The Balance Error Scoring System (BESS) is the most widely used clinical assessment of postural stability with post-concussion athletes, yet it lacks adequate quantitative metrics needed to detect subtle changes in stability. The Virtual Environment Traumatic brain injury (TBI) Screen (VETS) device is a new assessment tool that can potentially be used to measure postural stability in healthy and neurologically impaired individuals. The VETS is a variation of our previously approved (closed) IRB approved protocol (20839) for validation of our Therawii (Portable, Instrumented Postural Stability System). The VETS uses a large wide screen TV to display a virtual reality scene to the subject. Two hundred healthy adults will participate in this study. Subjects will perform standing postural tasks using the VETS, clinical examination and neurocognitive tests. The purpose of this study is to validate the use of the VETS as a measure of postural control for assessing an individual?s readiness to return to sport or activity.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000237',\n", " 'title': 'Development and Validation of the Virtual Environment TBI Screen (VETS) for Postural Control Testing',\n", " 'pi': 'Geoffrey Wright'},\n", " {'abstract': 'The goal of acute traumatic brain injury (TBI) treatment is to minimize secondary damage that evolves over hours to days after the primary injury. Until now, however, there have been no methods for monitoring heterogeneous pathomechanisms to identify patients for appropriate neuroprotection therapies. Using invasive monitoring in TBI patients requiring craniotomy, we have documented that spreading depolarizations (SD), a seizure-like pathology of cerebral gray matter that has been well-characterized through 60 years of research in animal models, are the dominant pathophysiologic process in peri-lesion cortex of many, but not all, severe TBI patients. Furthermore, we found that the occurrence of SD as a secondary injury process in patients is an independent predictor of worse neurologic outcomes. Thus, monitoring of SD provides the first real-time measure of neuronal secondary injury processes in patients to determine the selective application and benefit of neuroprotective therapies. However, since surgical patients are <10% of all TBI, less invasive and non-invasive techniques for SD monitoring are now required to generalize these findings. The premise of this proposal is that SD occurs across the spectrum of TBI severity as a pathologic mechanism of disease process and outcome heterogeneity.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000389',\n", " 'title': 'Development and validation of spreading depolarization monitoring for TBI management',\n", " 'pi': 'Jed Hartings',\n", " 'fundingAmount': 4729860.0},\n", " {'abstract': 'Importance: There is limited information about the effect of erythropoietin or a high transfusion threshold in traumatic brain injury (TBI).\\r\\n\\r\\nObjective: To compare the effects of erythropoietin and two transfusion thresholds (7 and 10 g/dl) on neurological recovery after TBI. \\r\\n\\r\\nDesign: Randomized trial using a factorial design to test: i.) whether erythropoietin would fail to improve favorable outcomes by 20%, and ii.) whether a transfusion threshold of >10 g/dl would increase favorable outcomes without increasing complications.\\r\\n\\r\\nSetting: Neurosurgical intensive care units of two Houston level 1 trauma centers\\r\\n\\r\\nParticipants: Between May 2006 and August 2012, 200 patients with closed head injury who were unable to follow commands were enrolled within 6 hours of injury; 102 patients received erythropoetin and 98 received placebo. Erythropoetin or placebo was initially dosed daily for 3 days and then weekly for 2 more weeks (n=74) and then the 24h and 48h doses were dropped for the remainder (n=126). Ninety-nine and 101 patients were assigned to the 7g/dl and 10g/dl transfusion thresholds.\\r\\n\\r\\nIntervention: Intravenous erythropoietin 500 IU/kg or saline per dose. Transfusion threshold maintained with packed red blood cell transfusion.\\r\\n\\r\\nMain Outcome: Glasgow Outcome Scale dichotomized as favorable (good recovery and moderate disability) and unfavorable (severe disability, vegetative, or dead) at 6 months post-injury.\\r\\n\\r\\nResults: There was no erythropoeitin-transfusion threshold interaction. Compared to placebo (favorable outcome rate: 34/89 [38.2%]; 95%CI=28.2-49.1%), both erythropoetin groups were futile (first dosing regimen: 17/35 [48.6%]; 95%CI=31.4-66.0%, p=0.13, and second dosing regimen: 17/57 [29.8%]; 95%CI=18.4-43.4%, p<0.001). Favorable outcome rates were 37/87 (42.5%) and 31/94 (33.0%) in the 7 and 10 g/dl threshold groups (95%CI for the difference = -0.05 to 0.25, p=0.28). There was a higher incidence of thromboembolic events in the 10 g/dl threshold group (22/101 [21.8%] vs. 8/99 [8.1%], p=0.009). \\r\\n\\r\\nConclusions and Relevance: In patients with closed head injury, neither the administration of erythropoietin nor maintaining hemoglobin concentration > 10 g/dl resulted in improved neurological outcome at 6 months and the 10 g/dl threshold was associated with a higher incidence of adverse events.. These findings do not support either approach in this setting.\\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000249',\n", " 'title': 'Effects of Erythropoietin on Cerebral Vascular Dysfunction and Anemia in Traumatic Brain Injury',\n", " 'pi': 'Claudia Robertson, MD'},\n", " {'abstract': 'This study is an observational study of mild TBI patients with serial outcome assessments, MRI imaging, EEG, and MEG studies.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000350',\n", " 'title': 'Mission Connect Mild TBI Research Consortium',\n", " 'pi': 'Claudia Robertson, MD'},\n", " {'abstract': 'We conducted this observational prospective cohort study at two large level 1 pediatric trauma centers in the U.S. This study was the first to report the use of the Functional Status Scale (FSS) in children with TBI. PEDALFAST also supported the development and validation of computational tools (phenotypes) to identify neurosurgical and critical care events in databases containing information about children with TBI.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000395',\n", " 'title': 'PEDiatric vALidation oF vAriableS in TBI (PEDALFAST)',\n", " 'pi': 'Tellen Bennett',\n", " 'fundingAmount': 700827.0},\n", " {'abstract': 'Effective treatment of traumatic brain injury (TBI) remains one of the great unmet needs of wounded warriors and in public health. Traumatic brain injury has impacted over 360,000 warriors in OIF and OEF and will likely exceed half a million before US withdrawals are complete. Each year in the US, at least 1.7 million people suffer TBI; an estimated 3.2 to 5.3 million people live with the long-term physical, cognitive, and psychological health disabilities of TBI. The NIH funded the Transforming Research and Clinical Knowledge in Traumatic Brain Injury study (TRACK TBI, U01NS086090, PI: G. Manley) to accelerate clinical research in TBI. TRACK-TBI recruited over 3,000 subjects and created a large, high quality TBI database that collected clinical, imaging, biomarker and outcome data.\\r\\n\\r\\nThis study expanded the scope of TRACK-TBI, the parent study, delivering on three core missions that harmonized TRACK-TBI resources and infrastructure with DOD-funded initiatives : 1) advancing diagnostic neuroimaging by applying 3T structural MRI followed by High Definition Fiber Tracking (HDFT) in 600 subjects (this Phase 2 MRI replaced the DTI sequence with HDFT sequences); 2) creation of a Biospecimen Repository of blood and DNA samples to validate proteomic and genetic biomarkers of TBI from 3000 subjects; and 3) foundation of a Bioinformatics Core necessary for validating neuroimaging, proteomic and genetic biomarkers of TBI. ',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000411',\n", " 'title': 'Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) - High Definition Fiber Tracking Neuroimaging, Biospecimen, and Data Informatics Repositories',\n", " 'pi': 'David Okonkwo, MD, PhD',\n", " 'fundingAmount': 4534300.0},\n", " {'abstract': 'Effective treatment of traumatic brain injury (TBI) remains one of the greatest unmet needs in public health. Each year in the US, at least 1.7 million people suffer TBI; an estimated 3.2 to 5.3 million people live with the long-term physical, cognitive, and psychological health disabilities of TBI, with annual direct and indirect costs estimated at over $60 billion. The unique public-private partnership of investigators, philanthropy, and industry leaders brought together in the multicenter Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) proposal share a mission to accelerate clinical research in TBI. The goal is to create a large, high quality TBI database that integrates clinical, imaging, proteomic, genomic, and outcome biomarkers, and provides analytic tools and resources to establish more precise methods for TBI diagnosis and prognosis, improve outcome assessment, and compare the effectiveness and costs of tests, treatments, and services. The investigators hypothesize that this approach will permit better characterization and stratification of patients, allowing meaningful comparisons of treatments and outcomes, and thereby improving the next generation of clinical trials.\\r\\nSpecific Aim 1. To create a widely accessible, comprehensive TBI Information Commons that integrates clinical, imaging, proteomic, genomic, and outcome biomarkers from subjects across the age and injury spectra, and provides analytic tools and resources to support TBI research. \\r\\nSpecific Aim 2. To validate imaging, proteomic, and genetic biomarkers that will improve classification of TBI, permit appropriate choice and stratification of patients for clinical trials, and contribute to the development of a new taxonomy for TBI. \\r\\nSpecific Aim 3. To evaluate a flexible outcome assessment battery comprised of a broad range of TBI common data elements that enables assessment of multiple outcome domains across all phases of recovery and at all levels of TBI severity. \\r\\nSpecific Aim 4. To determine which tests, treatments, and services are effective and appropriate for which TBI patients, and use this evidence to recommend practices that offer the best value. \\r\\nThe project will directly impact public health by creating an open-access Information Commons populated with robust Common Data Elements that will make international research collaboration a reality. Detailed clinical data on 3,000 subjects (11 sites) across the injury spectrum, along with CT/MRI imaging, blood biospecimens, and detailed outcomes, will be collected and analyzed, permitting the identification/validation of biomarkers, and identification of structural abnormalities that may be predictive of outcomes, making strides toward a new taxonomy for TBI. The infrastructure of integrated databases and imaging and biosample repositories will create a high quality, legacy database for current and future generations of international