Mechanisms of change in posttraumatic headache-related disability: A mediation model.

OBJECTIVE: To explore whether the association between change in headache management self-efficacy and posttraumatic headache-related disability is partially mediated by a change in anxiety symptom severity. BACKGROUND: Many cognitive-behavioral therapy treatments for headache emphasize stress management, which includes anxiety management strategies; however, little is currently known about mechanisms of change in posttraumatic headache-related disability. Increasing our understanding of mechanisms could lead to improvements in treatments for these debilitating headaches. METHODS: This study is a secondary analysis of veterans (N = 193) recruited to participate in a randomized clinical trial of cognitive-behavioral therapy, cognitive processing therapy, or treatment as usual for persistent posttraumatic headache. The direct relationship between headache management self-efficacy and headache-related disability, along with partial mediation through change in anxiety symptoms was tested. RESULTS: The mediated latent change direct, mediated, and total pathways were statistically significant. The path analysis supported a significant direct pathway between headache management self-efficacy and headache-related disability (b = -0.45, p < 0.001; 95% confidence interval [CI: -0.58, -0.33]). The total effect of change of headache management self-efficacy scores on change in Headache Impact Test-6 scores was significant with a moderate-to-strong effect (b = -0.57, p = 0.001; 95% CI [-0.73, -0.41]). There was also an indirect effect through anxiety symptom severity change (b = -0.12, p = 0.003; 95% CI [-0.20, -0.04]). CONCLUSIONS: In this study, most of the improvements in headache-related disability were related to increased headache management self-efficacy with mediation occurring through change in anxiety. This indicates that headache management self-efficacy is a likely mechanism of change of posttraumatic headache-related disability with decreases in anxiety explaining part of the improvement in headache-related disability.

Cognitive Behavioral Therapy for Veterans With Comorbid Posttraumatic Headache and Posttraumatic Stress Disorder Symptoms: A Randomized Clinical Trial.

Importance: Posttraumatic headache is the most disabling complication of mild traumatic brain injury. Posttraumatic stress disorder (PTSD) symptoms are often comorbid with posttraumatic headache, and there are no established treatments for this comorbidity. Objective: To compare cognitive behavioral therapies (CBTs) for headache and PTSD with treatment per usual (TPU) for posttraumatic headache attributable to mild traumatic brain injury. Design, Setting, and Participants: This was a single-site, 3-parallel group, randomized clinical trial with outcomes at posttreatment, 3-month follow-up, and 6-month follow-up. Participants were enrolled from May 1, 2015, through May 30, 2019; data collection ended on October 10, 2019. Post-9/11 US combat veterans from multiple trauma centers were included in the study. Veterans had comorbid posttraumatic headache and PTSD symptoms. Data were analyzed from January 20, 2020, to February 2, 2022. Interventions: Patients were randomly assigned to 8 sessions of CBT for headache, 12 sessions of cognitive processing therapy for PTSD, or treatment per usual for headache. Main Outcomes and Measures: Co-primary outcomes were headache-related disability on the 6-Item Headache Impact Test (HIT-6) and PTSD symptom severity on the PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition) (PCL-5) assessed from treatment completion to 6 months posttreatment. Results: A total of 193 post-9/11 combat veterans (mean [SD] age, 39.7 [8.4] years; 167 male veterans [87%]) were included in the study and reported severe baseline headache-related disability (mean [SD] HIT-6 score, 65.8 [5.6] points) and severe PTSD symptoms (mean [SD] PCL-5 score, 48.4 [14.2] points). For the HIT-6, compared with usual care, patients receiving CBT for headache reported -3.4 (95% CI, -5.4 to -1.4; P < .01) points lower, and patients receiving cognitive processing therapy reported -1.4 (95% CI, -3.7 to 0.8; P = .21) points lower across aggregated posttreatment measurements. For the PCL-5, compared with usual care, patients receiving CBT for headache reported -6.5 (95% CI, -12.7 to -0.3; P = .04) points lower, and patients receiving cognitive processing therapy reported -8.9 (95% CI, -15.9 to -1.9; P = .01) points lower across aggregated posttreatment measurements. Adverse events were minimal and similar across treatment groups. Conclusions and Relevance: This randomized clinical trial demonstrated that CBT for headache was efficacious for disability associated with posttraumatic headache in veterans and provided clinically significant improvement in PTSD symptom severity. Cognitive processing therapy was efficacious for PTSD symptoms but not for headache disability. Trial Registration: ClinicalTrials.gov Identifier: NCT02419131.

