As the number of Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF) Traumatic Brain Injury (TBI) patients has grown, so has the need to track and monitor care to meet the lifelong needs of these veterans. In March 2007, a Computerized Patient Record System (CPRS) OIF/OEF TBI Screening Reminder was released. This is a first-line screening tool to identify potential TBI patients. Additional information about veterans who have been identified as possible TBI patients by the initial Screening Reminder is collected through a Comprehensive TBI evaluation. Reminder results, in the form of Health Factors, Comprehensive TBI evaluation data, and Comprehensive TBI Follow-up results of individual Veterans will be sent to a national database. This data will be aggregated in order to provide relevant responses to key stakeholders, such as members of Congress, to monitor the quality of care and to implement system improvements. In addition, tracking applications will be used to collect data on TBI patient appointments.

The CENTER-TBI database contains prospectively collected data of more than 4,500 patients with TBI in Europe. The Registry and Acute Care data has been collected during a 3 years’ period (2015-2017) in 65 centers in Europe. For all patients, outcome data has been collected up to 2 years after injury.

ObjectiveTraumatic brain injury (TBI) is one of the leading causes of death and disability worldwide. In this study, the characteristics of the patients, who were admitted to the China Rehabilitation Research Center, were elucidated in the TBI database, and a prediction model based on the Fugl-Meyer assessment scale (FMA) was established using this database.MethodsA retrospective analysis of 463 TBI patients, who were hospitalized from June 2016 to June 2020, was performed. The data of the patients used for this study included the age and gender of the patients, course of TBI, complications, and concurrent dysfunctions, which were assessed using FMA and other measures. The information was collected at the time of admission to the hospital and 1 month after hospitalization. After 1 month, a prediction model, based on the correlation analyses and a 1-layer genetic algorithms modified back propagation (GA-BP) neural network with 175 patients, was established to predict the FMA. The correlations between the predicted and actual values of 58 patients (prediction set) were described.ResultsMost of the TBI patients, included in this study, had severe conditions (70%). The main causes of the TBI were car accidents (56.59%), while the most common complication and dysfunctions were hydrocephalus (46.44%) and cognitive and motor dysfunction (65.23 and 63.50%), respectively. A total of 233 patients were used in the prediction model, studying the 11 prognostic factors, such as gender, course of the disease, epilepsy, and hydrocephalus. The correlation between the predicted and the actual value of 58 patients was R2 = 0.95.ConclusionThe genetic algorithms modified back propagation neural network can predict motor function in patients with traumatic brain injury, which can be used as a reference for risk and prognosis assessment and guide clinical decision-making.

This Service provides access to Tramatic Brain injury patient data consult notes. The service also provides one write service method writeNote. The Service supports single site data access. Users of this Service are intended to be healthcare providers.

In general, total combined rates for traumatic brain injury (TBI)-related emergency department (ED) visits, hospitalizations and deaths have increased over the past decade. Total combined rates of TBI-related hospitalizations, ED visits, and deaths climbed slowly from a rate of 521.0 per 100,000 in 2001 to 615.7 per 100,000 in 2005. The rates then dipped to 595.1 per 100,000 in 2006 and 566.7 per 100,000 in 2007. The rates then spiked sharply in 2008 and continued to climb through 2010 to a rate of 823.7 per 100,000. Total combined rates of TBI-related hospitalizations, ED visits, and deaths are driven in large part by the relatively high number of TBI-related ED visits. In comparison to ED visits, the overall rates of TBI-related hospitalizations remained relatively stable changing from 82.7 per 100,000 in 2001 to 91.7 per 100,000 in 2010. TBI-related deaths also decreased slightly over time from 18.5 per 100,000 in 2001 to 17.1 per 100,000 in 2010. Note that the axis scale for TBI-related deaths appears to the right of the chart and differs from TBI-related hospitalizations and ED visits.Go to http://www.cdc.gov/traumaticbraininjury/data/index.html to view more TBI data & statistics.

Software as cloud based community driven repository to store, share, and publish traumatic brain injury research data. Aims to increase transparency with individual level data, enhance collaboration, facilitate advanced analytics, and conform to increasing mandates by funders and publishers to make data accessible. Members of ODC-TBI have access to private digital lab space managed by PI or multi-PIs for dataset storage and sharing. PIs can share their labs’ datasets with registered members of ODC-TBI community and make their datasets public and citable. ODC-TBI implements stewardship principles that scientific data be made FAIR (Findable, Accessible, Interoperable and Reusable).

CI, confidence interval; HR, hazard ratio; TBI, traumatic brain injury; HRs with a 95% CI and their P values were calculated using a Cox proportional-hazards regression model.Incidence and hazard ratios for herpes zoster and postherpetic neuralgia during the follow-up period for surgical versus nonsurgical traumatic brain injury patients.