researchers. \\r\\n',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000267',\n", " 'title': 'Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) - Adult',\n", " 'pi': 'Geoffrey Manley, MD, PhD',\n", " 'fundingAmount': 3435920.0},\n", " {'abstract': 'Effective treatment of traumatic brain injury (TBI) remains one of the greatest unmet needs in public health. Each year in the US, at least 1.7 million people suffer TBI; an estimated 3.2 to 5.3 million people live with the long-term physical, cognitive, and psychological health disabilities of TBI, with annual direct and indirect costs estimated at over $60 billion. The unique public-private partnership of investigators, philanthropy, and industry leaders brought together in the multicenter Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) proposal share a mission to accelerate clinical research in TBI. The goal is to create a large, high quality TBI database that integrates clinical, imaging, proteomic, genomic, and outcome biomarkers, and provides analytic tools and resources to establish more precise methods for TBI diagnosis and prognosis, improve outcome assessment, and compare the effectiveness and costs of tests, treatments, and services. The investigators hypothesize that this approach will permit better characterization and stratification of patients, allowing meaningful comparisons of treatments and outcomes, and thereby improving the next generation of clinical trials. Specific Aim 1. To create a widely accessible, comprehensive TBI Information Commons that integrates clinical, imaging, proteomic, genomic, and outcome biomarkers from subjects across the age and injury spectra, and provides analytic tools and resources to support TBI research. Specific Aim 2. To validate imaging, proteomic, and genetic biomarkers that will improve classification of TBI, permit appropriate choice and stratification of patients for clinical trials, and contribute to the development of a new taxonomy for TBI. Specific Aim 3. To evaluate a flexible outcome assessment battery comprised of a broad range of TBI common data elements that enables assessment of multiple outcome domains across all phases of recovery and at all levels of TBI severity. Specific Aim 4. To determine which tests, treatments, and services are effective and appropriate for which TBI patients, and use this evidence to recommend practices that offer the best value. The project will directly impact public health by creating an open-access Information Commons populated with robust Common Data Elements that will make international research collaboration a reality. Detailed clinical data on 3,000 subjects (11 sites) across the injury spectrum, along with CT/MRI imaging, blood biospecimens, and detailed outcomes, will be collected and analyzed, permitting the identification/validation of biomarkers, and identification of structural abnormalities that may be predictive of outcomes, making strides toward a new taxonomy for TBI. The infrastructure of integrated databases and imaging and biosample repositories will create a high quality, legacy database for current and future generations of international researchers.',\n", " 'status': 'Public',\n", " 'id': 'FITBIR-STUDY0000409',\n", " 'title': 'Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) - Pediatric',\n", " 'pi': 'Geoffrey Manley, MD, PhD',\n", " 'fundingAmount': 3735920.0}]}]" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "formstructureinformation = query.json()\n", "formstructureinformation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Form Structure API " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## GET FORM STRUCTURES FOR A STUDY\n", "### Returns all the form structures that have data submitted for the study. \n", "#### Example FITBIR-STUDY0000267 \n", "
See Swagger UI: https://fitbir.nih.gov/gateway/query-api/swagger-ui/index.html#/form/getFormByStudyPrefixedId for more information regarding this endpoint\n" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Enter Study PrefixID FITBIR-STUDY0000267 \n" ] } ], "source": [ "url = \"https://\" + BRICSInstance + \"/gateway/query-api/form/study?prefixedId=\"\n", "\n", "headers = {\n", " 'accept': 'application/json',\n", " 'Content-type': 'application/json',\n", " 'Authorization':'Bearer ' + token \n", "}\n", "studyid = input(\"Enter Study PrefixID \")" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query= requests.get(url + studyid, headers = headers)\n", "query" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Output Format: JSON \n", "The user will receive the following information in JSON format\n", "1. Study ID\n", "2. Forms associated with the Study\n", " - Form Structure Short Name\n", " - Form Structure title\n", " - Form Structure Version" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[{'studyId': 'FITBIR-STUDY0000267',\n", " 'forms': [{'id': 2314,\n", " 'shortName': 'AIS',\n", " 'title': 'Abbreviated Injury Scale (AIS)',\n", " 'version': '1.0'},\n", " {'id': 2727,\n", " 'shortName': 'AIS_Appdx_TRACKTBI',\n", " 'title': 'Abbreviated Injury Scale (AIS) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2575,\n", " 'shortName': 'AUDITC',\n", " 'title': 'Alcohol Use Disorders Identification Test - Consumption Questions (AUDIT-C)',\n", " 'version': '1.2'},\n", " {'id': 2782,\n", " 'shortName': 'AUDITC_Appdx_TRACKTBI',\n", " 'title': 'Alcohol Use Disorders Identification Test - Consumption Questions (AUDIT-C) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2641,\n", " 'shortName': 'Adverse_Events_FITBIR',\n", " 'title': 'FITBIR Adverse Events',\n", " 'version': '1.3'},\n", " {'id': 2722,\n", " 'shortName': 'AdvrseEvnts_Appdx_TRACKTBI',\n", " 'title': 'FITBIR Adverse Events Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2584,\n", " 'shortName': 'BSI18',\n", " 'title': 'Brief Symptoms Inventory-18 (BSI-18)',\n", " 'version': '1.4'},\n", " {'id': 2672,\n", " 'shortName': 'BSI18_Appdx_TRACKTBI',\n", " 'title': 'Brief Symptoms Inventory-18 (BSI-18) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 1466,\n", " 'shortName': 'BTACT',\n", " 'title': 'Brief Test of Adult Cognition by Telephone (BTACT)',\n", " 'version': '1.0'},\n", " {'id': 2674,\n", " 'shortName': 'BTACT_Appdx_TRACKTBI',\n", " 'title': 'Brief Test of Adult Cognition by Telephone (BTACT) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2512,\n", " 'shortName': 'Biomarker',\n", " 'title': 'BRICS Biomarker Assay and Genetics Data Form',\n", " 'version': '1.0'},\n", " {'id': 2675,\n", " 'shortName': 'CAP_Mod_Appdx_TRACKTBI',\n", " 'title': 'Confusion Assessment Protocol (CAP) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2269,\n", " 'shortName': 'CAP_mod_TRACK',\n", " 'title': 'Confusion Assessment Protocol (CAP) - modified for TRACK TBI',\n", " 'version': '1.0'},\n", " {'id': 2591,\n", " 'shortName': 'CSSRS',\n", " 'title': 'Columbia-Suicide Severity Rating Scale (C-SSRS)',\n", " 'version': '1.3'},\n", " {'id': 2676,\n", " 'shortName': 'CSSRS_Appdx_TRACKTBI',\n", " 'title': 'Columbia-Suicide Severity Rating Scale (C-SSRS) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 1356,\n", " 'shortName': 'DemogrFITBIR',\n", " 'title': 'FITBIR Demographics Form',\n", " 'version': '1.1'},\n", " {'id': 2747,\n", " 'shortName': 'Demogr_Appdx_TRACKTBI',\n", " 'title': 'FITBIR Demographics Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2677,\n", " 'shortName': 'EDRSPICarAppdxTRACKTBI',\n", " 'title': 'Expanded Disability Rating Scale - Postacute Interview (E-DRS-PI) caregiver Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2678,\n", " 'shortName': 'EDRSPISurvrAppdxTRACKTBI',\n", " 'title': 'Expanded Disability Rating Scale - Postacute Interview (E-DRS-PI) survivor Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2570,\n", " 'shortName': 'EDRSPI_Car',\n", " 'title': 'Expanded Disability Rating Sale-Postacute Interview (E-DRS-PI) caregiver measure',\n", " 'version': '1.1'},\n", " {'id': 2571,\n", " 'shortName': 'EDRSPI_Sur',\n", " 'title': 'Expanded Disability Rating Sale-Postacute Interview (E-DRS-PI) survivor measure',\n", " 'version': '1.1'},\n", " {'id': 2372,\n", " 'shortName': 'GCS',\n", " 'title': 'Neurological Assessment: Glasgow Coma Scale (GCS) and Pupils',\n", " 'version': '1.2'},\n", " {'id': 2746,\n", " 'shortName': 'GCS_Appdx_TRACKTBI',\n", " 'title': 'Glasgow Coma Scale (GCS) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2679,\n", " 'shortName': 'GOAT_Appdx_TRACKTBI',\n", " 'title': 'Galveston Orientation and Amnesia Test (GOAT) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2582,\n", " 'shortName': 'GOAT_FITBIR',\n", " 'title': 'Galveston Orientation and Amnesia Test (GOAT)',\n", " 'version': '1.2'},\n", " {'id': 2566,\n", " 'shortName': 'GOSE_Standard',\n", " 'title': 'Glasgow Outcome Scale Extended (GOS-E)',\n", " 'version': '1.3'},\n", " {'id': 2715,\n", " 'shortName': 'GOSE_Std_Appdx_TRACKTBI',\n", " 'title': 'Glasgow Outcome Scale Extended (GOS-E) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2665,\n", " 'shortName': 'GOSEmodTRACKTBI',\n", " 'title': 'Glasgow Outcome Scale Extended (GOS-E) modified TRACK TBI',\n", " 'version': '1.0'},\n", " {'id': 2673,\n", " 'shortName': 'GOSEmodTRCK_Appdx_TRACKTBI',\n", " 'title': 'Glasgow Outcome Scale Extended (GOS-E) modified Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2772,\n", " 'shortName': 'ICPAppdx_TRACKTBI',\n", " 'title': 'Monitoring Devices Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2691,\n", " 'shortName': 'ISI_Appdx_TRACKTBI',\n", " 'title': 'Insomnia Severity Index (ISI) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 1536,\n", " 'shortName': 'ImagingDiffusion',\n", " 'title': 'Imaging Diffusion',\n", " 'version': '1.1'},\n", " {'id': 1537,\n", " 'shortName': 'ImagingFunctionalMR',\n", " 'title': 'Imaging Functional MR',\n", " 'version': '1.1'},\n", " {'id': 1564,\n", " 'shortName': 'ImagingMR',\n", " 'title': 'Imaging MR',\n", " 'version': '1.2'},\n", " {'id': 1737,\n", " 'shortName': 'ImagingRead_FITBIR',\n", " 'title': 'FITBIR Imaging Read form',\n", " 'version': '1.0'},\n", " {'id': 2743,\n", " 'shortName': 'ImgngRd_Appdx_TRACKTBI',\n", " 'title': 'FITBIR Imaging Read Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2744,\n", " 'shortName': 'InjHx_Appdx_TRACKTBI',\n", " 'title': 'FITBIR Injury History Form Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2377,\n", " 'shortName': 'InjHx_FITBIR',\n", " 'title': 'FITBIR Injury History Form',\n", " 'version': '1.1'},\n", " {'id': 2181,\n", " 'shortName': 'InsomniaSeverityIndex_FIT',\n", " 'title': 'Insomnia Severity Index (ISI)',\n", " 'version': '1.1'},\n", " {'id': 2577,\n", " 'shortName': 'JKFCRSR',\n", " 'title': 'JFK Coma Recovery Scale- Revised (CRS-R)',\n", " 'version': '1.2'},\n", " {'id': 2695,\n", " 'shortName': 'JKFCRSR_Appdx_TRACKTBI',\n", " 'title': 'JFK Coma Recovery Scale - Revised (CRS-R) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2748,\n", " 'shortName': 'LabTest_Appdx_TRACKTBI',\n", " 'title': 'FITBIR Laboratory Test Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2190,\n", " 'shortName': 'LabTest_FITBIR',\n", " 'title': 'FITBIR Laboratory Test Form',\n", " 'version': '1.2'},\n", " {'id': 2572,\n", " 'shortName': 