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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]

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]

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]

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]

AbstractObjectiveMethodResultsDemonstrate how patient-level traumatic brain injury (TBI) data from studies in the Federal Interagency Traumatic Brain Injury Research (FITBIR) Informatics System can be harmonized and pooled to examine relationships between TBI and cognitive functioning.We harmonized and pooled data across studies and analyzed rates of probable cognitive functioning deficits by TBI history and severity.Four publicly available FITBIR studies with 3,445 participants included data on cognitive dysfunction, though only one included comparison groups (mild TBI vs. no history of TBI) and could be used in the final comparative analyses. Of the 1,539 participants, 82% had a history of mild TBI and 67% had data suggesting the presence of cognitive dysfunction. Participants with a history of mild TBI were mostly male (87%), 25–39 years old (53%), and Non-Hispanic White (60%). Conclusions: One publicly available FITBIR study reported cognitive dysfunction data as of January 2021, though findings were similar to prior research and supported an association between mild TBI and cognitive dysfunction. This proof-of-concept study shared newly developed methods including harmonization, analysis syntax, and meta-data via the FITBIR website to encourage dissemination of these TBI data resources in line with FAIR data goals. [ABSTRACT FROM AUTHOR]