Changes in the rates of TBI-related deaths vary depending on age. For persons 44 years of age and younger, TBI-related deaths decreased between the periods of 2001-2002 and 2009-2010. Rates for age groups 45-64 years of age remained stable for this same ten-year period. For persons 65 years and older, rates of TBI-related deaths increased during this time period, from 41.2 to 45.2 deaths per 100,000.Go to http://www.cdc.gov/traumaticbraininjury/data/index.html to view more TBI data & statistics.Source: http://www.cdc.gov/traumaticbraininjury/data/rates_deaths_byage.html

The Federal Interagency Traumatic Brain Injury Research (FITBIR) informatics system is an extensible, scalable informatics platform for TBI relevant imaging, assessment, genomics, and other data types. It was developed to share data across the entire TBI research field and to facilitate collaboration between laboratories, as well as interconnectivity with other informatics platforms.

The dataset contains summary statistics for the genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in traumatic brain injury (TBI). The study participants attended hospital within 24 hours of TBI, and underwent head computed tomography imaging.

Study participants

European ancestry data set contains 4710 individuals; multi-ethnic cohort 5268 individuals, including Europeans (n = 4710), Africans (n = 245) and Admixed Americans (n = 313).

The largest European population contribution was from CENTER-TBI (Collaborative European NeuroTrauma Effectiveness Research, https://www.center-tbi.eu), where each participating center (60 centers from 20 countries in Europe) recruited patients between December 2013 and December 2017. The patients recruited in CENTER-TBI were supplemented by subjects from cohorts recruited at two European centres (Cambridge, UK, and Turku, Finland).

The majority of patients in the US cohort were recruited between 2014 and 2018 to TRACK-TBI (Transforming Research and Clinical Knowledge in TBI, https://tracktbi.ucsf.edu) by the 18 US participant sites. The subjects recruited to the US cohort from TRACK-TBI were supplemented by patients recruited to an institutional research initiative at Mass General Brigham (MGB).

Outcome definition

Outcomes were measured using the extended Glasgow Outcome Scale (GOSE), ranging from 1 (dead) to 8 (upper good recovery), measured 6 months post-TBI. TBI severity was specified using the Glasgow Coma Score (GCS), with TBI classified as mild (GCS 13-15), moderate (GCS 9-12), or severe (GCS 3-8).

To account for the effect of injury severity on outcome, sliding dichotomization was used to categorize outcome as favourable or unfavourable. A GOSE ≤ 4 was used to define an unfavourable outcome for patients with either moderate (GCS 9-12) or severe (GCS 3-8) TBI, while the unfavourable group was extended to patients with GOSE ≤ 7 if they had mild (GCS 13-15) TBI.

Genotype data and imputation

Genotyping was completed at FIMM Technology Center for CENTER-TBI, Cambridge, Turku patients and the Broad Institute for TRACK-TBI, using the Illumina Global Screening Array (GSA-24v2-0 + Multi-Disease). The MGB cohort were genotyped using Illumina’s Multi-Ethnic Global array (MEGA) and the pre-releases forms, including MEGA and MEGA-Ex arrays at Illumina at the MGB Translational Genomics Core.

A unified quality control procedure was applied for each study cohort and the array-based genotypes were imputed using the Haplotype Reference Consortium panel. Autosomal chromosomes were considered, post-imputation data was filtered by imputation quality (INFO > 0.4 for CENTER-TBI, Cambridge and Turku; R2 > 0.4 for TRACK-TBI and MGB) and MAF > 1%.

Genome-wide association analysis and meta-analysis

Genome-wide single-marker scans were performed using a penalized likelihood-based Firth logistic regression, and implemented in PLINK v2.0. Using favourable outcome as reference, models were fitted on the basis of imputed allelic dosages. Age, sex, major extracranial injury, pupillary reactivity, and the first 10 principal components were included as covariates. Study cohort (CENTER-TBI, Cambridge, Turku) was an additional covariate in the CENTER-TBI GWAS.

Fixed-effects meta-analysis of the three European ancestry GWAS was performed using METAL. For trans-ethnic meta-analysis, summary statistics of five GWASs in patients of European, African and Admixed Americans were aggregated via MR-MEGA.

Transcriptome-wide association study

Genetically regulated gene expression (GREx) was imputed using a regression model fitted on a separate gene expression database. Elastic net models provided by PrediXcan for all available GTEx brain tissues and whole blood were used. For TWAS, the same sliding dichotomy model for outcome with the same set of covariates as in the GWAS, but PCA components were replaced with the top five principal components of the respective gene expression data.

Column headers - GWAS

rsID: variant rsID
Chrom: chromosome
Pos: position (build GRCh38)
A1: effect allele
A2: reference allele
EAF: allele frequency of effect allele
Effect: effect size of effect allele
StdErr: standard error of effect size
P: p value of association (with genomic correction)
N: sample size

Note. 'Effect' and 'StdErr' are only available for the European ancestry meta-analysis.