'MPAI4',\n", " 'title': 'Mayo-Portland Adaptability Inventory-4 (MPAI-4)',\n", " 'version': '1.2'},\n", " {'id': 2692,\n", " 'shortName': 'MPAI4_Appdx_TRACKTBI',\n", " 'title': 'Mayo-Portland Adaptability Inventory-4 (MPAI-4) Appendix for TRACK-TBI ',\n", " 'version': '1.0'},\n", " {'id': 2680,\n", " 'shortName': 'MedHx_Appdx_TRACKTBI',\n", " 'title': 'FITBIR Medical History Form (MedHx_FITBIR) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 1294,\n", " 'shortName': 'MedHx_FITBIR',\n", " 'title': 'FITBIR Medical History Form',\n", " 'version': '1.0'},\n", " {'id': 2029,\n", " 'shortName': 'NIHTBDimChngeCrdSrtTest',\n", " 'title': 'NIH ToolBox Cognition Domain Dimensional Change Card Sort Test',\n", " 'version': '1.1'},\n", " {'id': 1555,\n", " 'shortName': 'NIHTBFlankrInhbtCntrAtnTst',\n", " 'title': 'NIH ToolBox Cognition Domain Flanker Inhibitory Control and Attention Test ',\n", " 'version': '1.0'},\n", " {'id': 1553,\n", " 'shortName': 'NIHTBListSortWorkMemTest',\n", " 'title': 'NIH ToolBox Cognition Domain List Sorting Working Memory Test',\n", " 'version': '1.0'},\n", " {'id': 1554,\n", " 'shortName': 'NIHTBOralReadRecogTestEng',\n", " 'title': 'NIH ToolBox Cognition Domain Oral Reading Recognition Test (English)',\n", " 'version': '1.0'},\n", " {'id': 1548,\n", " 'shortName': 'NIHTBPatrnCompProcSpdTst',\n", " 'title': 'NIH ToolBox Cognition Domain Pattern Comparison Processing Speed Test',\n", " 'version': '1.0'},\n", " {'id': 1578,\n", " 'shortName': 'NIHTBPictureSeqMemoryTest',\n", " 'title': 'NIH ToolBox Cognition Domain Picture Sequence Memory Test',\n", " 'version': '1.0'},\n", " {'id': 1579,\n", " 'shortName': 'NIHTBPictureVocabTest',\n", " 'title': 'NIH Toolbox Cognition Domain Picture Vocabulary Test',\n", " 'version': '1.0'},\n", " {'id': 1790,\n", " 'shortName': 'OSUTBIMSF',\n", " 'title': 'Ohio State University TBI Identification Method short form (OSUTBIMS)',\n", " 'version': '1.0'},\n", " {'id': 2728,\n", " 'shortName': 'OSUTBIMSF_Appdx_TRACKTBI',\n", " 'title': 'FITBIR OSUTBIMSF Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2637,\n", " 'shortName': 'PCL5',\n", " 'title': 'PTSD Checklist for DSM-5 (PCL-5)',\n", " 'version': '1.2'},\n", " {'id': 2684,\n", " 'shortName': 'PCL5_Appdx_TRACKTBI',\n", " 'title': 'PTSD Checklist for DSM-5 (PCL-5) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2636,\n", " 'shortName': 'PHQ9',\n", " 'title': 'Patient Health Questionnaire - 9 (PHQ-9)',\n", " 'version': '1.3'},\n", " {'id': 2693,\n", " 'shortName': 'PHQ9_Appdx_TRACKTBI',\n", " 'title': 'Patient Health Questionnaire - 9 (PHQ-9) Appendix for TRACK-TBI ',\n", " 'version': '1.0'},\n", " {'id': 2175,\n", " 'shortName': 'PROMISPainInterference',\n", " 'title': 'PROMIS Bank v1.0 - Pain Interference',\n", " 'version': '1.0'},\n", " {'id': 2685,\n", " 'shortName': 'PROMISPain_Appdx_TRACKTBI',\n", " 'title': 'PROMIS - Pain Interference Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2589,\n", " 'shortName': 'QOLIBRIOS',\n", " 'title': 'Quality of Life After Brain Injury - Overall Scale (QOLIBRI-OS) ',\n", " 'version': '1.2'},\n", " {'id': 2681,\n", " 'shortName': 'QOLIBRIOSTRACKTBI_App',\n", " 'title': 'QOLIBRIOS Appendix for TRACK TBI',\n", " 'version': '1.0'},\n", " {'id': 2686,\n", " 'shortName': 'RAVLT_Appdx_TRACKTBI',\n", " 'title': 'Rey Auditory Verbal Learning Test (RAVLT) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2298,\n", " 'shortName': 'Rivermead',\n", " 'title': 'Rivermead Post-Concussion Symptoms Questionnaire (RPQ) - do not use',\n", " 'version': '1.3'},\n", " {'id': 2682,\n", " 'shortName': 'Rivermead_Appdx_TRACKTBI',\n", " 'title': 'Rivermead Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2037,\n", " 'shortName': 'SF12',\n", " 'title': '12-item Short Form Health Survey Version 2 (SF-12v2)',\n", " 'version': '1.3'},\n", " {'id': 2234,\n", " 'shortName': 'SF12mod',\n", " 'title': '12-item Short Form Health Survey Version 2 (SF-12v1)',\n", " 'version': '1.0'},\n", " {'id': 2687,\n", " 'shortName': 'SF12v1_appdx_TRACKTBI',\n", " 'title': '12-item Short Form (SF-12v1) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2688,\n", " 'shortName': 'SF12v2_Appdx_TRACKTBI',\n", " 'title': '12-item Short Form (SF-12v2) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2694,\n", " 'shortName': 'SWLS_Appdx_TRACKTBI',\n", " 'title': 'Satisfaction with Life Scale (SWLS) Appendix for TRACK-TBI ',\n", " 'version': '1.0'},\n", " {'id': 2640,\n", " 'shortName': 'SWLS_CDISC_FITBIR',\n", " 'title': 'Satisfaction with Life Scale (SWLS)',\n", " 'version': '1.3'},\n", " {'id': 1858,\n", " 'shortName': 'SecInsultsOtherComplctns',\n", " 'title': 'Second Insults and Other Complications',\n", " 'version': '1.0'},\n", " {'id': 2729,\n", " 'shortName': 'SecInsults_Appdx_TRACKTBI',\n", " 'title': 'FITBIR SecInsults Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2719,\n", " 'shortName': 'TIL_Appdx_TRACKTBI',\n", " 'title': 'Therapy Intensity Level Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2689,\n", " 'shortName': 'TMT_Appdx_TRACKTBI',\n", " 'title': 'Trail Making Test (TMT) Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2630,\n", " 'shortName': 'TMT_Standard',\n", " 'title': 'Trail Making Test (TMT)',\n", " 'version': '1.3'},\n", " {'id': 2794,\n", " 'shortName': 'TRACKTBIInterviewMod',\n", " 'title': 'Track TBI Interview Modified',\n", " 'version': '1.0'},\n", " {'id': 2428,\n", " 'shortName': 'TRACKTBI_Hospital',\n", " 'title': 'TRACK TBI Secondary Complications',\n", " 'version': '1.1'},\n", " {'id': 2294,\n", " 'shortName': 'TRACK_AdmissionDischarge',\n", " 'title': 'Track Admission and Discharge',\n", " 'version': '1.0'},\n", " {'id': 2749,\n", " 'shortName': 'TRACK_Surg_Appdx_TRACKTBI',\n", " 'title': 'TRACK-TBI Surgeries Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2270,\n", " 'shortName': 'TRACK_Surgery',\n", " 'title': 'TRACK TBI Surgeries',\n", " 'version': '1.0'},\n", " {'id': 2174,\n", " 'shortName': 'TherapyIntensityLevel',\n", " 'title': 'Therapy Intensity Level',\n", " 'version': '1.1'},\n", " {'id': 2301,\n", " 'shortName': 'VitalSigns_FITBIR',\n", " 'title': 'FITBIR Vital Signs',\n", " 'version': '1.1'},\n", " {'id': 2696,\n", " 'shortName': 'WAISIVCod_Appdx_TRACKTBI',\n", " 'title': 'Wechsler Adult Intelligence Scale Coding Appendix for TRACK-TBI',\n", " 'version': '1.0'},\n", " {'id': 2697,\n", " 'shortName': 'WAISIVSym_Appdx_TRACKTBI',\n", " 'title': 'Wechsler Adult Intelligence Scale, Fourth Edition (WAIS-IV) Symbol Search Appendix for TRACK-TBI',\n", " 'version': '1.0'}]}]" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "studyformstructuredata = query.json()\n", "studyformstructuredata\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Data Elements API " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## GET DATA ELEMENTS FOR A FORM STRUCTURE\n", "### Return all data elements associated with the form structure. \n", "#### Example Form: [GCS](https://fitbir.nih.gov/dictionary/publicData/dataStructureAction!view.action?dataStructureName=GCS&publicArea=true&style.key=fitbir-style) from FITBIR
\n", "Search additional FITBIR Forms Here: https://fitbir.nih.gov/content/data-dictionary#form-structures
\n", "See Swagger UI: https://fitbir.nih.gov/gateway/query-api/swagger-ui/index.html#/dataElement/getDataElementsByFormNames for more information regarding this endpoint" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "GCS\n" ] } ], "source": [ "url = \"https://\" + BRICSInstance + \"/gateway/query-api/dataElement/form/\"\n", "\n", "headers = {\n", "# 'accept': 'application/json',\n", " 'Content-type': 'application/json',\n", " 'Authorization':'Bearer ' + token \n", "}\n", "\n", "# print(\"Input Form Structure Short Name\")\n", "formstructureshortname = input()\n" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dataelementapiquery = requests.get(url + formstructureshortname,headers = headers)\n", "dataelementapiquery" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Output Format: JSON\n", "The user will receive the following information from the JSON.\n", "1. Repeatable Group Name\n", "2. Position in the Form Structure\n", "3. Data Element ID\n", "4. Name and Title of Data Element\n", "5. Description of Data Element\n", "6. Data Type\n", "7. Input Restriction \n", "8. Required Type" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[{'name': 'Main',\n", " 'position': 0,\n", " 'threshold': 1,\n", " 'dataElements': [{'id': 69410,\n", " 'name': 'GUID',\n", " 'title': 'GUID',\n", " 'description': 'Global Unique ID (GUID) which uniquely identifies a subject',\n", " 'dataType': 'GUID',\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Required'},\n", " {'id': 69738,\n", " 'name': 'SubjectIDNum',\n", " 'title': 'Subject identifier number',\n", " 'description': 'An identification number assigned to the participant/subject within a given protocol or a study.',\n", " 'dataType': 'Alphanumeric',\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Optional'},\n", " {'id': 70501,\n", " 'name': 'AgeYrs',\n", " 'title': 'Age in years',\n", " 'description': \"Value for participant's subject age, calculated as elapsed time since the birth of the participant/subject in years. The subjects age is typically recorded to the nearest full year completed, e.g. 11 years and 6 months should be recorded as 11 years.\",\n", " 'dataType': 'Numeric Values',\n", " 'minimumValue': 0.0,\n", " 'maximumValue': 150.0,\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Recommended'},\n", " {'id': 71778,\n", " 'name': 'VitStatus',\n", " 'title': 'Vital status',\n", " 'description': 'Status of participant/subject as alive or dead',\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Alive', 'Dead', 'Unknown'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Optional'},\n", " {'id': 69741,\n", " 'name': 'VisitDate',\n", " 'title': 'Visit date',\n", " 'description': 'Interview or visit date (actually the date when data in the form were captured)',\n", " 'dataType': 'Date or Date & Time',\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Recommended'},\n", " {'id': 69409,\n", " 'name': 'SiteName',\n", " 'title': 'Site name',\n", " 'description': 'The name of the site for the study',\n", " 'dataType': 'Alphanumeric',\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Recommended'},\n", " {'id': 70279,\n", " 'name': 'DaysSinceBaseline',\n", " 'title': 'Days since baseline',\n", " 'description': 'The number of days since baseline',\n", " 'dataType': 'Numeric Values',\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Optional'},\n", " {'id': 70444,\n", " 'name': 'CaseContrlInd',\n", " 'title': 'Case control indicator',\n", " 'description': 'Indicator of whether subject is in the case or control arm of the study.',\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Case', 'Control', 'Unknown'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Optional'},\n", " {'id': 69728,\n", " 'name': 'GeneralNotesTxt',\n", " 'title': 'General notes text',\n", " 'description': 'General notes',\n", " 'dataType': 'Alphanumeric',\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Optional'}]},\n", " {'name': 'Form Administration',\n", " 'position': 1,\n", " 'threshold': 0,\n", " 