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It is widely appreciated that the spectrum of traumatic brain injury (TBI), mild through severe, contains distinct clinical presentations, variably referred to as subtypes, phenotypes, and/or clinical profiles. As part of the Brain Trauma Blueprint TBI State of the Science, we review the current literature on TBI phenotyping with an emphasis on unsupervised methodological approaches, and describe five phenotypes that appear similar across reports. However, we also find the literature contains divergent analysis strategies, inclusion criteria, findings, and use of terms. Further, whereas some studies delineate phenotypes within a specific severity of TBI, others derive phenotypes across the full spectrum of severity. Together, these facts confound direct synthesis of the findings. To overcome this, we introduce PhenoBench, a freely available code repository for the standardization and evaluation of raw phenotyping data. With this review and toolset, we provide a pathway toward robust, data-driven phenotypes that can capture the heterogeneity of TBI, enabling reproducible insights and targeted care. [ABSTRACT FROM AUTHOR]

Although many patients diagnosed with traumatic brain injury (TBI), particularly mild TBI, recover from their symptoms within a few weeks, a small but meaningful subset experience symptoms that persist for months or years after injury and significantly impact quality of life for the person and their family. Factors associated with an increased likelihood of negative TBI outcomes include not only characteristics of the injury and injury mechanism, but also the person's age, pre-injury status, comorbid conditions, environment, and propensity for resilience. In this article, as part of the Brain Trauma Blueprint: TBI State of the Science framework, we examine the epidemiology of long-term outcomes of TBI, including incidence, prevalence, and risk factors. We identify the need for increased longitudinal, global, standardized, and validated assessments on incidence, recovery, and treatments, as well as standardized assessments of the influence of genetics, race, ethnicity, sex, and environment on TBI outcomes. By identifying how epidemiological factors contribute to TBI outcomes in different groups of persons and potentially impact differential disease progression, we can guide investigators and clinicians toward more-precise patient diagnosis, along with tailored management, and improve clinical trial designs, data evaluation, and patient selection criteria. [ABSTRACT FROM AUTHOR]

Understanding risk for epilepsy among persons who sustain a mild (mTBI) traumatic brain injury (TBI) is crucial for effective intervention and prevention. However, mTBI is frequently undocumented or poorly documented in health records. Further, health records are non-continuous, such as when persons move through health systems (e.g., from Department of Defense to Veterans Affairs [VA] or between jobs in the civilian sector), making population-based assessments of this relationship challenging. Here, we introduce the MINUTE (Military INjuries—Understanding post-Traumatic Epilepsy) study, which integrates data from the Veterans Health Administration with self-report survey data for post-9/11 veterans (n = 2603) with histories of TBI, epilepsy and controls without a history of TBI or epilepsy. This article describes the MINUTE study design, implementation, hypotheses, and initial results across four groups of interest for neurotrauma: 1) control; 2) epilepsy; 3) TBI; and 4) post-traumatic epilepsy (PTE). Using combined survey and health record data, we test hypotheses examining lifetime history of TBI and the differential impacts of TBI, epilepsy, and PTE on quality of life. The MINUTE study revealed high rates of undocumented lifetime TBIs among veterans with epilepsy who had no evidence of TBI in VA medical records. Further, worse physical functioning and health-related quality of life were found for persons with epilepsy + TBI compared to those with either epilepsy or TBI alone. This effect was not fully explained by TBI severity. These insights provide valuable opportunities to optimize the resilience, delivery of health services, and community reintegration of veterans with TBI and complex comorbidity. [ABSTRACT FROM AUTHOR]