Complex pain phenotypes: Suicidal ideation and attempt through latent multimorbidity.

BACKGROUND: Given the relatively high rates of suicidal ideation and attempt among people with chronic pain, there is a need to understand the underlying factors to target suicide prevention efforts. To date, no study has examined the association between pain phenotypes and suicide related behaviors among those with mild traumatic brain injuries. OBJECTIVE: To determine if pain phenotypes were independently associated with suicidal ideation / attempt or if comorbidities within the pain phenotypes account for the association between pain phenotypes and suicide related behaviors. METHODS: This is a longitudinal retrospective cohort study of suicide ideation/attempts among pain phenotypes previously derived using general mixture latent variable models of the joint distribution of repeated measures of pain scores and pain medications/treatment. We used national VA inpatient, outpatient, and pharmacy data files for Post-9/11 Veterans with mild traumatic injury who entered VA care between fiscal years (FY) 2007 and 2009. We considered a counterfactual causal modeling framework to assess the extent that the pain phenotypes during years 1-5 of VA care were predictive of suicide ideation/attempt during years 6-8 of VA care conditioned on covariates being balanced between pain phenotypes. RESULTS: Without adjustment, pain phenotypes were significant predictors of suicide related behaviors. When we used propensity scores to balance the comorbidities present in the pain phenotypes, the pain phenotypes were no longer significantly associated with suicide related behaviors. CONCLUSION: These findings suggest that suicide ideation/attempt is associated with pain trajectories primarily through latent multimorbidity. Therefore, it is critical to identify and manage comorbidities (e.g., depression, post-traumatic stress disorder) to prevent tragic outcomes associated with suicide related behaviors throughout the course of chronic pain and mild traumatic brain injury management.

PTSD symptoms and tinnitus severity: An analysis of veterans with posttraumatic headaches.

OBJECTIVE: Tinnitus and posttraumatic stress disorder (PTSD) are among the top service-connected disabilities within the Veterans Health Administration. Extant research shows that there is considerable overlap between tinnitus-related distress and PTSD, including sleep difficulty, irritability, hyperarousal, and concentration problems. However, no studies have prospectively examined the relationship between the two disorders. The purpose of this study was to examine that relationship. METHOD: Participants (N = 112) with posttraumatic headache completed measures of tinnitus and PTSD. Correlational analyses and analyses of variance were conducted to examine the associations with PTSD symptom clusters and factors of tinnitus-related distress. RESULTS: Approximately, half of participants with tinnitus demonstrated severe impairment. Correlational analyses indicated that reexperiencing, avoidance, negative emotions and cognitions, and hyperarousal PTSD symptoms were significantly related to many factors of tinnitus-related distress, including intrusiveness of tinnitus, perceived loudness, awareness, and annoyance. Participants with severe tinnitus demonstrated significantly greater reexperiencing, negative mood/cognitions, hyperarousal, and PTSD total severity compared to those with mild or moderate tinnitus. CONCLUSIONS: Trauma therapists should assess for the presence of tinnitus in order to more fully conceptualize key health problems of help-seeking patients. Heightened psychological symptoms seemingly related to PTSD may be a function of tinnitus-related distress. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Persistent posttraumatic headaches and functioning in veterans: Injury type can matter.

OBJECTIVE: To characterize the relationship between head trauma types (blast injury, blunt injury, combined blast+blunt injury) with subsequent headache presentations and functioning. BACKGROUND: Posttraumatic headaches (PTHs), the most common sequelae of traumatic brain injury (TBI), are painful and disabling. More than 400,000 veterans report having experienced a TBI, and understanding the predictors of PTHs may guide treatment developments. METHODS: This study used a nested-cohort design analyzing baseline data from a randomized clinical trial of cognitive behavioral therapy for PTH (N = 190). Participants had PTH (from blast and/or blunt head trauma) and symptoms of posttraumatic stress disorder (PTSD). The Structured Diagnostic Interview for Headache-Revised and Ohio State University Traumatic Brain Injury Identification Method were used to phenotype headaches and head injury histories, respectively. RESULTS: Individuals with persistent PTHs after a combined blast and blunt head trauma were more likely (OR =3.45; 95% CI [1.41, 8.4]) to experience chronic (vs. episodic) PTHs compared with the blunt trauma only group (23/33, 70% vs. 26/65, 40%, respectively); and they were more likely (OR =2.51; 95% CI [1.07, 5.9]) to experience chronic PTH compared with the blast trauma only group (44/92, 48%). There were no differences between head injury type on headache-related disability, depression symptoms, or severity of PTSD symptoms. CONCLUSION: The combination of blast and blunt injuries was associated with headache chronicity, but not headache disability. Considering the refractory nature of chronic headaches, the potential added and synergistic effects of distinct head injuries warrant further study.