'dataElements': [{'id': 69739,\n", " 'name': 'ContextType',\n", " 'title': 'Context type',\n", " 'description': 'The context to which the questions were answered, e.g. since the last interview or after the injury.',\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['After injury',\n", " 'At time of assessment',\n", " 'Before injury',\n", " 'Last 24 hours',\n", " 'Last 2 weeks',\n", " 'Last 6 months',\n", " 'Last month',\n", " 'Last week',\n", " 'Last year',\n", " 'Other, specify',\n", " 'Prior to death',\n", " 'Since the last interview',\n", " 'Time of injury'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 69743,\n", " 'name': 'ContextTypeOTH',\n", " 'title': 'Context type other text',\n", " 'description': 'The free-text related to Context type specifying other text.',\n", " 'dataType': 'Alphanumeric',\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Recommended'},\n", " {'id': 70457,\n", " 'name': 'DataSource',\n", " 'title': 'Data source',\n", " 'description': 'Source of the data provided on the case report form',\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Brother',\n", " 'Chart/Medical record',\n", " 'Daughter',\n", " 'Family, specify relation',\n", " 'Father',\n", " 'Friend',\n", " 'Mother',\n", " 'Other, specify',\n", " 'Participant/subject',\n", " 'Physician',\n", " 'Sister',\n", " 'Son',\n", " 'Spouse',\n", " 'Unknown'],\n", " 'inputRestriction': 'Multiple Pre-Defined Values Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 69731,\n", " 'name': 'DataSourceOTH',\n", " 'title': 'Data source other text',\n", " 'description': 'The free-text field related to Data source specifying other text. Source of the data provided on the case report form',\n", " 'dataType': 'Alphanumeric',\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Recommended'}]},\n", " {'name': 'Glasgow Coma Scale',\n", " 'position': 2,\n", " 'threshold': 0,\n", " 'dataElements': [{'id': 40826,\n", " 'name': 'GCSConfounderTyp',\n", " 'title': 'Glasgow Coma Scale (GCS) - Confounders type',\n", " 'description': \"Type of confounders influencing participant's/subject's Glasgow Coma Scale (GCS) score\",\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Alcohol/drugs of abuse',\n", " 'C-spine injury',\n", " 'GCS Accurate',\n", " 'Hypothermia',\n", " 'Hypoxia/hypotension',\n", " 'Paralytic',\n", " 'Sedation',\n", " 'Unknown'],\n", " 'inputRestriction': 'Multiple Pre-Defined Values Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 67698,\n", " 'name': 'GCSEyeRespnsScale',\n", " 'title': 'Glasgow Coma Scale (GCS) - eye response scale',\n", " 'description': 'Glasgow Coma Scale (GCS) - Best eye response (E). The GCS is a standardized instrument for assessing the level of consciousness. It evaluates three aspects of responsiveness: eye opening, motor response, verbal response.',\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['1', '2', '3', '4', 'Unknown', 'Untestable'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 67699,\n", " 'name': 'GCSMotorRespnsScale',\n", " 'title': 'Glasgow Coma Scale (GCS) - motor response scale',\n", " 'description': 'Glasgow Coma Scale (GCS) - Best motor response (M). The GCS is a standardized instrument for assessing the level of consciousness. It evaluates three aspects of responsiveness: eye opening, motor response, verbal response.',\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['1',\n", " '2',\n", " '3',\n", " '4',\n", " '5',\n", " '6',\n", " 'Unknown',\n", " 'Untestable'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 67701,\n", " 'name': 'GCSVerbalRspnsScale',\n", " 'title': 'Glasgow Coma Scale (GCS) - verbal response scale',\n", " 'description': \"Score that describes the participant's verbal response according to the Glasgow Coma Scale (GCS)\",\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['1', '2', '3', '4', '5', 'Unknown', 'Untestable'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 67703,\n", " 'name': 'GCSTotalScore',\n", " 'title': 'Glasgow Coma Scale (GCS) - total score',\n", " 'description': 'Glasgow Coma Scale (GCS) - Total Score. The GCS is a standardized instrument for assessing the level of consciousness. It evaluates three aspects of responsiveness: eye opening, motor response, verbal response. The total score is the sum of the scores for the three response types. (3-15)',\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['10',\n", " '11',\n", " '12',\n", " '13',\n", " '14',\n", " '15',\n", " '3',\n", " '4',\n", " '5',\n", " '6',\n", " '7',\n", " '8',\n", " '9',\n", " 'Unknown',\n", " 'Untestable'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 40816,\n", " 'name': 'PupilReactivityLghtLftEyeReslt',\n", " 'title': 'Pupil reactivity light left eye result',\n", " 'description': \"Result of testing of the contraction of the participant's/subject's left pupil when a bright light is shone on it from an angle\",\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Brisk',\n", " 'Nonreactive',\n", " 'Sluggish',\n", " 'Unknown',\n", " 'Untestable'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 40817,\n", " 'name': 'PupilReactivityLghtRtEyeReslt',\n", " 'title': 'Pupil reactivity light right eye result',\n", " 'description': \"Result of testing of the contraction of the participant's/subject's right pupil when a bright light is shone on it from an angle\",\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Brisk',\n", " 'Nonreactive',\n", " 'Sluggish',\n", " 'Unknown',\n", " 'Untestable'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 40815,\n", " 'name': 'PupilLftEyeMeasr',\n", " 'title': 'Pupil left eye measurement',\n", " 'description': 'Measurement of the left pupil in millimeters',\n", " 'dataType': 'Numeric Values',\n", " 'minimumValue': 1.0,\n", " 'maximumValue': 10.0,\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Recommended'},\n", " {'id': 40814,\n", " 'name': 'PupilRtEyeMeasr',\n", " 'title': 'Pupil right eye measurement',\n", " 'description': 'Measurement of the right pupil in millimeters',\n", " 'dataType': 'Numeric Values',\n", " 'minimumValue': 1.0,\n", " 'maximumValue': 10.0,\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Recommended'},\n", " {'id': 40812,\n", " 'name': 'PupilShapeLftEyeTyp',\n", " 'title': 'Pupil shape left eye type',\n", " 'description': 'Type of shape of the pupil of the left eye',\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Oval', 'Round', 'Unknown'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 40813,\n", " 'name': 'PupilShapeRtEyeTyp',\n", " 'title': 'Pupil shape right eye type',\n", " 'description': 'Type of shape of the pupil of the right eye',\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Oval', 'Round', 'Unknown'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'}]},\n", " {'name': 'Pediatric Glasgow Coma Scale',\n", " 'position': 3,\n", " 'threshold': 0,\n", " 'dataElements': [{'id': 40826,\n", " 'name': 'GCSConfounderTyp',\n", " 'title': 'Glasgow Coma Scale (GCS) - Confounders type',\n", " 'description': \"Type of confounders influencing participant's/subject's Glasgow Coma Scale (GCS) score\",\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Alcohol/drugs of abuse',\n", " 'C-spine injury',\n", " 'GCS Accurate',\n", " 'Hypothermia',\n", " 'Hypoxia/hypotension',\n", " 'Paralytic',\n", " 'Sedation',\n", " 'Unknown'],\n", " 'inputRestriction': 'Multiple Pre-Defined Values Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 67604,\n", " 'name': 'PGCSEyeRespnsScore',\n", " 'title': 'Pediatric Glasgow Coma Scale (PGCS) - eye response score',\n", " 'description': \"Score for the participant's eye response according to the Pediatric Glasgow Coma Scale (PGCS) if the participant is under the age of 18.\",\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['1', '2', '3', '4', 'Unknown', 'Untestable'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 67700,\n", " 'name': 'PGCSMotorRespnsScore',\n", " 'title': 'Pediatric Glasgow Coma Scale (PGCS) - motor response score',\n", " 'description': \"Score for the participant's motor response according to the Pediatric Glasgow Coma Scale (PGCS) if the participant is under the age of 18.\",\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['1',\n", " '2',\n", " '3',\n", " '4',\n", " '5',\n", " '6',\n", " 'Unknown',\n", " 'Untestable'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 67704,\n", " 'name': 'PGCSVerbalRespnsScore',\n", " 'title': 'Pediatric Glasgow Coma Scale (PGCS) - verbal response score',\n", " 'description': \"Score for the participant's verbal response according to the Pediatric Glasgow Coma Scale (PGCS) if the participant is under the age of 18.\",\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['1', '2', '3', '4', '5', 'Unknown', 'Untestable'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 67702,\n", " 'name': 'PGCSTotalScore',\n", " 'title': 'Pediatric Glasgow Coma Scale (PGCS) - total score',\n", " 'description': \"Score for the participant's total Pediatric Glasgow Coma Scale (PGCS) score of the 3 tests, eye, motor, and verbal responses. A score of less than 9 would indicate that that participant is in a severe coma while a score of greater than 9 is a mild or no coma at all.\",\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['10',\n", " '11',\n", " '12',\n", " '13',\n", " '14',\n", " '15',\n", " '3',\n", " '4',\n", " '5',\n", " '6',\n", " '7',\n", " '8',\n", " '9',\n", " 'Unknown',\n", " 'Untestable'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 40816,\n", " 'name': 'PupilReactivityLghtLftEyeReslt',\n", " 'title': 'Pupil reactivity light left eye result',\n", " 'description': \"Result of testing of the contraction of the participant's/subject's left pupil when a bright light is shone on it from an angle\",\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Brisk',\n", " 'Nonreactive',\n", " 'Sluggish',\n", " 'Unknown',\n", " 'Untestable'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 40817,\n", " 'name': 'PupilReactivityLghtRtEyeReslt',\n", " 'title': 'Pupil reactivity light right eye result',\n", " 'description': \"Result of testing of the contraction of the participant's/subject's right pupil when a bright light is shone on it from an angle\",\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Brisk',\n", " 'Nonreactive',\n", " 'Sluggish',\n", " 'Unknown',\n", " 'Untestable'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 40815,\n", " 'name': 'PupilLftEyeMeasr',\n", " 'title': 'Pupil left eye measurement',\n", " 'description': 'Measurement of the left pupil in millimeters',\n", " 'dataType': 'Numeric Values',\n", " 'minimumValue': 1.0,\n", " 'maximumValue': 10.0,\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Recommended'},\n", " {'id': 40814,\n", " 'name': 'PupilRtEyeMeasr',\n", " 'title': 'Pupil right eye measurement',\n", " 'description': 'Measurement of the right pupil in millimeters',\n", " 'dataType': 'Numeric Values',\n", " 'minimumValue': 1.0,\n", " 'maximumValue': 10.0,\n", " 'inputRestriction': 'Free-Form Entry',\n", " 'requiredType': 'Recommended'},\n", " {'id': 40812,\n", " 'name': 'PupilShapeLftEyeTyp',\n", " 'title': 'Pupil shape left eye type',\n", " 'description': 'Type of shape of the pupil of the left