Mild traumatic brain injury in the Veteran population is frequently comorbid with pain, post-traumatic stress disorder, and/or depression. However, not everyone exposed to mild traumatic brain injury experiences these comorbidities and it is unclear what factors contribute to this variability. The objective of this study was to identify comorbidity phenotypes among Post-9/11 deployed Veterans with no or mild traumatic brain injury and examine the association of comorbidity phenotypes with adverse outcomes. We found that Veterans with mild traumatic brain injury (n = 93,003) and no brain injury (n = 434,378) were mean age of 32.0 (SD 9.21) on entering Department of Veterans Health Administration care, were predominantly Caucasian non-Hispanic (64.69%), and served in the Army (61.31%). Latent class analysis revealed five phenotypes in each subcohort; and phenotypes were common to both. The phenotype was found only in no brain injury. Unique phenotypes in mild traumatic brain injury included , , and . There was substantial variation in adverse outcomes. The phenotype had the lowest likelihood of adverse outcomes. There were no differences between and phenotypes. Phenotypes of comorbidity vary significantly by traumatic brain injury status including divergence in phenotypes (and outcomes) over time in the mild traumatic brain injury subcohort. Understanding risk factors for the divergence between vs. and vs. , will improve our ability to proactively mitigate risk, better understand the early patterns of comorbidity that are associated with neurodegenerative sequelae following mild traumatic brain injury, and plan more patient-centered care. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance Epilepsy is associated with significant mortality risk. There is limited research examining how traumatic brain injury (TBI) timing affects mortality in relation to the onset of epilepsy. We aimed to assess the temporal relationship between epilepsy and TBI regarding mortality in a cohort of post‐9/11 veterans.This retrospective cohort study included veterans who received health care in the Defense Health Agency and the Veterans Health Administration between 2000 and 2019. For those diagnosed with epilepsy, the index date was the date of first antiseizure medication or first seizure; we simulated the index date for those without epilepsy. We created the study groups by the index date and first documented TBI: (1) controls (no TBI, no epilepsy), (2) TBI only, (3) epilepsy only, (4) TBI before epilepsy, (5) TBI within 6 months after epilepsy, and (6) TBI >6 months after epilepsy. Kaplan–Meier estimates of all‐cause mortality were calculated, and log‐rank tests were used to compare unadjusted cumulative mortality rates among groups compared to controls. Cox proportional hazard models were used to compute hazard ratios (HRs) with 95% confidence intervals (CIs).Among 938 890 veterans, 27 436 (2.92%) met epilepsy criteria, and 264 890 (28.22%) had a TBI diagnosis. Mortality was higher for veterans with epilepsy than controls (6.26% vs. 1.12%; p < .01). Veterans with TBI diagnosed ≤6 months after epilepsy had the highest mortality hazard (HR = 5.02, 95% CI = 4.21–5.99) compared to controls, followed by those with TBI before epilepsy (HR = 4.25, 95% CI = 3.89–4.58), epilepsy only (HR = 4.00, 95% CI = 3.67–4.36), and TBI >6 months after epilepsy (HR = 2.49, 95% CI = 2.17–2.85). These differences were significant across groups.TBI timing relative to epilepsy affects time to mortality; TBI within 6 months after epilepsy or before epilepsy diagnosis was associated with earlier time to death compared to those with epilepsy only or TBI >6 months after epilepsy. [ABSTRACT FROM AUTHOR]