The Military Injuries: Understanding Post-Traumatic Epilepsy Study: Understanding Relationships among Lifetime Traumatic Brain Injury History, Epilepsy, and Quality of Life.

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.

Study design for a randomized clinical trial of cognitive-behavioral therapy for posttraumatic headache.

Posttraumatic headache (PTH) is a common debilitating condition arising from head injury and is highly prevalent among military service members and veterans with traumatic brain injury (TBI). Diagnosis and treatment for PTH is still evolving, and surprisingly little is known about the putative mechanisms that drive these headaches. This manuscript describes the design of a randomized clinical trial of two nonpharmacological (i.e., behavioral) interventions for posttraumatic headache. Design of this trial required careful consideration of PTH diagnosis and inclusion criteria, which was challenging due to the lack of standard clinical characteristics in PTH unique from other types of headaches. The treatments under study differed in clinical focus and dose (i.e., number of treatment sessions), but the trial was designed to balance the treatments as well as possible. Finally, while the primary endpoints for pain research can vary from assessments of pain intensity to objective and subjective functional measures, this trial of PTH interventions chose carefully to establish clinically relevant endpoints and to maximize the opportunity to detect significant differences between groups with two primary outcomes. All these issues are discussed in this manuscript.

A Functional Model for Structure Learning and Parameter Estimation in Continuous Time Bayesian Network: An Application in Identifying Patterns of Multiple Chronic Conditions.

Bayesian networks are powerful statistical models to study the probabilistic relationships among sets of random variables with significant applications in disease modeling and prediction. Here, we propose a continuous time Bayesian network with conditional dependencies represented as regularized Poisson regressions to model the impact of exogenous variables on the conditional intensities of the network. We also propose an adaptive group regularization method with an intuitive early stopping feature based on Gaussian mixture model clustering for efficient learning of the structure and parameters of the proposed network. Using a dataset of patients with multiple chronic conditions extracted from electronic health records of the Department of Veterans Affairs, we compare the performance of the proposed network with some of the existing methods in the literature for both short-term (one-year ahead) and long-term (multi-year ahead) predictions. The proposed model provides a sparse intuitive representation of the complex functional relationships between multiple chronic conditions. It also provides the capability of analyzing multiple disease trajectories over time, given any combination of preexisting conditions.

Five-year Pain Intensity and Treatment Trajectories of Post-9/11 Veterans With Mild Traumatic Brain Injury.

Pain is a pervasive problem that affects nearly half of the U.S. Veterans deployed in support of the Global War on Terror (Post-9/11 Veterans) and over half of the Post-9/11 Veterans with diagnosed traumatic brain injury (TBI). The goal of the current study was to identify pain phenotypes based on distinct longitudinal patterns of pain scores in light of pain treatment among Post-9/11 Veterans over 5 years of care using latent growth mixture analysis stratified by TBI status. Five pain phenotypes emerged: 1) simple low impact stable pain, 2) complex low impact stable pain, 3) complex low impact worsening pain, 4) complex moderate impact worsening pain, and 5) complex high impact stable pain. Baseline pain scores and slopes were significantly higher in Veterans with mild TBI for some phenotypes. The mild TBI cohort was younger, had more men, more whites, less blacks, less education, more unmarried, more Marines and Army, more active duty in comparison to the no TBI cohort. Distinct trajectories in pain treatment were apparent among the pain intensity subgroups. PERSPECTIVE: The complexity of pain in patients with mTBI is categorically different than those with no TBI. Pain in patients with mTBI is heterogeneous with distinct phenotypes which may explain poor outcomes in this group. Identification of the individual differences may have a significant impact on the success of interventions.

Deployment, suicide, and overdose among comorbidity phenotypes following mild traumatic brain injury: A retrospective cohort study from the Chronic Effects of Neurotrauma Consortium.

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; Moderately Healthy and Mental Health phenotypes were common to both. The Healthy phenotype was found only in no brain injury. Unique phenotypes in mild traumatic brain injury included Moderately Healthy+Decline, Polytrauma, and Polytrauma+Improvement. There was substantial variation in adverse outcomes. The Polytrauma+Improvement phenotype had the lowest likelihood of adverse outcomes. There were no differences between Moderately Healthy+Decline and Polytrauma 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 Polytrauma vs. Polytrauma+Improvement and Moderately Healthy vs. Moderately Healthy+Decline, 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.