eye',\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Oval', 'Round', 'Unknown'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'},\n", " {'id': 40813,\n", " 'name': 'PupilShapeRtEyeTyp',\n", " 'title': 'Pupil shape right eye type',\n", " 'description': 'Type of shape of the pupil of the right eye',\n", " 'dataType': 'Alphanumeric',\n", " 'permissibleValue': ['Oval', 'Round', 'Unknown'],\n", " 'inputRestriction': 'Single Pre-Defined Value Selected',\n", " 'requiredType': 'Recommended'}]}]" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dataelementapiinformation = dataelementapiquery.json()\n", "dataelementapiinformation" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Data API " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## GET DATA FROM MULTIPLE FORM STRUCTURES WITHOUT DOING JOINS\n", "#### Example Below Uses Form1 = GCS and Form2 = Imaging Diffusion from FITBIR \n", "#### See Swagger-UI https://fitbir.nih.gov/gateway/query-api/swagger-ui/index.html#/data/bulkSingleForm for more information regarding this endpoint" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "# set input parameters: \n", "# Input any form structures associated with your BRICs instance of interest (use short name)\n", "form1 = 'GCS'\n", "form2 = 'ImagingDiffusion'\n", "\n", "# Input any study study prefix ID \n", "study1 = ['FITBIR-STUDY0000409'] \n", "study2 = ['FITBIR-STUDY0000267']" ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [], "source": [ "multipleformsheader = {\n", " 'Content-type': 'application/json',\n", " 'Authorization':'Bearer ' + token\n", " }\n", "\n", "multipleformsurl = \"https://\" + BRICSInstance + \"/gateway/query-api/data/bulk/form/study\"" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "multipleformsfilter ={\n", " \"flattened\": \"false\",\n", " \"formStudies\": [\n", " {\n", " \"form\": form1,\n", " \"studies\": \n", " study1\n", " },\n", " {\n", " \"form\": form1,\n", " \"studies\": \n", " study2\n", " },\n", " {\n", " \"form\": form2,\n", " \"studies\": \n", " study1\n", " },\n", " {\n", " \"form\": form2,\n", " \"studies\": \n", " study2\n", " }\n", " ] \n", " ,\n", " \"outputFormat\": \"csv\"\n", "}" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "multipleformsquery = requests.post(multipleformsurl,headers = multipleformsheader,json = multipleformsfilter)\n", "multipleformsquery" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'Date': 'Wed, 10 Apr 2024 13:31:06 GMT', 'Server': 'Apache', 'X-Content-Type-Options': 'nosniff', 'X-Frame-Options': 'sameorigin', 'X-Xss-Protection': '1; mode=block', 'Referrer-Policy': 'strict-origin-when-cross-origin, no-referrer', 'Strict-Transport-Security': 'max-age=63072000;includeSubdomains;preload', 'Vary': 'Origin,Access-Control-Request-Method,Access-Control-Request-Headers', 'Cache-Control': 'no-cache, no-store, must-revalidate', 'Pragma': 'no-cache', 'Expires': '0', 'Content-Disposition': 'attachment;filename=\"bulkForm_2024-04-10T09-31-052168278122481513904.zip\"', 'Content-Type': 'application/zip', 'Keep-Alive': 'timeout=5, max=100', 'Connection': 'Keep-Alive', 'Transfer-Encoding': 'chunked'}" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "multipleformsquery.headers" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Output Format: Zipped CSV Files\n", "Extract all .csvs and save them locally " ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [], "source": [ "# Extract all .csv files from zip \n", "import zipfile, io\n", "z = zipfile.ZipFile(io.BytesIO(multipleformsquery.content))\n", "z.extractall(created_dir)" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "scrolled": true }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Here is the location of your files: C:\\Users\\bagonismm\\Desktop\\Coding\\api-development\\QueryToolandAPIPresentation_04112024\\UserGuides\\BRICsQueryTool_2024_04_10_outputfiles\\query_result_GCS_2024-04-10T09-30-464513621180269995292.csv\n", "_____________________________________________\n", "Here is the location of your files: C:\\Users\\bagonismm\\Desktop\\Coding\\api-development\\QueryToolandAPIPresentation_04112024\\UserGuides\\BRICsQueryTool_2024_04_10_outputfiles\\query_result_GCS_2024-04-10T09-31-0017826347010607676307.csv\n", "_____________________________________________\n", "Here is the location of your files: C:\\Users\\bagonismm\\Desktop\\Coding\\api-development\\QueryToolandAPIPresentation_04112024\\UserGuides\\BRICsQueryTool_2024_04_10_outputfiles\\query_result_ImagingDiffusion_2024-04-10T09-31-03786940054294527485.csv\n", "_____________________________________________\n", "Here is the location of your files: C:\\Users\\bagonismm\\Desktop\\Coding\\api-development\\QueryToolandAPIPresentation_04112024\\UserGuides\\BRICsQueryTool_2024_04_10_outputfiles\\query_result_ImagingDiffusion_2024-04-10T09-31-0515687447877164834836.csv\n", "_____________________________________________\n" ] } ], "source": [ "#file information\n", "import glob\n", "files = sorted(glob.glob(created_dir + '/*.csv'))\n", "\n", "for file in files:\n", " print(\"Here is the location of your files: \" + file)\n", " print(\"_____________________________________________\")\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Return data with a data element value filter \n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Define Filter on Data Element (as defined by Form.RepeatableGroup.dataElement) Values
\n", "Here use FITBIR GCS.Main.AgeYrs (20-50) AND DemogrFITBIR.Subject Demographics.GenderTyp (Female)
\n", "This filter can be input into either the CSV or JSON endpoint \n" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [], "source": [ "# get GCS and DemogrFITBIR forms joined for FITBIR-STUDY0000267\n", "# for female subjects 20-50 years of age\n", "filterForQuery = {\n", " \"formStudy\": [\n", " {\n", " \"form\": 'GCS',\n", " \"studies\": ['FITBIR-STUDY0000267']\n", " },\n", " {\n", " \"form\": \"DemogrFITBIR\",\n", " \"studies\": ['FITBIR-STUDY0000267']\n", " },\n", " ],\n", " \"filter\": [\n", " {\n", " \"dataElement\": \"AgeYrs\",\n", " \"form\": \"GCS\",\n", " \"repeatableGroup\": \"Main\",\n", " \"operator\":\"AND\",\n", " \"rangeStart\": \"20\",\n", " \"rangeEnd\": \"50\",\n", " \"mode\": \"inclusive\"\n", " \n", " },\n", " {\n", " \"dataElement\": \"GenderTyp\",\n", " \"form\": \"DemogrFITBIR\",\n", " \"repeatableGroup\": \"Subject Demographics\",\n", " \"value\": [\n", " \"Female\"\n", " ]\n", " }\n", " ]\n", "}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Output CSV Format \n", "See Swagger-UI https://fitbir.nih.gov/gateway/query-api/swagger-ui/index.html#/data/getInstancedDataCsv for more information regarding this endpoint" ] }, { "cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": [ "queryurl = \"https://\" + BRICSInstance + \"/gateway/query-api/data/csv\"\n", "\n", "headers = {\n", " 'accept': 'application/zip',\n", " 'Content-type': 'application/json',\n", " 'Authorization':'Bearer ' + token }" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query = requests.post(queryurl,headers=headers,json=filterForQuery)\n", "query" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Response: \n", "Data received: query_result_GCS_join_DemogrFITBIR_2024-04-10T09-32-1314825941161510811561.\n" ] } ], "source": [ "print(f\"Response: {query}\")\n", "print(\"Data received: \" + query.headers[\"Content-Disposition\"][21:96]) " ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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GUIDGCS.Study IDGCS.DatasetGCS.Main.GUIDGCS.Main.ASSOCIATED GUIDGCS.Main.SubjectIDNumGCS.Main.AgeYrsGCS.Main.VitStatusGCS.Main.VisitDateGCS.Main.SiteNameGCS.Main.DaysSinceBaselineGCS.Main.CaseContrlIndGCS.Main.GeneralNotesTxtGCS.Form Administration.ContextTypeGCS.Form Administration.ContextTypeOTHGCS.Form Administration.DataSourceGCS.Form Administration.DataSourceOTHGCS.Glasgow Coma Scale.GCSConfounderTypGCS.Glasgow Coma Scale.GCSEyeRespnsScaleGCS.Glasgow Coma Scale.GCSMotorRespnsScaleGCS.Glasgow Coma Scale.GCSVerbalRspnsScaleGCS.Glasgow Coma Scale.GCSTotalScoreGCS.Glasgow Coma Scale.PupilReactivityLghtLftEyeResltGCS.Glasgow Coma Scale.PupilReactivityLghtRtEyeResltGCS.Glasgow Coma Scale.PupilLftEyeMeasrGCS.Glasgow Coma Scale.PupilRtEyeMeasrGCS.Glasgow Coma Scale.PupilShapeLftEyeTypGCS.Glasgow Coma Scale.PupilShapeRtEyeTypGCS.Pediatric Glasgow Coma Scale.GCSConfounderTypGCS.Pediatric Glasgow Coma Scale.PGCSEyeRespnsScoreGCS.Pediatric Glasgow Coma Scale.PGCSMotorRespnsScoreGCS.Pediatric Glasgow Coma Scale.PGCSVerbalRespnsScoreGCS.Pediatric Glasgow Coma Scale.PGCSTotalScoreGCS.Pediatric Glasgow Coma Scale.PupilReactivityLghtLftEyeResltGCS.Pediatric Glasgow Coma Scale.PupilReactivityLghtRtEyeResltGCS.Pediatric Glasgow Coma Scale.PupilLftEyeMeasrGCS.Pediatric Glasgow Coma Scale.PupilRtEyeMeasrGCS.Pediatric Glasgow Coma Scale.PupilShapeLftEyeTypGCS.Pediatric Glasgow Coma Scale.PupilShapeRtEyeTypDemogrFITBIR.Study IDDemogrFITBIR.DatasetDemogrFITBIR.Main Group.GUIDDemogrFITBIR.Main Group.ASSOCIATED GUIDDemogrFITBIR.Main Group.SubjectIDNumDemogrFITBIR.Main Group.AgeYrsDemogrFITBIR.Main Group.VisitDateDemogrFITBIR.Main Group.SiteNameDemogrFITBIR.Main Group.DaysSinceBaselineDemogrFITBIR.Main Group.CaseContrlIndDemogrFITBIR.Main Group.GeneralNotesTxtDemogrFITBIR.Form Administration.ContextTypeDemogrFITBIR.Form Administration.ContextTypeOTHDemogrFITBIR.Form Administration.DataSourceDemogrFITBIR.Form Administration.DataSourceOTHDemogrFITBIR.Subject Demographics.BirthDateDemogrFITBIR.Subject Demographics.GenderTypDemogrFITBIR.Subject Demographics.SexSubjectGenotypTypDemogrFITBIR.Subject Demographics.SexSubjectGenotypOTHDemogrFITBIR.Subject Demographics.HandPrefTypDemogrFITBIR.Subject Demographics.RaceUSACatDemogrFITBIR.Subject Demographics.RaceCatDemogrFITBIR.Subject Demographics.EthnUSACatDemogrFITBIR.Subject Demographics.EthnCatTxtDemogrFITBIR.Subject Country of Birth and Current Residency.BirthCntryISOCodeDemogrFITBIR.Subject Country of Birth and Current Residency.BirthCntryNameDemogrFITBIR.Subject Country of Birth and Current Residency.CntryResdnceISOCodeDemogrFITBIR.Subject Country of Birth and Current Residency.CntryResdnceNameDemogrFITBIR.Subject Language.LangPrimryTxtDemogrFITBIR.Subject Language.LangPrimryOTHDemogrFITBIR.Subject Language.LangSpokeFluentISOCodeDemogrFITBIR.Subject Language.LangSpokeFluentTxtDemogrFITBIR.Subject Language.LandWrtnFlntlyISOCodeDemogrFITBIR.Subject Language.LangWrtnFlntlyTxtDemogrFITBIR.Subject Marital Status.MartlPartnerStatusDemogrFITBIR.Subject Marital Status.MartlPartnerStatusOTHDemogrFITBIR.Subject Living Situation.SesPrimAdultDemogrFITBIR.Subject Living Situation.SesPrimAdultOtherDemogrFITBIR.Subject Living Situation.SesPrimChildDemogrFITBIR.Subject Living Situation.SesPrimChildOTHDemogrFITBIR.Subject Living Situation.LivingSituationPreInjTypDemogrFITBIR.Subject Living Situation.LivingSituationPreInjTypOTHDemogrFITBIR.Subject Living Situation.SubjectCohabitCtDemogrFITBIR.Subject Living Situation.DpndntChildLvngHshldNumDemogrFITBIR.Subject Living Situation.DependentChildNumDemogrFITBIR.Subject Living Situation.ResidenceAreaTypDemogrFITBIR.Subject Living Situation.ResdncTypDemogrFITBIR.Subject Living Situation.ResdncOTHDemogrFITBIR.Subject