The chronic mental health consequences of mild traumatic brain injury (TBI) are a leading cause of disability. This is surprising given the expectation of significant recovery after mild TBI, which suggests that other injury-related factors may contribute to long-term adverse outcomes. The objective of this study was to determine how number of prior injuries, gender, and environment/context of injury may contribute to depressive symptoms after mild TBI among deployed United States service members and veterans (SMVs). Data from the Long-term Impact of Military-Relevant Brain Injury Consortium Prospective Longitudinal Study was used to assess TBI injury characteristics and depression scores previously measured on the Patient Health Questionnaire-9 (PHQ-9) among a sample of 1456 deployed SMVs. Clinical diagnosis of mild TBI was defined via a multi-step process centered on a structured face-to-face interview. Logistical and linear regressions stratified by gender and environment of injury were used to model depressive symptoms controlling for sociodemographic and combat deployment covariates. Relative to controls with no history of mild TBI (n = 280), the odds ratios (OR) for moderate/severe depression (PHQ-9 ≥ 10) were higher for SMVs with one mild TBI (n = 358) OR: 1.62 (95% confidence interval [CI] 1.09–2.40, p = 0.016) and two or more mild TBIs (n = 818) OR: 1.84 (95% CI 1.31–2.59, p < 0.001). Risk differences across groups were assessed in stratified linear models, which found that depression symptoms were elevated in those with a history of multiple mild TBIs compared with those who had a single mild TBI (p < 0.001). Combat deployment-related injuries were also associated with higher depression scores than injuries occurring in non-combat or civilian settings (p < 0.001). Increased rates of depression after mild TBI persisted in the absence of post-traumatic stress disorder. Both men and women SMVs separately exhibited significantly increased depressive symptom scores if they had had combat-related mild TBI. These results suggest that contextual information, gender, and prior injury history may influence long-term mental health outcomes among SMVs with mild TBI exposure. [ABSTRACT FROM AUTHOR]

For many years, experts have recognized the importance of studying traumatic brain injury (TBI) among active-duty service members and veterans. A majority of this research has been conducted in Veterans Administration (VA) or Department of Defense settings. However, far less is known about military personnel who seek their medical care outside these settings. Studies that have been conducted in civilian settings have either not enrolled active duty or veteran participants, or failed to measure military history, precluding study of TBI outcomes by military history. The purpose of the present study was to determine associations between military history and medical (prevalence of 25 comorbid health conditions), cognition (Brief Test of Adult Cognition by Telephone), and psychological health (Patient Health Questionnaire-9 [PHQ-9], Generalized Anxiety Disorder-7, suicidality [9th item from PHQ-9]) in the first 5 years after TBI. In this prospective study, we analyzed data from the TBI Model Systems National Database. Participants were 7797 individuals with TBI admitted to one of 21 civilian inpatient rehabilitation facilities from April 1, 2010, to November 19, 2020, and followed up to 5 years. We assessed the relationship between military history (any versus none, combat exposure, service era, and service duration) and TBI outcomes. We found specific medical conditions were significantly more prevalent 1 year post-TBI among individuals who had a history of combat deployment (lung disorders, post-traumatic stress disorder [PTSD], and sleep disorder), served in post-draft era (chronic pain, liver disease, arthritis), and served >4 years (high cholesterol, PTSD, sleep disorder). Individuals with military history without combat deployment had modestly more favorable cognition and psychological health in the first 5 years post-injury relative to those without military history. Our data suggest that individuals with TBI with military history are heterogeneous, with some favorable and other deleterious health outcomes, relative to their non-military counterparts, which may be driven by characteristics of service, including combat exposure and era of service. [ABSTRACT FROM AUTHOR]

To assess traumatic brain injury (TBI)-related risks factors for early-onset dementia (EOD). Younger Post-9/11 Veterans may be at elevated risk for EOD due to high rates of TBI in early/mid adulthood. Few studies have explored the longitudinal relationship between traumatic brain injury (TBI) and the emergence of EOD subtypes. This matched case-control study used data from the Veterans Health Administration (VHA) to identify Veterans with EOD. To address the low positive predictive value (PPV = 0.27) of dementia algorithms in VHA records, primary outcomes were Alzheimer's disease (AD) and frontotemporal dementia (FTD). Logistic regression identified conditions associated with dementia subtypes. The EOD cohort included Veterans with AD (n = 689) and FTD (n = 284). There were no significant demographic differences between the EOD cohort and their matched controls. After adjustment, EOD was significantly associated with history of TBI (OR: 3.05, 2.42–3.83), epilepsy (OR: 4.8, 3.3–6.97), other neurological conditions (OR: 2.0, 1.35–2.97), depression (OR: 1.35, 1.12–1.63) and cardiac disease (OR: 1.36, 1.1–1.67). Post-9/11 Veterans have higher odds of EOD following TBI. A sensitivity analysis across TBI severity confirmed this trend, indicating that the odds for both AD and FTD increased after more severe TBIs. [ABSTRACT FROM AUTHOR]