Long-term physical and mental health outcomes associated with traumatic brain injury severity in post-9/11 veterans: A retrospective cohort study.

OBJECTIVES: To examine long-term outcomes of self-reported physical and mental health among Post-9/11 Veterans stratified by traumatic brain injury (TBI) severity, we hypothesized that more severe TBI would be associated with significantly poorer outcomes. METHODS: A prospective longitudinal survey of physical and mental health status was conducted with a national cohort of Post-9/11 Veterans. We then used generalized linear models (GLM) to assess the unique contribution of TBI severity on long-term outcomes after controlling for socio-demographic characteristics, comorbidity phenotypes, and deployment experiences. RESULTS: TBI of any severity was associated with significantly poorer outcomes relative to the No TBI group. However, the manifestation of these outcomes identified in our study differed meaningfully by TBI severity level. CONCLUSIONS: Veterans with any TBI exposure experience poorer long-term outcomes than those with no TBI even when covariates are considered. In particular, measures of somatization, PTSD symptom distress, and depression indicate pervasive and long-term health concerns among individuals with TBI. Additional research is required to fully explicate what appear to be complex relationships among TBI severity, physical and mental well-being, combat exposures, and socioeconomic resources in this population.

Structural Analysis of Variability and Interaction of the N-terminal of the Oncogenic Effector CagA of Helicobacter pylori with Phosphatidylserine.

Helicobacter pylori cytotoxin-associated gene A protein (CagA) has been associated with the increase in virulence and risk of cancer. It has been demonstrated that CagA's translocation is dependent on its interaction with phosphatidylserine. We evaluated the variability of the N-terminal CagA in 127 sequences reported in NCBI, by referring to molecular interaction forces with the phosphatidylserine and the docking of three mutations chosen from variations in specific positions. The major sites of conservation of the residues involved in CagA⁻Phosphatidylserine interaction were 617, 621 and 626 which had no amino acid variation. Position 636 had the lowest conservation score; mutations in this position were evaluated to observe the differences in intermolecular forces for the CagA⁻Phosphatidylserine complex. We evaluated the docking of three mutations: K636A, K636R and K636N. The crystal and mutation models presented a ΔG of -8.919907, -8.665261, -8.701923, -8.515097 Kcal/mol, respectively, while mutations K636A, K636R, K636N and the crystal structure presented 0, 3, 4 and 1 H-bonds, respectively. Likewise, the bulk effect of the ΔG and amount of H-bonds was estimated in all of the docking models. The type of mutation affected both the ΔG ( χ 2 ( 1 ) = 93.82 , p-value < 2.2 × 10 - 16 ) and the H-bonds ( χ 2 ( 1 ) = 91.93 , p-value < 2.2 × 10 - 16 ). Overall, 76.9% of the strains that exhibit the K636N mutation produced a severe pathology. The average H-bond count diminished when comparing the mutations with the crystal structure of all the docking models, which means that other molecular forces are involved in the CagA⁻Phosphatidylserine complex interaction.

Mining patterns of comorbidity evolution in patients with multiple chronic conditions using unsupervised multi-level temporal Bayesian network.

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.

ENIGMA MILITARY BRAIN INJURY: A COORDINATED META-ANALYSIS OF DIFFUSION MRI FROM MULTIPLE COHORTS.

Traumatic brain injury (TBI) is a significant cause of morbidity in military Veterans and Service Members. While most individuals recover fully from mild injuries within weeks, some continue to experience symptoms including headaches, disrupted sleep, and other cognitive, behavioral or physical symptoms. Diffusion magnetic resonance imaging (dMRI) shows promise in identifying areas of structural disruption and predicting outcomes. Although some studies suggest widespread structural disruption after brain injury, dMRI studies of military brain injury have yielded mixed results so far, perhaps due to the subtlety of mild injury, individual differences in injury location, severity and mechanism, and comorbidity with other disorders such as post-traumatic stress disorder (PTSD), depression, and substance abuse. We present preliminary dMRI results from the ENIGMA (Enhancing Neuroimaging Genetics through Meta-Analysis) military brain injury working group. We found higher fractional anisotropy (FA) in participants with a history of TBI. Understanding the injury and recovery process, along with factors that influence these, will lead to improved diagnosis and treatment.

Acquired Stuttering in Veterans of the Wars in Iraq and Afghanistan: The Role of Traumatic Brain Injury, Post-Traumatic Stress Disorder, and Medications.

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.

Evaluation of Helicobacter pylori Infection and Clarithromycin Resistance in Strains From Symptomatic Colombian Children.