Family Income.FmlyIncRangeDemogrFITBIR.Subject Family Income.FamilyIncmeSupprtPersCtDemogrFITBIR.Subject Family Income.FamilyIncmeValDemogrFITBIR.Subject Family Income.HshldWgeEarnNumDemogrFITBIR.Subject Family Income.IncomeBasicNeedsStatusDemogrFITBIR.Subject Education.EduLvlUSATypDemogrFITBIR.Subject Education.EduLvlUSATypOTHDemogrFITBIR.Subject Education.EduTypDemogrFITBIR.Subject Education.EduOTHDemogrFITBIR.Subject Education.EduYrCtDemogrFITBIR.Subject Education.HighestLvlEduPreInjDemogrFITBIR.Subject Education.EduSchoolParticipStatusDemogrFITBIR.Subject Education.SchoolPlacementTypDemogrFITBIR.Subject Education.SchoolPlacementOTHDemogrFITBIR.Subject Occupation and Employment.OccupationPrimaryStatusDemogrFITBIR.Subject Occupation and Employment.OccupationPrimaryStatusOTHDemogrFITBIR.Subject Occupation and Employment.EmplmtExpndStatusDemogrFITBIR.Subject Occupation and Employment.EmplmtExpndOTHDemogrFITBIR.Subject Occupation and Employment.JobClassPreInjDemogrFITBIR.Subject Occupation and Employment.JobClassPreInjOTHDemogrFITBIR.Subject Occupation and Employment.JobClassNowDemogrFITBIR.Subject Occupation and Employment.JobClassNowOTHDemogrFITBIR.Subject Occupation and Employment.UnemplymntRsnDemogrFITBIR.Parent Guardian or Caregiver Information.CaregvPrimryExtendTypeDemogrFITBIR.Parent Guardian or Caregiver Information.CaregvPrimryExtendOTHDemogrFITBIR.Parent Guardian or Caregiver Information.ParentAliveStatusDemogrFITBIR.Parent Guardian or Caregiver Information.GenderTypDemogrFITBIR.Parent Guardian or Caregiver Information.RaceUSACatDemogrFITBIR.Parent Guardian or Caregiver Information.RaceCatDemogrFITBIR.Parent Guardian or Caregiver Information.EthnUSACatDemogrFITBIR.Parent Guardian or Caregiver Information.EthnCatTxtDemogrFITBIR.Parent Guardian or Caregiver Information.BirthCntryISOCodeDemogrFITBIR.Parent Guardian or Caregiver Information.BirthCntryNameDemogrFITBIR.Parent Guardian or Caregiver Information.MartlPartnerStatusDemogrFITBIR.Parent Guardian or Caregiver Information.DpndntChildLvngHshldNumDemogrFITBIR.Parent Guardian or Caregiver Information.DependentChildNumDemogrFITBIR.Parent Guardian or Caregiver Information.ResidenceAreaTypDemogrFITBIR.Parent Guardian or Caregiver Information.ResdncTypDemogrFITBIR.Parent Guardian or Caregiver Information.ResdncOTHDemogrFITBIR.Parent Guardian or Caregiver Information.EduLvlPrimCaregiverUSATypDemogrFITBIR.Parent Guardian or Caregiver Information.EduPrimCaregiverYrCtDemogrFITBIR.Parent Guardian or Caregiver Information.OccupationPrimaryStatusDemogrFITBIR.Parent Guardian or Caregiver Information.OccupationPrimaryStatusOTHDemogrFITBIR.Parent Guardian or Caregiver Information.JobclassCatDemogrFITBIR.Parent Guardian or Caregiver Information.EmplmtExpndStatusDemogrFITBIR.Parent Guardian or Caregiver Information.EmplmtExpndOTHDemogrFITBIR.Parent Guardian or Caregiver Information.UnemplymntRsnDemogrFITBIR.Parent Guardian or Caregiver Information.FmlyIncRangeDemogrFITBIR.Parent Guardian or Caregiver Information.FamilyIncmeValDemogrFITBIR.Parent Guardian or Caregiver Information.FamilyIncmeSupprtPersCtDemogrFITBIR.Subject Military Status.MilActiveIndDemogrFITBIR.Subject Military Status.MilMOSDemogrFITBIR.Subject Military Status.MilMOSOTHDemogrFITBIR.Subject Military Status.MilUSAServBrnchTypDemogrFITBIR.Subject Military Status.MilUSAServBrnchOTHDemogrFITBIR.Subject Military Status.MilRnkCatDemogrFITBIR.Subject Military Status.MilRnkCatOTHDemogrFITBIR.Subject Military Status.MilDeployDemogrFITBIR.Subject Military Status.MilDeployOTHDemogrFITBIR.Subject Involvement in Sports.TBISportIndDemogrFITBIR.Subject Involvement in Sports.ElementarySchoolSprtIndDemogrFITBIR.Subject Involvement in Sports.ElementarySchoolPrimaryPlayedDemogrFITBIR.Subject Involvement in Sports.ElementarPrimarySprtYrsNumDemogrFITBIR.Subject Involvement in Sports.ElementarySchoolSportOthrPlaydDemogrFITBIR.Subject Involvement in Sports.ElementarySchoolSportOtherYrsDemogrFITBIR.Subject Involvement in Sports.JuniorHighSchoolSportIndDemogrFITBIR.Subject Involvement in Sports.JuniorHighPrimarySportPlayedDemogrFITBIR.Subject Involvement in Sports.JuniorHighPrimarySprtYrsNumDemogrFITBIR.Subject Involvement in Sports.JuniorHighSportOtherplayedDemogrFITBIR.Subject Involvement in Sports.JuniorHighSportOtherYrsDemogrFITBIR.Subject Involvement in Sports.HighSchoolSportIndDemogrFITBIR.Subject Involvement in Sports.HighSchoolSportPrimaryplayedDemogrFITBIR.Subject Involvement in Sports.HighSchoolPrimarySportYearsDemogrFITBIR.Subject Involvement in Sports.HighSchoolSportOtherplayedDemogrFITBIR.Subject Involvement in Sports.HighSchoolSportOtherYearsDemogrFITBIR.Subject Involvement in Sports.CollegeSportIndDemogrFITBIR.Subject Involvement in Sports.CollegeSportPrimaryPlayedDemogrFITBIR.Subject Involvement in Sports.CollegeSportPrimaryYearsDemogrFITBIR.Subject Involvement in Sports.CollegeSportPlayedOTHDemogrFITBIR.Subject Involvement in Sports.CollegeSportOtherPlayedDemogrFITBIR.Subject Involvement in Sports.CollegeSportOtherYearsDemogrFITBIR.Subject Involvement in Sports.RecreationallSportIndDemogrFITBIR.Subject Involvement in Sports.RecreationaSportPrimaryPlayedDemogrFITBIR.Subject Involvement in Sports.RecreationaSportPrimaryYearsDemogrFITBIR.Subject Involvement in Sports.RecreationaSportOtherPlayedDemogrFITBIR.Subject Involvement in Sports.RecreationaSportOtherYearsDemogrFITBIR.Subject Involvement in Sports.ProfessionalSportIndDemogrFITBIR.Subject Involvement in Sports.ProfessionalSportPrimaryPlayedDemogrFITBIR.Subject Involvement in Sports.ProfessionalSportPrimaryYearsDemogrFITBIR.Subject Involvement in Sports.ProfessionalSportPlayedOTHDemogrFITBIR.Subject Involvement in Sports.ProfessionalSportOtherPlayedDemogrFITBIR.Subject Involvement in Sports.ProfessionalSportOtherYears
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2TBITW423YBL267FITBIR-DATA0011942TBITW423YBLNaNNaN27NaNNaN11.031944CaseCAMRIOther, specify2727Other, specify21595.0NaN46515BriskBrisk3.03.0RoundRoundNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN267FITBIR-DATA0012048TBITW423YBLNaNNaN27NaN1NaNCaseCAMRIOther, specifyHospital admit with ICUNaNNaNNaNFemaleNaNNaNLeft handBlack or African-AmericanNaNNot Hispanic or LatinoNaNNaN1.0NaN1.0engNaNNaNNaNNaNNaNNever marriedNaNParentsNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNUnder $15,000NaNNaNNaNNaNHigh school graduateNaNNaNNaNNaNNaNNeitherNaNNaNPaid workNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
3TBITW423YBL267FITBIR-DATA0011942TBITW423YBLNaNNaN27NaNNaN11.781944CaseCAMRIOther, specify2728Other, specify21613.0NaN46515BriskBrisk3.03.0RoundRoundNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN267FITBIR-DATA0012048TBITW423YBLNaNNaN27NaN1NaNCaseCAMRIOther, specifyHospital admit with ICUNaNNaNNaNFemaleNaNNaNLeft handBlack or African-AmericanNaNNot Hispanic or LatinoNaNNaN1.0NaN1.0engNaNNaNNaNNaNNaNNever marriedNaNParentsNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNUnder $15,000NaNNaNNaNNaNHigh school graduateNaNNaNNaNNaNNaNNeitherNaNNaNPaid workNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
4TBITW423YBL267FITBIR-DATA0011942TBITW423YBLNaNNaN27NaNNaN11.198611CaseCAMRIOther, specify2728Other, specify21599.0NaN46515BriskBrisk3.03.0RoundRoundNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN267FITBIR-DATA0012048TBITW423YBLNaNNaN27NaN1NaNCaseCAMRIOther, specifyHospital admit with ICUNaNNaNNaNFemaleNaNNaNLeft handBlack or African-AmericanNaNNot Hispanic or LatinoNaNNaN1.0NaN1.0engNaNNaNNaNNaNNaNNever marriedNaNParentsNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNUnder $15,000NaNNaNNaNNaNHigh school graduateNaNNaNNaNNaNNaNNeitherNaNNaNPaid workNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
\n", "
" ], "text/plain": [ " GUID GCS.Study ID GCS.Dataset GCS.Main.GUID \\\n", "0 TBITW423YBL 267 FITBIR-DATA0011942 TBITW423YBL \n", "1 TBITW423YBL 267 FITBIR-DATA0011942 TBITW423YBL \n", "2 TBITW423YBL 267 FITBIR-DATA0011942 TBITW423YBL \n", "3 TBITW423YBL 267 FITBIR-DATA0011942 TBITW423YBL \n", "4 TBITW423YBL 267 FITBIR-DATA0011942 TBITW423YBL \n", "\n", " GCS.Main.ASSOCIATED GUID GCS.Main.SubjectIDNum GCS.Main.AgeYrs \\\n", "0 NaN NaN 27 \n", "1 NaN NaN 27 \n", "2 NaN NaN 27 \n", "3 NaN NaN 27 \n", "4 NaN NaN 27 \n", "\n", " GCS.Main.VitStatus GCS.Main.VisitDate GCS.Main.SiteName \\\n", "0 NaN NaN 1 \n", "1 NaN NaN 1 \n", "2 NaN NaN 1 \n", "3 NaN NaN 1 \n", "4 NaN NaN 1 \n", "\n", " GCS.Main.DaysSinceBaseline GCS.Main.CaseContrlInd GCS.Main.GeneralNotesTxt \\\n", "0 0.740278 Case CAMRI \n", "1 2.031944 Case CAMRI \n", "2 1.031944 Case CAMRI \n", "3 1.781944 Case CAMRI \n", "4 1.198611 Case CAMRI \n", "\n", " GCS.Form Administration.ContextType GCS.Form Administration.ContextTypeOTH \\\n", "0 Other, specify 2727 \n", "1 Other, specify 2728 \n", "2 Other, specify 2727 \n", "3 Other, specify 2728 \n", "4 Other, specify 2728 \n", "\n", " GCS.Form Administration.DataSource GCS.Form Administration.DataSourceOTH \\\n", "0 Other, specify 21588.0 \n", "1 Other, specify 21619.0 \n", "2 Other, specify 21595.0 \n", "3 Other, specify 21613.0 \n", "4 Other, specify 21599.0 \n", "\n", " GCS.Glasgow Coma Scale.GCSConfounderTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " GCS.Glasgow Coma Scale.GCSEyeRespnsScale \\\n", "0 3 \n", "1 4 \n", "2 4 \n", "3 4 \n", "4 4 \n", "\n", " GCS.Glasgow Coma Scale.GCSMotorRespnsScale \\\n", "0 6 \n", "1 6 \n", "2 6 \n", "3 6 \n", "4 6 \n", "\n", " GCS.Glasgow Coma Scale.GCSVerbalRspnsScale \\\n", "0 5 \n", "1 5 \n", "2 5 \n", "3 5 \n", "4 5 \n", "\n", " GCS.Glasgow Coma Scale.GCSTotalScore \\\n", "0 14 \n", "1 15 \n", "2 15 \n", "3 15 \n", "4 15 \n", "\n", " GCS.Glasgow Coma Scale.PupilReactivityLghtLftEyeReslt \\\n", "0 Brisk \n", "1 Brisk \n", "2 Brisk \n", "3 Brisk \n", "4 Brisk \n", "\n", " GCS.Glasgow Coma Scale.PupilReactivityLghtRtEyeReslt \\\n", "0 Brisk \n", "1 Brisk \n", "2 Brisk \n", "3 Brisk \n", "4 Brisk \n", "\n", " GCS.Glasgow Coma Scale.PupilLftEyeMeasr \\\n", "0 3.0 \n", "1 3.0 \n", "2 3.0 \n", "3 3.0 \n", "4 3.0 \n", "\n", " GCS.Glasgow Coma Scale.PupilRtEyeMeasr \\\n", "0 3.0 \n", "1 3.0 \n", "2 3.0 \n", "3 3.0 \n", "4 3.0 \n", "\n", " GCS.Glasgow Coma Scale.PupilShapeLftEyeTyp \\\n", "0 Round \n", "1 Round \n", "2 Round \n", "3 Round \n", "4 Round \n", "\n", " GCS.Glasgow Coma Scale.PupilShapeRtEyeTyp \\\n", "0 Round \n", "1 Round \n", "2 Round \n", "3 Round \n", "4 Round \n", "\n", " GCS.Pediatric Glasgow Coma Scale.GCSConfounderTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " GCS.Pediatric Glasgow Coma Scale.PGCSEyeRespnsScore \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " GCS.Pediatric Glasgow Coma Scale.PGCSMotorRespnsScore \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " GCS.Pediatric Glasgow Coma Scale.PGCSVerbalRespnsScore \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " GCS.Pediatric Glasgow Coma Scale.PGCSTotalScore \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " GCS.Pediatric Glasgow Coma Scale.PupilReactivityLghtLftEyeReslt \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " GCS.Pediatric Glasgow Coma Scale.PupilReactivityLghtRtEyeReslt \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " GCS.Pediatric Glasgow Coma Scale.PupilLftEyeMeasr \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " GCS.Pediatric Glasgow Coma Scale.PupilRtEyeMeasr \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " GCS.Pediatric Glasgow Coma Scale.PupilShapeLftEyeTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " GCS.Pediatric Glasgow Coma Scale.PupilShapeRtEyeTyp DemogrFITBIR.Study ID \\\n", "0 NaN 267 \n", "1 NaN 267 \n", "2 NaN 267 \n", "3 NaN 267 \n", "4 NaN 267 \n", "\n", " DemogrFITBIR.Dataset DemogrFITBIR.Main Group.GUID \\\n", "0 FITBIR-DATA0012048 TBITW423YBL \n", "1 FITBIR-DATA0012048 TBITW423YBL \n", "2 FITBIR-DATA0012048 TBITW423YBL \n", "3 FITBIR-DATA0012048 TBITW423YBL \n", "4 FITBIR-DATA0012048 TBITW423YBL \n", "\n", " DemogrFITBIR.Main Group.ASSOCIATED GUID \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Main Group.SubjectIDNum DemogrFITBIR.Main Group.AgeYrs \\\n", "0 NaN 27 \n", "1 NaN 27 \n", "2 NaN 27 \n", "3 NaN 27 \n", "4 NaN 27 \n", "\n", " DemogrFITBIR.Main Group.VisitDate DemogrFITBIR.Main Group.SiteName \\\n", "0 NaN 1 \n", "1 NaN 1 \n", "2 NaN 1 \n", "3 NaN 1 \n", "4 NaN 1 \n", "\n", " DemogrFITBIR.Main Group.DaysSinceBaseline \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Main Group.CaseContrlInd \\\n", "0 Case \n", "1 Case \n", "2 Case \n", "3 Case \n", "4 Case \n", "\n", " DemogrFITBIR.Main Group.GeneralNotesTxt \\\n", "0 CAMRI \n", "1 CAMRI \n", "2 CAMRI \n", "3 CAMRI \n", "4 CAMRI \n", "\n", " DemogrFITBIR.Form Administration.ContextType \\\n", "0 Other, specify \n", "1 Other, specify \n", "2 Other, specify \n", "3 Other, specify \n", "4 Other, specify \n", "\n", " DemogrFITBIR.Form Administration.ContextTypeOTH \\\n", "0 Hospital admit with ICU \n", "1 Hospital admit with ICU \n", "2 Hospital admit with ICU \n", "3 Hospital admit with ICU \n", "4 Hospital admit with ICU \n", "\n", " DemogrFITBIR.Form Administration.DataSource \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Form Administration.DataSourceOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Demographics.BirthDate \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Demographics.GenderTyp \\\n", "0 Female \n", "1 Female \n", "2 Female \n", "3 Female \n", "4 Female \n", "\n", " DemogrFITBIR.Subject Demographics.SexSubjectGenotypTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Demographics.SexSubjectGenotypOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Demographics.HandPrefTyp \\\n", "0 Left hand \n", "1 Left hand \n", "2 Left hand \n", "3 Left hand \n", "4 Left hand \n", "\n", " DemogrFITBIR.Subject Demographics.RaceUSACat \\\n", "0 Black or African-American \n", "1 Black or African-American \n", "2 Black or African-American \n", "3 Black or African-American \n", "4 Black or African-American \n", "\n", " DemogrFITBIR.Subject Demographics.RaceCat \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Demographics.EthnUSACat \\\n", "0 Not Hispanic or Latino \n", "1 Not Hispanic or Latino \n", "2 Not Hispanic or Latino \n", "3 Not Hispanic or Latino \n", "4 Not Hispanic or Latino \n", "\n", " DemogrFITBIR.Subject Demographics.EthnCatTxt \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Country of Birth and Current Residency.BirthCntryISOCode \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Country of Birth and Current Residency.BirthCntryName \\\n", "0 1.0 \n", "1 1.0 \n", "2 1.0 \n", "3 1.0 \n", "4 1.0 \n", "\n", " DemogrFITBIR.Subject Country of Birth and Current Residency.CntryResdnceISOCode \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Country of Birth and Current Residency.CntryResdnceName \\\n", "0 1.0 \n", "1 1.0 \n", "2 1.0 \n", "3 1.0 \n", "4 1.0 \n", "\n", " DemogrFITBIR.Subject Language.LangPrimryTxt \\\n", "0 eng \n", "1 eng \n", "2 eng \n", "3 eng \n", "4 eng \n", "\n", " DemogrFITBIR.Subject Language.LangPrimryOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Language.LangSpokeFluentISOCode \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Language.LangSpokeFluentTxt \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Language.LandWrtnFlntlyISOCode \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Language.LangWrtnFlntlyTxt \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Marital Status.MartlPartnerStatus \\\n", "0 Never married \n", "1 Never married \n", "2 Never married \n", "3 Never married \n", "4 Never married \n", "\n", " DemogrFITBIR.Subject Marital Status.MartlPartnerStatusOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Living Situation.SesPrimAdult \\\n", "0 Parents \n", "1 Parents \n", "2 Parents \n", "3 Parents \n", "4 Parents \n", "\n", " DemogrFITBIR.Subject Living Situation.SesPrimAdultOther \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Living Situation.SesPrimChild \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Living Situation.SesPrimChildOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Living Situation.LivingSituationPreInjTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Living Situation.LivingSituationPreInjTypOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Living Situation.SubjectCohabitCt \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Living Situation.DpndntChildLvngHshldNum \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Living Situation.DependentChildNum \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Living Situation.ResidenceAreaTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Living Situation.ResdncTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Living Situation.ResdncOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Family Income.FmlyIncRange \\\n", "0 Under $15,000 \n", "1 Under $15,000 \n", "2 Under $15,000 \n", "3 Under $15,000 \n", "4 Under $15,000 \n", "\n", " DemogrFITBIR.Subject Family Income.FamilyIncmeSupprtPersCt \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Family Income.FamilyIncmeVal \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Family Income.HshldWgeEarnNum \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Family Income.IncomeBasicNeedsStatus \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Education.EduLvlUSATyp \\\n", "0 High school graduate \n", "1 High school graduate \n", "2 High school graduate \n", "3 High school graduate \n", "4 High school graduate \n", "\n", " DemogrFITBIR.Subject Education.EduLvlUSATypOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Education.EduTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Education.EduOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Education.EduYrCt \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Education.HighestLvlEduPreInj \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Education.EduSchoolParticipStatus \\\n", "0 Neither \n", "1 Neither \n", "2 Neither \n", "3 Neither \n", "4 Neither \n", "\n", " DemogrFITBIR.Subject Education.SchoolPlacementTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Education.SchoolPlacementOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Occupation and Employment.OccupationPrimaryStatus \\\n", "0 Paid work \n", "1 Paid work \n", "2 Paid work \n", "3 Paid work \n", "4 Paid work \n", "\n", " DemogrFITBIR.Subject Occupation and Employment.OccupationPrimaryStatusOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Occupation and Employment.EmplmtExpndStatus \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Occupation and Employment.EmplmtExpndOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Occupation and Employment.JobClassPreInj \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Occupation and Employment.JobClassPreInjOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Occupation and Employment.JobClassNow \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Occupation and Employment.JobClassNowOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Occupation and Employment.UnemplymntRsn \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.CaregvPrimryExtendType \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.CaregvPrimryExtendOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.ParentAliveStatus \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.GenderTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.RaceUSACat \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.RaceCat \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.EthnUSACat \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.EthnCatTxt \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.BirthCntryISOCode \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.BirthCntryName \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.MartlPartnerStatus \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.DpndntChildLvngHshldNum \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.DependentChildNum \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.ResidenceAreaTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.ResdncTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.ResdncOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.EduLvlPrimCaregiverUSATyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.EduPrimCaregiverYrCt \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.OccupationPrimaryStatus \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.OccupationPrimaryStatusOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.JobclassCat \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.EmplmtExpndStatus \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.EmplmtExpndOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.UnemplymntRsn \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.FmlyIncRange \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.FamilyIncmeVal \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Parent Guardian or Caregiver Information.FamilyIncmeSupprtPersCt \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Military Status.MilActiveInd \\\n", "0 No \n", "1 No \n", "2 No \n", "3 No \n", "4 No \n", "\n", " DemogrFITBIR.Subject Military Status.MilMOS \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Military Status.MilMOSOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Military Status.MilUSAServBrnchTyp \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Military Status.MilUSAServBrnchOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Military Status.MilRnkCat \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Military Status.MilRnkCatOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Military Status.MilDeploy \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Military Status.MilDeployOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.TBISportInd \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.ElementarySchoolSprtInd \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.ElementarySchoolPrimaryPlayed \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.ElementarPrimarySprtYrsNum \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.ElementarySchoolSportOthrPlayd \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.ElementarySchoolSportOtherYrs \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.JuniorHighSchoolSportInd \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.JuniorHighPrimarySportPlayed \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.JuniorHighPrimarySprtYrsNum \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.JuniorHighSportOtherplayed \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.JuniorHighSportOtherYrs \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.HighSchoolSportInd \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.HighSchoolSportPrimaryplayed \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.HighSchoolPrimarySportYears \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.HighSchoolSportOtherplayed \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.HighSchoolSportOtherYears \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.CollegeSportInd \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.CollegeSportPrimaryPlayed \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.CollegeSportPrimaryYears \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.CollegeSportPlayedOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.CollegeSportOtherPlayed \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.CollegeSportOtherYears \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.RecreationallSportInd \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.RecreationaSportPrimaryPlayed \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.RecreationaSportPrimaryYears \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.RecreationaSportOtherPlayed \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.RecreationaSportOtherYears \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.ProfessionalSportInd \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.ProfessionalSportPrimaryPlayed \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.ProfessionalSportPrimaryYears \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.ProfessionalSportPlayedOTH \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.ProfessionalSportOtherPlayed \\\n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "\n", " DemogrFITBIR.Subject Involvement in Sports.ProfessionalSportOtherYears \n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN " ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.set_option('display.max_columns', None)\n", "dataset = query.text\n", "texttodf = StringIO(dataset)\n", "fitbir_data = pd.read_csv(texttodf, sep=\",\",low_memory=False)\n", "fitbir_data.head()" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "(array([1645., 1660., 1749., 927., 821., 639., 781., 570., 742.,\n", " 1240.]),\n", " array([20., 23., 26., 29., 32., 35., 38., 41., 44., 47., 50.]),\n", " )" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Check that filtering \n", "import matplotlib.pyplot as plt\n", "plt.hist(fitbir_data['GCS.Main.AgeYrs'])" ] }, { "cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['Female'], dtype=object)" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "fitbir_data['DemogrFITBIR.Subject Demographics.GenderTyp'].unique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Output JSON Format \n", "See Swagger-UI https://fitbir.nih.gov/gateway/query-api/swagger-ui/index.html#/data/getInstancedDataJson for more information regarding this endpoint" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [], "source": [ "queryurl =\"https://\" + BRICSInstance + \"/gateway/query-api/data/json\"\n", "\n", "headers = {\n", " 'accept': 'application/json',\n", " 'Content-type': 'application/json',\n", " 'Authorization':'Bearer ' + token }" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "query = requests.post(queryurl,headers=headers,json=filterForQuery)\n", "query" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Response: \n", "Data received: query_result_GCS_join_DemogrFITBIR_2024-04-10T09-34-0711890295064841579210.\n" ] } ], "source": [ "print(f\"Response: {query}\")\n", "print(\"Data received: \" + query.headers[\"Content-Disposition\"][21:96]) " ] }, { "cell_type": "code", "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[{'guid': 'TBITW423YBL',\n", " 'forms': [{'name': 'GCSV1.2',\n", " 'studyId': 'FITBIR-STUDY0000267',\n", " 'datasetId': 'FITBIR-DATA0011942',\n", " 'repeatableGroups': [{'name': 'Main',\n", " 'data': [[{'GUID': 'TBITW423YBL'},\n", " {'SubjectIDNum': ''},\n", " {'AgeYrs': '27'},\n", " {'VitStatus': ''},\n", " {'VisitDate': ''},\n", " {'SiteName': '1'},\n", " {'DaysSinceBaseline': '0.740277778'},\n", " {'CaseContrlInd': 'Case'},\n", " {'GeneralNotesTxt': 'CAMRI'}]]},\n", " {'name': 'Form Administration',\n", " 'data': [[[{'ContextType': 'Other, specify'},\n", " {'ContextTypeOTH': '2727'},\n", " {'DataSource': 'Other, specify'},\n", " {'DataSourceOTH': '21588'}]]]},\n", " {'name': 'Glasgow Coma Scale',\n", " 'data': [[[{'GCSConfounderTyp': ''},\n", " {'GCSEyeRespnsScale': '3'},\n", " {'GCSMotorRespnsScale': '6'},\n", " {'GCSVerbalRspnsScale': '5'},\n", " {'GCSTotalScore': '14'},\n", " {'PupilReactivityLghtLftEyeReslt': 'Brisk'},\n", " {'PupilReactivityLghtRtEyeReslt': 'Brisk'},\n", " {'PupilLftEyeMeasr': '3'},\n", " {'PupilRtEyeMeasr': '3'},\n", " {'PupilShapeLftEyeTyp': 'Round'},\n", " {'PupilShapeRtEyeTyp': 'Round'}]]]},\n", " {'name': 'Pediatric Glasgow Coma Scale',\n", " 'data': [[[{'GCSConfounderTyp': ''},\n", " {'PGCSEyeRespnsScore': ''},\n", " {'PGCSMotorRespnsScore': ''},\n", " {'PGCSVerbalRespnsScore': ''},\n", " {'PGCSTotalScore': ''},\n", " {'PupilReactivityLghtLftEyeReslt': ''},\n", " {'PupilReactivityLghtRtEyeReslt': ''},\n", " {'PupilLftEyeMeasr': ''},\n", " {'PupilRtEyeMeasr': ''},\n", " {'PupilShapeLftEyeTyp': ''},\n", " {'PupilShapeRtEyeTyp': ''}]]]}]},\n", " {'name': 'DemogrFITBIRV1.1',\n", " 'studyId': 'FITBIR-STUDY0000267',\n", " 'datasetId': 'FITBIR-DATA0012048',\n", " 'repeatableGroups': [{'name': 'Main Group',\n", " 'data': [[{'GUID': 'TBITW423YBL'},\n", " {'SubjectIDNum': ''},\n", " {'AgeYrs': '27'},\n", " {'VisitDate': ''},\n", " {'SiteName': '1'},\n", " {'DaysSinceBaseline': ''},\n", " {'CaseContrlInd': 'Case'},\n", " {'GeneralNotesTxt': 'CAMRI'}]]},\n", " {'name': 'Form Administration',\n", " 'data': [[{'ContextType': 'Other, specify'},\n", " {'ContextTypeOTH': 'Hospital admit with ICU'},\n", " {'DataSource': ''},\n", " {'DataSourceOTH': ''}]]},\n", " {'name': 'Subject Demographics',\n", " 'data': [[{'BirthDate': ''},\n", " {'GenderTyp': 'Female'},\n", " {'SexSubjectGenotypTyp': ''},\n", " {'SexSubjectGenotypOTH': ''},\n", " {'HandPrefTyp': 'Left hand'},\n", " {'RaceUSACat': 'Black or African-American'},\n", " {'RaceCat': ''},\n", " {'EthnUSACat': 'Not Hispanic or Latino'},\n", " {'EthnCatTxt': ''}]]},\n", " {'name': 'Subject Country of Birth and Current Residency',\n", " 'data': [[[{'BirthCntryISOCode': ''},\n", " {'BirthCntryName': '1'},\n", " {'CntryResdnceISOCode': ''},\n", " {'CntryResdnceName': '1'}]]]},\n", " {'name': 'Subject Language',\n", " 'data': [[{'LangPrimryTxt': 'eng'},\n", " {'LangPrimryOTH': ''},\n", " {'LangSpokeFluentISOCode': ''},\n", " {'LangSpokeFluentTxt': ''},\n", " {'LandWrtnFlntlyISOCode': ''},\n", " {'LangWrtnFlntlyTxt': ''}]]},\n", " {'name': 'Subject Marital Status',\n", " 'data': [[[{'MartlPartnerStatus': 'Never married'},\n", " {'MartlPartnerStatusOTH': ''}]]]},\n", " {'name': 'Subject Living Situation',\n", " 'data': [[[{'SesPrimAdult': 'Parents'},\n", " {'SesPrimAdultOther': ''},\n", " {'SesPrimChild': ''},\n", " {'SesPrimChildOTH': ''},\n", " {'LivingSituationPreInjTyp': ''},\n", " {'LivingSituationPreInjTypOTH': ''},\n", " {'SubjectCohabitCt': ''},\n", " {'DpndntChildLvngHshldNum': ''},\n", " {'DependentChildNum': ''},\n", " {'ResidenceAreaTyp': ''},\n", " {'ResdncTyp': ''},\n", " {'ResdncOTH': ''}]]]},\n", " {'name': 'Subject Family Income',\n", " 'data': [[{'FmlyIncRange': 'Under $15,000'},\n", " {'FamilyIncmeSupprtPersCt': ''},\n", " {'FamilyIncmeVal': ''},\n", " {'HshldWgeEarnNum': ''},\n", " {'IncomeBasicNeedsStatus': ''}]]},\n", " {'name': 'Subject Education',\n", " 'data': [[[{'EduLvlUSATyp': 'High school graduate'},\n", " {'EduLvlUSATypOTH': ''},\n", " {'EduTyp': ''},\n", " {'EduOTH': ''},\n", " {'EduYrCt': ''},\n", " {'HighestLvlEduPreInj': ''},\n", " {'EduSchoolParticipStatus': 'Neither'},\n", " {'SchoolPlacementTyp': ''},\n", " 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{'ProfessionalSportInd': ''},\n", " {'ProfessionalSportPrimaryPlayed': ''},\n", " {'ProfessionalSportPrimaryYears': ''},\n", " {'ProfessionalSportPlayedOTH': ''},\n", " {'ProfessionalSportOtherPlayed': ''},\n", " {'ProfessionalSportOtherYears': ''}]]]}]}]},\n", " {'guid': 'TBIFE680FR4',\n", " 'forms': [{'name': 'GCSV1.2',\n", " 'studyId': 'FITBIR-STUDY0000267',\n", " 'datasetId': 'FITBIR-DATA0011942',\n", " 'repeatableGroups': [{'name': 'Main',\n", " 'data': [[{'GUID': 'TBIFE680FR4'},\n", " {'SubjectIDNum': ''},\n", " {'AgeYrs': '23'},\n", " {'VitStatus': ''},\n", " {'VisitDate': ''},\n", " {'SiteName': '1'},\n", " {'DaysSinceBaseline': '1.790277778'},\n", " {'CaseContrlInd': 'Case'},\n", " {'GeneralNotesTxt': 'CA'}]]},\n", " {'name': 'Form Administration',\n", " 'data': [[[{'ContextType': 'Other, specify'},\n", " {'ContextTypeOTH': '5621'},\n", " {'DataSource': 'Other, specify'},\n", " {'DataSourceOTH': '45126'}]]]},\n", " {'name': 'Glasgow Coma Scale',\n", " 'data': 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'repeatableGroups': [{'name': 'Main Group',\n", " 'data': [[{'GUID': 'TBIFE680FR4'},\n", " {'SubjectIDNum': ''},\n", " {'AgeYrs': '23'},\n", " {'VisitDate': ''},\n", " {'SiteName': '1'},\n", " {'DaysSinceBaseline': ''},\n", " {'CaseContrlInd': 'Case'},\n", " {'GeneralNotesTxt': 'CA'}]]},\n", " {'name': 'Form Administration',\n", " 'data': [[{'ContextType': 'Other, specify'},\n", " {'ContextTypeOTH': 'Hospital admit with ICU'},\n", " {'DataSource': ''},\n", " {'DataSourceOTH': ''}]]},\n", " {'name': 'Subject Demographics',\n", " 'data': [[{'BirthDate': ''},\n", " {'GenderTyp': 'Female'},\n", " {'SexSubjectGenotypTyp': ''},\n", " {'SexSubjectGenotypOTH': ''},\n", " {'HandPrefTyp': 'Right hand'},\n", " {'RaceUSACat': 'White'},\n", " {'RaceCat': ''},\n", " {'EthnUSACat': 'Hispanic or Latino'},\n", " {'EthnCatTxt': ''}]]},\n", " {'name': 'Subject Country of Birth and Current Residency',\n", " 'data': [[[{'BirthCntryISOCode': ''},\n", " {'BirthCntryName': '1'},\n", " {'CntryResdnceISOCode': ''},\n", " {'CntryResdnceName': '1'}]]]},\n", " {'name': 'Subject Language',\n", " 'data': [[{'LangPrimryTxt': 'eng'},\n", " {'LangPrimryOTH': ''},\n", " {'LangSpokeFluentISOCode': ''},\n", " {'LangSpokeFluentTxt': ''},\n", " {'LandWrtnFlntlyISOCode': ''},\n", " {'LangWrtnFlntlyTxt': ''}]]},\n", " {'name': 'Subject Marital Status',\n", " 'data': [[[{'MartlPartnerStatus': 'Never married'},\n", " {'MartlPartnerStatusOTH': ''}]]]},\n", " {'name': 'Subject Living Situation',\n", " 'data': [[[{'SesPrimAdult': 'Other residents'},\n", " {'SesPrimAdultOther': ''},\n", " {'SesPrimChild': ''},\n", " {'SesPrimChildOTH': ''},\n", " {'LivingSituationPreInjTyp': ''},\n", " {'LivingSituationPreInjTypOTH': ''},\n", " {'SubjectCohabitCt': ''},\n", " {'DpndntChildLvngHshldNum': ''},\n", " {'DependentChildNum': ''},\n", " {'ResidenceAreaTyp': ''},\n", " {'ResdncTyp': ''},\n", " {'ResdncOTH': ''}]]]},\n", " {'name': 'Subject Family Income',\n", " 'data': [[{'FmlyIncRange': 'Unknown'},\n", " 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