Following mild traumatic brain injury (mTBI), many individuals suffer from persistent post-concussive, depressive, post-traumatic stress, and sleep-related symptoms. Findings from self-report scales link these symptoms to biomarkers of neurodegeneration, although the underlying pathophysiology is unclear. Each linked self-report scale includes sleep items, raising the possibility that despite varied symptomology, disordered sleep may underlie these associations. To isolate sleep effects, we examined associations between post-mTBI biomarkers of neurodegeneration and symptom scales according to composite, non-sleep, and sleep components. Plasma biomarkers and self-report scales were obtained from 143 mTBI-positive warfighters. Pearson's correlations and regression models were constructed to estimate associations between total, sleep, and non-sleep scale items with biomarker levels, and with measured sleep quality. Symptom severity positively correlated with biomarker levels across scales. Biomarker associations were largely unchanged when sleep items were included, excluded, or considered in isolation. Pittsburgh Sleep Quality Index demonstrated strong correlations with sleep and non-sleep items of all scales. The congruency of associations raises the possibility of a common pathophysiological process underlying differing symptomologies. Given its role in neurodegeneration and mood dysregulation, sleep physiology seems a likely candidate. Future longitudinal studies should test this hypothesis, with a focus on identifying novel sleep-related therapeutic targets. [ABSTRACT FROM AUTHOR]

There is evidence Traumatic Brain Injury (TBI) is associated with increased risk of dementia (D). We compared VA and non-VA facility costs associated with TBI+D and each diagnosis alone, relative to neither diagnosis, annually and over time, 2000–2020. We estimated adjusted panel models of annual VHA costs in VA and non-VA facilities, stratified by age, and by TBI-dementia status. We also estimated cost for the TBI+D cohort by time since TBI and dementia diagnoses. All costs were 2021 inflation adjusted. Veterans <65 ($30,736) and ≥65 ($15,650) with TBI+D, while veterans <65 ($3,379) and ≥65 ($4,252) with TBI-only had higher annual total VHA costs, relative to neither diagnosis. Veterans with TBI+D < 65 ($42,864) and ≥65 ($72,424) had higher costs in years≥15 after TBI diagnosis, while <65 ($36,431) and ≥65 ($37,589) had higher costs in years ≥10 after dementia diagnosis. The main cost driver was inpatient non-VA facility costs. Veterans had continuously increasing inpatient care costs in non-VA facilities over time since their TBI and dementia diagnoses. Given budget constraints on the VA system, quality of care in non-VA facilities warrants comparison with VA facilities to make informed decisions regarding referrals to non-VA facilities. [ABSTRACT FROM AUTHOR]

Describe dementia cases identified through International Classification of Diseases (ICD) coding in the Long-term Impact of Military-relevant Brain Injury Consortium – Chronic Effects of Neurotrauma Consortium (LIMBIC-CENC) multicenter prospective longitudinal study (PLS) of mild traumatic brain injury (mTBI). Descriptive case series using cross-sectional data. Veterans Affairs (VA) health system data including ICD codes were obtained for 1563 PLS participants through the VA Informatics and Computing Infrastructure (VINCI). Demographic, injury, and clinical characteristics of Dementia positive and negative cases are described. Five cases of dementia were identified, all under 65 years old. The dementia cases all had a history of blast-related mTBI and all had self-reported functional problems and four had PTSD symptomatology at the clinical disorder range. Cognitive testing revealed some deficits especially in the visual memory and verbal learning and memory domains, and that two of the cases might be false positives. ICD codes for early dementia in the VA system have specificity concerns, but could be indicative of cognitive performance and self-reported cognitive function. Further research is needed to better determine links to blast exposure, blast-related mTBI, and PTSD to early dementia in the military population. [ABSTRACT FROM AUTHOR]