The aim of the study was to determine the current prevalence of Helicobacter pylori in symptomatic Colombian children and evaluate the presence of mutations associated with clarithromycin resistance. Biopsies from 133 children were analyzed. The gastric fragment was used for urease test and reused for polymerase chain reaction sequencing of the 23SrDNA gene. Mutations were detected by bioinformatic analysis. Polymerase chain reaction sequencing established that H pylori infection was present in 47% of patients. Bioinformatics analysis of the 62 positive sequences for 23SrDNA revealed that 92% exhibited a genotype susceptible to clarithromycin, whereas the remaining strains (8%) showed mutations associated with clarithromycin resistance. The low rate of resistance to clarithromycin (8%) suggests that conventional treatment methods are an appropriate choice for children. Recycling a biopsy that is normally discarded reduces the risks associated with the procedure. The 23SrDNA gene amplification could be used for a dual purpose: detection of H pylori and determination of susceptibility to clarithromycin.

Patterns of zolpidem use among Iraq and Afghanistan veterans: A retrospective cohort analysis.

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.

Traumatic Brain Injury Severity, Comorbidity, Social Support, Family Functioning, and Community Reintegration Among Veterans of the Afghanistan and Iraq Wars.

OBJECTIVE: To examine the association between traumatic brain injury (TBI) severity; social, family, and community reintegration outcomes; and return to work status among post-9/11 veterans in Department of Veterans Affairs (VA) care. DESIGN: Retrospective observational cohort study. SETTING: Mail/online survey fielded to a national sample of veterans. PARTICIPANTS: Sample of post-9/11 veterans with at least 3 years of VA care stratified according to TBI severity and comorbidities who completed and returned surveys (N=2023). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Deployment Risk and Resilience Inventory-2 family functioning and social support subscales; Military to Civilian Questionnaire; and employment status. RESULTS: Bivariate analyses revealed that veterans with every classification of TBI severity reported significantly more difficulty on social, family, and community reintegration outcomes than those with no TBI. In the fully adjusted model, veterans with unclassified and moderate/severe TBI reported significantly more difficulty with community reintegration and were less likely to be employed relative to those with no TBI; those with unclassified TBI also reported significantly more difficulty with family functioning. Veterans with mild TBI also reported significantly more difficulty with community reintegration. CONCLUSIONS: This study provides insight into long-term outcomes associated with TBI in post-9/11 veterans and suggests that exposure to TBI has a negative effect on social and family functioning, community reintegration, and return to work even after controlling for comorbidity, deployment experiences, and sociodemographic characteristics. Additional research is required to explicate what appears to be complex interactions among TBI severity, psychosocial well-being, combat exposures, and socioeconomic resources in this population.

Mining Major Transitions of Chronic Conditions in Patients with Multiple Chronic Conditions.

OBJECTIVES: Evolution of multiple chronic conditions (MCC) follows a complex stochastic process, influenced by several factors including the inter-relationship of existing conditions, and patient-level risk factors. Nearly 20% of citizens aged 18 years and older are burdened with two or more (multiple) chronic conditions (MCC). Treatment for people living with MCC currently accounts for an estimated 66% of the Nation's healthcare costs. However, it is still not known precisely how MCC emerge and accumulate among individuals or in the general population. This study investigates major patterns of MCC transitions in a diverse population of patients and identifies the risk factors affecting the transition process. METHODS: A Latent regression Markov clustering (LRMCL) algorithm is proposed to identify major transitions of four MCC that include hypertension (HTN), depression, Post- Traumatic Stress Disorder (PTSD), and back pain. A cohort of 601,805 individuals randomly selected from the population of Iraq and Afghanistan war Veterans (IAVs) who received VA care during three or more years between 2002-2015, is used for training the proposed LRMCL algorithm. RESULTS: Two major clusters of MCC transition patterns with 78% and 22% probability of membership respectively were identified. The primary cluster demonstrated the possibility of improvement when the number of MCC is small and an increase in probability of MCC accumulation as the number of co- morbidities increased. The second cluster showed stability (no change) of MCC overtime as the major pattern. Age was the most significant risk factor associated with the most probable cluster for each IAV. CONCLUSIONS: These findings suggest that our proposed LRMCL algorithm can be used to describe and understand MCC transitions, which may ultimately allow healthcare systems to support optimal clinical decision- making. This method will be used to describe a broader range of MCC transitions in this and non-VA populations, and will add treatment information to see if models including treatments and MCC emergence can be used to support clinical decision-making in patient care.