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ObjectiveDescribe 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).DesignDescriptive case series using cross-sectional data.MethodsVeterans 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.ResultsFive 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.ConclusionsICD 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.

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.

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.

Traumatic brain injury (TBI) is common among military personnel and the civilian population and is often followed by a heterogeneous array of clinical, cognitive, behavioral, mood, and neuroimaging changes. Unlike many neurological disorders that have a characteristic abnormal central neurologic area(s) of abnormality pathognomonic to the disorder, a sufficient head impact may cause focal, multifocal, diffuse or combination of injury to the brain. This inconsistent presentation makes it difficult to establish or validate biological and imaging markers that could help improve diagnostic and prognostic accuracy in this patient population. The purpose of this manuscript is to describe both the challenges and opportunities when conducting military-relevant TBI research and introduce the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Military Brain Injury working group. ENIGMA is a worldwide consortium focused on improving replicability and analytical power through data sharing and collaboration. In this paper, we discuss challenges affecting efforts to aggregate data in this patient group. In addition, we highlight how "big data" approaches might be used to understand better the role that each of these variables might play in the imaging and functional phenotypes of TBI in Service member and Veteran populations, and how data may be used to examine important military specific issues such as return to duty, the late effects of combat-related injury, and alteration of the natural aging processes.

Objective: 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. Methods: 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). Results: 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. Significance: 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]

Introduction: Frontotemporal dementia (FTD) encompasses a clinically and pathologically diverse group of neurodegenerative disorders, yet little work has quantified the unique phenotypic clinical presentations of FTD among post-9/11 era veterans. To identify phenotypes of FTD using natural language processing (NLP) aided medical chart reviews of post-9/11 era U.S. military Veterans diagnosed with FTD in Veterans Health Administration care. Methods: A medical record chart review of clinician/provider notes was conducted using a Natural Language Processing (NLP) tool, which extracted features related to cognitive dysfunction. NLP features were further organized into seven Research Domain Criteria Initiative (RDoC) domains, which were clustered to identify distinct phenotypes. Results: Veterans with FTD were more likely to have notes that reflected the RDoC domains, with cognitive and positive valence domains showing the greatest difference across groups. Clustering of domains identified three symptom phenotypes agnostic to time of an individual having FTD, categorized as Low (16.4%), Moderate (69.2%), and High (14.5%) distress. Comparison across distress groups showed significant differences in physical and psychological characteristics, particularly prior history of head injury, insomnia, cardiac issues, anxiety, and alcohol misuse. The clustering result within the FTD group demonstrated a phenotype variant that exhibited a combination of language and behavioral symptoms. This phenotype presented with manifestations indicative of both language-related impairments and behavioral changes, showcasing the coexistence of features from both domains within the same individual. Discussion: This study suggests FTD also presents across a continuum of severity and symptom distress, both within and across variants. The intensity of distress evident in clinical notes tends to cluster with more co-occurring conditions. This examination of phenotypic heterogeneity in clinical notes indicates that sensitivity to FTD diagnosis may be correlated to overall symptom distress, and future work incorporating NLP and phenotyping may help promote strategies for early detection of FTD. [ABSTRACT FROM AUTHOR]

Background: Studies have demonstrated that individuals diagnosed with traumatic brain injury (TBI) frequently use medical and recreational cannabis to treat persistent symptoms of TBI, such as chronic pain and sleep disturbances, which can lead to cannabis use disorder (CUD). We aimed to determine the Veterans Health Administration (VHA) healthcare utilization and costs associated with CUD and dementia diagnosis in veterans with TBI. Methods: This observational study used administrative datasets from the population of post-9/11 veterans from the Long-term Impact of Military-Relevant Brain Injury Consortium-Chronic Effects of Neurotrauma Consortium and the VA Data Warehouse. We compared the differential VHA costs among the following cohorts of veterans: (1) No dementia diagnosis and No CUD group, (2) Dementia diagnosis only (Dementia only), (3) CUD only, and (4) comorbid dementia diagnosis and CUD (Dementia and CUD). Generalized estimating equations and negative binomial regression models were used to estimate total annual costs (inflation-adjusted) and the incidence rate of healthcare utilization, respectively, by dementia diagnosis and CUD status. Results: Data from 387,770 veterans with TBI (88.4% men; median [interquartile range (IQR)] age at the time of TBI: 30 [14] years; 63.5% white) were followed from 2000 to 2020. Overall, we observed a trend of gradually increasing healthcare costs 5 years after TBI onset. Interestingly, in this cohort of veterans within 5 years of TBI, we observed substantial healthcare costs in the Dementia only group (peak = $46,808) that were not observed in the CUD and dementia group. Relative to those without either condition, the annual total VHA costs were $3,368 higher in the CUD only group, while no significant differences were observed in the Dementia only and Dementia and CUD groups. Discussion: The findings suggest that those in the Dementia only group might be getting their healthcare needs met more quickly and within 5 years of TBI diagnosis, whereas veterans in the Dementia and CUD group are not receiving early care, resulting in higher long-term healthcare costs. Further investigations should examine what impact the timing of dementia and CUD diagnoses have on specific categories of inpatient and outpatient care in VA and community care facilities. [ABSTRACT FROM AUTHOR]