Traumatic brain injury (TBI) is a risk factor for later-life dementia. Clinical and pre-clinical studies have elucidated multiple mechanisms through which TBI may influence or exacerbate multiple pathological processes underlying Alzheimer's disease and Alzheimer's disease–related dementias (AD/ADRD). The National Institutes of Health hosts triennial ADRD Summits to inform a national research agenda, and the 2019 ADRD Summit was the first to highlight "TBI and AD/ADRD Risk" as an emerging topic in the field. A multidisciplinary committee of TBI researchers with relevant expertise reviewed extant literature, identified research gaps and opportunities, and proposed draft research recommendations at the 2019 ADRD Summit. These research recommendations, further refined after broad stakeholder input at the Summit, cover four overall areas: 1) Encourage crosstalk and interdisciplinary collaboration between TBI and dementia researchers; 2) Establish infrastructure to study TBI as a risk factor for AD/ADRD; 3) Promote basic and clinical research examining the development and progression of TBI AD/ADRD neuropathologies and associated clinical symptoms; and 4) Characterize the clinical phenotype of progressive dementia associated with TBI and develop non-invasive diagnostic approaches. These recommendations recognize a need to strengthen communication and build frameworks to connect the complexity of TBI with rapidly evolving AD/ADRD research. Recommendations acknowledge TBI as a clinically and pathologically heterogeneous disease whose associations with AD/ADRDs remain incompletely understood. The recommendations highlight the scientific advantage of investigating AD/ADRD in the context of a known TBI exposure, the study of which can directly inform on disease mechanisms and treatment targets for AD/ADRDs with shared common pathways. [ABSTRACT FROM AUTHOR]

Introduction: Determine the association between acquired stuttering (AS), traumatic brain injury (TBI), and post-traumatic stress disorder (PTSD) in a cohort of 309,675 U.S. Iraq and Afghanistan veterans. The secondary aim was to determine the association between AS and medication patterns for veterans in the sample.Materials and Methods: Retrospective study using data from the Veterans Health Administration National Repository for veterans deployed in support of combat operations in Iraq and Afghanistan and who received Veterans Health Administration care in 2010 and 2011. We identified stuttering using ICD-9 codes to establish the association between AS, TBI, and PTSD, controlling for demographic characteristics and other comorbidities. Multivariable logistic regression was used to determine the association between comorbid conditions and potentially problematic medications associated with stuttering.Results: Two hundred thirty-five veterans (0.08%) were diagnosed with AS in the cohort. There was the greater likelihood of an AS diagnosis for veterans with concomitant TBI and PTSD when compared with veterans without these diagnoses. Over 66% of those with stuttering were prescribed at least one medication that affected speech fluency (antidepressants, anxiolytics, and antiepileptic drugs) compared with 35% of those without AS.Conclusion: Veterans with a comorbid diagnosis of TBI and PTSD were more likely to be diagnosed with AS AOR: 9.77 (95% CI = 6.93-13.78, p < 0.05) and more likely to have been prescribed medications known to affect speech production OR: 3.68 (95% CI = 2.81-4.82, p < 0.05). Clinicians treating veterans with these complex comorbid conditions should consider the impact of medications on speech fluency. [ABSTRACT FROM AUTHOR]