Column headers - TWAS

tissue: GTEx tissue type
id: ensembl gene id
coef: model coefficient
se: model standard error for coefficient
p: model-based p value
symbol: gene symbol
name: gene name written out
chr: chromosome
start: gene start position (build GRCh38)

TBI, traumatic brain injury; SD, standard deviation; HZ, herpes zosterCharacteristics of adult patients with traumatic brain injury and control cohorts in Taiwan, 1996–2010.

STUDY PURPOSE: The dataset was created to provide descriptions of the animal subjects with data uploaded to the ODC-TBI (but not necessarily published yet).DATA COLLECTED: The metadata was aggregated from 11 papers published from the labs of Susanna Rosi, Michael S Beattie, Jacqueline C Bresnahan, and Adam R Ferguson from UCSF as well as the dataset published by Bridget E Hawkins through the ODC-TBI (DOI:10.34945/F51591). The animal species, strain, sex, genotype and age at time of injury are included in addition to the preclinical TBI model used, the experimental group the subject was assigned to, and the time post-injury of the data entry. The dataset contains a total of N=1250 animals with 3313 observations total. Subject IDs are provided to align this data to the corresponding datasets when they are published.DATA USAGE NOTES: The data was summarized to describe a cohort of animals with data uploaded by January 2021.

HZ, herpes zoster; CI, confidence interval; HR, hazard ratio; TBI, traumatic brain injury.aAdjusted HRs with 95% CI and their P values. The results were adjusted for age and Charlson comorbidity index using a Cox proportional-hazards regression model.bAdjusted HRs with 95% CI and their P values. The results were adjusted for age, sex and Charlson comorbidity index using a Cox proportional-hazards regression model.P for interaction: a Cox proportional-hazards regression model including a gender x TBI interaction was appliedIncidence and hazard ratios for herpes zoster during the follow-up period for adult patients with traumatic brain injury versus control cohorts.

The Aging, Dementia and Traumatic Brain Injury Study is a detailed neuropathologic, molecular and transcriptomic characterization of brains of control and TBI exposure cases from a unique aged population-based cohort from the Adult Changes in Thought (ACT) study. The study contains six data sets: histology and immunohistochemistry, in situ hybridization, rna-seq, protein quantification by luminex, isoprostane quantification, and specimen metadata.

The Open Data Commons for Traumatic Brain Injury is a cloud-based community-driven repository to store, share, and publish traumatic brain injury research data.

PHN, postherpetic neuralgia; CI, confidence interval; HR, hazard ratio; CCI, Charlson comorbidity index; HZ, herpes zoster; TBI, traumatic brain injury; HRs with a 95% CI and their P values were calculated using a Cox proportional-hazards regression model.Incidence and hazard ratios for postherpetic neuralgia during the follow-up period for herpes zoster patients with traumatic brain injury (TBI) versus without TBI with a Charlson comorbidity index = 0 or ≥ 1.

Platform for preclinical Traumatic Brain Injury model literature metadata. Model catalog to enhance reproducibility of preclinical TBI research by increasing ability to find and access preclinical TBI model papers.

This dataset include individual locations of the Independent Living Section of the Department of Rehabilitation (DOR). Independent Living Centers (ILC) and Traumatic Brain Injury (TBI) locations are dedicated to the ideal that communities become fully accessible and integrated so that all persons with disabilities can live, work, shop, and play where they choose, without barriers. This data is public information and also shared on the DOR website.

Overall rates of TBI climbed slowly from 2001 through 2007, then spiked sharply in 2008 and continued to climb through 2010. The increase in TBI rates in 2008 was much sharper for men (nearly 40% increase) than for women (20% increase). In 2007, overall rates of TBI were 26% higher in men compared to women. In 2008, that gap began to widen, reaching 61% in 2009 before narrowing to 29% in 2010. Rates of overall TBI are largely driven by rates of TBI-related ED visits.

This information is designed to provide service members, their families, veterans, the general public, and other concerned citizens with the most comprehensive and accurate figures available regarding diagnosed cases of TBI within the U.S. military. Information is collected from electronic medical records and analyzed by the Defense and Veterans Brain Injury Center in cooperation with the Armed Forces Health Surveillance Center. Numbers for the current year will be updated on a quarterly basis. Other data will be updated annually. At this time, the MHS is unable to provide information regarding cause of injury or location because that information is not available in most medical records. The numbers represent actual medical diagnoses of TBI within the U.S. Military. Other, larger numbers routinely reported in the media must be considered inaccurate because they do not reflect actual medical diagnoses. Many of these larger numbers are developed utilizing sources such as the Post Deployment Health Assessment (PDHA) or Post Deployment Health Reassessment (PDHRA). However, these documents are assessment tools with TBI screening questions and are not diagnostic tools.