Background: Headache (HA) is a common persistent complaint following mild traumatic brain injury (mTBI), but the association with remote mTBI is not well established, and risk factors are understudied. Objective: Determine the relationship of mTBI history and other factors with HA prevalence and impact among combat-exposed current and former service members (SMs). Design: Secondary cross-sectional data analysis from the Long-Term Impact of Military-Relevant Brain Injury Consortium—Chronic Effects of Neurotrauma Consortium prospective longitudinal study. Methods: We examined the association of lifetime mTBI history, demographic, military, medical and psychosocial factors with (1) HA prevalence (“lately, have you experienced headaches?”) using logistic regression and (2) HA burden via the Headache Impact Test-6 (HIT-6) using linear regression. Each lifetime mTBI was categorized by mechanism (blast-related or not) and setting (combat deployed or not). Participants with non-credible symptom reporting were excluded, leaving N = 1,685 of whom 81% had positive mTBI histories. Results: At a median 10 years since last mTBI, mTBI positive participants had higher HA prevalence (69% overall, 78% if 3 or more mTBIs) and greater HA burden (67% substantial/severe impact) than non-TBI controls (46% prevalence, 54% substantial/severe impact). In covariate-adjusted analysis, HA prevalence was higher with greater number of blast-related mTBIs (OR 1.81; 95% CI 1.48, 2.23), non-blast mTBIs while deployed (OR 1.42; 95% CI 1.14, 1.79), or non-blast mTBIs when not deployed (OR 1.23; 95% CI 1.02, 1.49). HA impact was only higher with blast-related mTBIs. Female identity, younger age, PTSD symptoms, and subjective sleep quality showed effects in both prevalence and impact models, with the largest mean HIT-6 elevation for PTSD symptoms. Additionally, combat deployment duration and depression symptoms were factors for HA prevalence, and Black race and Hispanic/Latino ethnicity were factors for HA impact. In sensitivity analyses, time since last mTBI and early HA onset were both nonsignificant. Conclusion: The prevalence of HA symptoms among formerly combat-deployed veterans and SMs is higher with more lifetime mTBIs regardless of how remote. Blast-related mTBI raises the risk the most and is uniquely associated with elevated HA burden. Other demographic and potentially modifiable risk factors were identified that may inform clinical care. [ABSTRACT FROM AUTHOR]

Background: Veterans with posttraumatic epilepsy (PTE), particularly those with comorbidities associated with epilepsy or traumatic brain injury (TBI), have poorer health status and higher symptom burden than their peers without PTE. One area that has been particularly poorly studied is that of the role of caregivers in the health of veterans with PTE and the impact caring for someone with PTE has on the caregivers themselves. Objective: In this study, we aim to address the following: describe and compare the health and quality of life of veterans and caregivers of veterans with and without PTE; evaluate the change in available supports and unmet needs for services among caregivers of post-9/11 veterans with PTE over a 2-year period and to compare support and unmet needs with those without PTE; and identify veteran and caregiver characteristics associated with the 2-year health trajectories of caregivers and veterans with PTE compared with veterans without PTE. Methods: We conducted a prospective cohort study of the health and quality of life among 4 groups of veterans and their caregivers: veterans with PTE, nontraumatic epilepsy, TBI only, and neither epilepsy nor TBI. We will recruit participants from previous related studies and collect information about both the veterans and their primary informal caregivers on health, quality of life, unmet needs for care, PTE and TBI symptoms and treatment, relationship, and caregiver experience. Data sources will include existing data supplemented with primary data, such as survey data collected at baseline, intermittent brief reporting using ecological momentary assessment, and qualitative interviews. We will make both cross-sectional and longitudinal comparisons, using veteran-caregiver dyads, along with qualitative findings to better understand risk and promotive factors for quality of life and health among veterans and caregivers, as well as the bidirectional impact of caregivers and care recipients on one another. Results: This study was approved by the institutional review boards of the University of Utah and Salt Lake City Veterans Affairs and is under review by the Human Research Protection Office of the United States Army Medical Research and Development Command. The Service Member, Veteran, and Caregiver Community Stakeholders Group has been formed and the study questionnaire will be finalized once the panel reviews it. We anticipate the start of recruitment and primary data collection by January 2022. Conclusions: New national initiatives aim to incorporate the caregiver into the veteran's treatment plan; however, we know little about the impact of caregiving--both positive and negative--on the caregivers themselves and on the veterans for whom they provide care. We will identify specific needs in this understudied population, which will inform clinicians, patients, families, and policy makers about the specific impact and needs to equip caregivers in caring for veterans at home. [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]

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]

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]

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]