Objective: To describe change in body mass index (BMI) and weight classification 1-year post- traumatic brain injury (TBI) among Veterans and service members. Design: Prospective observational cohort study. Setting: VA Polytrauma Rehabilitation Centers. Participants: Veterans and service members (N = 84) enrolled in VA Traumatic Brain Injury Model Systems (VA TBIMS) study with BMI scores at enrollment and 1-year post-injury. Interventions: N/A. Main outcome measures: BMI scores from height and weight and weight classifications (underweight, normal weight, overweight, obese classes 1-3) defined by WHO. Results: Twenty per cent were obese at time of injury and 24% were obese at 1-year post-injury. Cross-tab analyses revealed 7% of normal weight and 24% overweight participants at time of injury as obese Class 1 one-year post-injury. Univariate models found BMI and tobacco smoking at time of injury were significant predictors of higher BMI scores 1-year post-TBI. Multivariable models found BMI at time of injury and motor functioning, were significant predictors. Preinjury BMI, tobacco smoking and PTSD symptom severity predicted change in weight category. Conclusion: While obesity among service members and Veterans post-TBI is below national averages, trends in weight gain between time of injury and 1-year follow-up were observed. Implications for health promotion and chronic disease management efforts with regards to rehabilitation for injured military are discussed. List of Abbreviations: BMI, Body mass index; BRFSS, Behavioural Risk Factor Surveillance; GCS, Glasgow Coma Scale; FIM, Functional Independence Measure; NIDILRR, National Institute on Independent Living and Rehabilitation Research; PCL-C, PTSD checklist-civilian; PSTD, Post-traumatic stress disorder; VA, Veterans Affairs; VA PRC, Veterans Affairs Polytrauma Rehabilitation; VA TBIMS, Veterans Affairs TBI Model Systems; [ABSTRACT FROM AUTHOR]

Over the past few decades, the rise of multiple chronic conditions has become a major concern for clinicians. However, it is still not known precisely how multiple chronic conditions emerge among patients. We propose an unsupervised multi-level temporal Bayesian network to provide a compact representation of the relationship among emergence of multiple chronic conditions and patient level risk factors over time. To improve the efficiency of the learning process, we use an extension of maximum weight spanning tree algorithm and greedy search algorithm to study the structure of the proposed network in three stages, starting with learning the inter-relationship of comorbidities within each year, followed by learning the intra-relationship of comorbidity emergence between consecutive years, and finally learning the hierarchical relationship of comorbidities and patient level risk factors. We also use a longest path algorithm to identify the most likely sequence of comorbidities emerging from and/or leading to specific chronic conditions. Using a de-identified dataset of more than 250,000 patients receiving care from the U.S. Department of Veterans Affairs for a period of five years, we compare the performance of the proposed unsupervised Bayesian network in comparison with those of Bayesian networks developed based on supervised and semi-supervised learning approaches, as well as multivariate probit regression, multinomial logistic regression, and latent regression Markov mixture clustering focusing on traumatic brain injury (TBI), post-traumatic stress disorder (PTSD), depression (Depr), substance abuse (SuAb), and back pain (BaPa). Our findings show that the unsupervised approach has noticeably accurate predictive performance that is comparable to the best performing semi-supervised and the second-best performing supervised approaches. These findings also revealed that the unsupervised approach has improved performance over multivariate probit regression, multinomial logistic regression, and latent regression Markov mixture clustering. [ABSTRACT FROM AUTHOR]

Background: Although concern exists regarding the adverse effects and rate of zolpidem use, especially long-term use, limited information is available concerning patterns of zolpidem use. Objective: To examine the prevalence and correlates of zolpidem exposure in Iraq and Afghanistan Veterans (IAVs). Methods: A retrospective cohort study of zolpidem prescriptions was performed with National Veterans Health Administration (VHA) data. We gathered national VA inpatient, outpatient, and pharmacy data files for IAV’s who received VA care between fiscal years (FY) 2013 and 2014. The VA pharmacy database was used to identify the prevalence of long term (>30 days), high-dose zolpidem exposure (>10mg immediate-release; >12.5mg extended-release) and other medications received in FY14. Baseline characteristics (demographics, diagnoses) were identified in FY13. Bivariate and multivariable analyses were used to examine the demographic, clinical, and medication correlates of zolpidem use. Results: Of 493,683 IAVs who received VHA care in FY 2013 and 2014, 7.6% (n = 37,422) were prescribed zolpidem in FY 2014. Women had lower odds of high-dose zolpidem exposure than men. The majority (77.3%) of IAVs who received zolpidem prescriptions had long-term use with an average days’ supply of 189.3 days and a minority (0.9%) had high-dose exposure. In multivariable analyses, factors associated with long-term zolpidem exposure included age greater than 29 years old, PTSD, insomnia, Selim Index, physical 2–3 conditions, opioids, antidepressants, benzodiazepines, atypical antipsychotics, and stimulants. High dose exposure was associated with PTSD, depression, substance use disorder, insomnia, benzodiazepines, atypical antipsychotics, and stimulant prescriptions. Conclusion: The current practices of insomnia pharmacotherapy in IAVs fall short of the clinical guidelines and may reflect high-risk zolpidem prescribing practices that put Iraq and Afghanistan Veterans at risk for adverse effects of zolpidem and poor health outcomes. [ABSTRACT FROM AUTHOR]

Purpose Research suggests that there are reciprocal relationships between mental health (MH) disorders and epilepsy risk. However, MH relationships to post-traumatic epilepsy (PTE) have not been explored. Thus, the objective of this study was to assess associations between PTE and frequency of depression and/or anxiety in a cohort of individuals with moderate-to-severe TBI who received acute inpatient rehabilitation. Methods Multivariate regression models were developed using a recent (2010–2012) cohort (n = 867 unique participants) from the TBI Model Systems (TBIMS) National Database, a time frame during which self-reported seizures, depression [Patient Health Questionnaire (PHQ)-9], and anxiety [Generalized Anxiety Disorder (GAD-7)] follow-up measures were concurrently collected at year-1 and year-2 after injury. Results PTE did not significantly contribute to depression status in either the year-1 or year-2 cohort, nor did it contribute significantly to anxiety status in the year-1 cohort, after controlling for other known depression and anxiety predictors. However, those with PTE in year-2 had 3.34 times the odds (p = .002) of having clinically significant anxiety, even after accounting for other relevant predictors. In this model, participants who self-identified as Black were also more likely to report clinical symptoms of anxiety than those who identified as White. PTE was the only significant predictor of comorbid depression and anxiety at year-2 (Odds Ratio 2.71; p = 0.049). Conclusions Our data suggest that PTE is associated with MH outcomes 2 years after TBI, findings whose significance may reflect reciprocal, biological, psychological, and/or experiential factors contributing to and resulting from both PTE and MH status post-TBI. Future work should consider temporal and reciprocal relationships between PTE and MH as well as if/how treatment of each condition influences biosusceptibility to the other condition. [ABSTRACT FROM AUTHOR]

Objective: We review health services and reintegration practices that contribute to the rehabilitation of US active duty service members (ADSMs) and Veterans who experienced traumatic brain injury (TBI), especially mild TBI (mTBI), as discussed at the 2015 Department of Veterans Affairs (VA) TBI State-of-the-Art (SOTA) Conference. Methodology: We reviewed the state-of-the-art at the time of the previous 2008 TBI SOTA Conference, advances in the field since then, and future directions to address gaps in knowledge. Main results: We reviewed: (1) mTBI and its comorbid conditions documented in ADSMs and Veterans, and recognized the need for additional healthcare utilization, health cost and quality of care studies; (2) VA vocational rehabilitation programmes and the effectiveness of supported employment for helping those with workplace difficulties; (3) the application of technology to assist in TBI rehabilitation, including mobile device applications for self-management, videoconferencing with providers, and virtual reality to help with behavioural and cognitive challenges, and (4) Department of Defense (DoD)-VA partnerships on identification, evaluation and dissemination of TBI best practices. Conclusions: There have been significant advances in TBI rehabilitation, but multiple areas across the DoD and VA care continuum need further exploration and development to meet the needs of ADSMs and Veterans. [ABSTRACT FROM PUBLISHER]