Posttraumatic Stress Disorder Symptoms Contribute to Staff Perceived Irritability, Anger, and Aggression After TBI in a Longitudinal Veteran Cohort: A VA TBI Model Systems Study

Objective To examine the relationship between staff perceived irritability, anger, and aggression and posttraumatic stress disorder (PTSD) in veterans with traumatic brain injury (TBI) of all severity levels. Design Longitudinal cohort design. Setting Veterans Affairs Polytrauma Transitional Rehabilitation Programs. Participants Veterans and service members with TBI of all severity levels enrolled in the Veterans Affairs Polytrauma Rehabilitation Centers’ Traumatic Brain Injury Model System national database (N=240). Interventions Not applicable. Main Outcome Measure Univariable and multivariable logistic regression modeling was used to examine the association between irritability, anger, and aggression and potential risk factors, including PTSD symptoms. Irritability, anger, and aggression was measured as a single construct using an item from the Mayo-Portland Adaptability Inventory-4 that was rated by program staff at admission and discharge from the inpatient rehabilitation program. PTSD symptoms were assessed using the PTSD Checklist–Civilian Version. Results PTSD symptoms uniquely predicted program staff-rated irritability, anger, and aggression at discharge even after controlling for severity of TBI, age, male sex, education, and annual earnings. The model explained 19% of the variance in irritability, anger, and aggression. Conclusions When TBI severity and PTSD symptoms were considered simultaneously in a sample of veterans, only PTSD symptoms predicted staff-rated irritability, anger, and aggression. Given the negative outcomes linked with irritability, anger, and aggression, veterans may benefit from assessment and treatment of PTSD symptoms within rehabilitation settings

Demographic and Mental Health Predictors of Arrests Up to 10 Years Post-Traumatic Brain Injury: A Veterans Affairs TBI Model Systems Study

OBJECTIVE: Examine rates and predictors of arrests in Veterans and Service Members (V/SM) who received inpatient rehabilitation for traumatic brain injury (TBI). SETTING: Veterans Administration (VA) Polytrauma Rehabilitation Centers. PARTICIPANTS: A total of 948 V/SM drawn from the VA TBI Model Systems cohort with arrest data up to 10 years post-TBI. DESIGN: Longitudinal cohort study; secondary analysis of pre-TBI characteristics predicting post-TBI arrests. MAIN MEASURES: Disclosure of arrests pre-TBI and up to10 years post-TBI. RESULTS: Thirty-six percent of the sample had been arrested prior to their TBI; 7% were arrested post-TBI. When considering all variables simultaneously in a multivariate model, pre-TBI mental health treatment (adjusted odds ratio [aOR] = 4.30; 95% confidence interval [CI]: 2.03-9.14), pre-TBI heavy alcohol use (aOR = 3.04; CI: 1.08-8.55), and number of follow-up interviews (aOR = 2.05; CI: 1.39-4.50) were significant predictors of post-TBI arrest. CONCLUSION: Arrest rates of V/SM prior to TBI were consistent with rates of arrest for people of similar ages in the United States. Post-TBI rates were lower for V/SM than published rates of post-TBI arrests in civilians with TBI. As part of rehabilitation planning for V/SM with TBI, providers should assess for preinjury mental health services and alcohol misuse to (1) identify those who may be at risk for postinjury arrests and (2) provide relevant resources and/or supports

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment

Self-reported Participation Restrictions Among Male and Female Veterans With Traumatic Brain Injury in Veterans Health Administration Outpatient Polytrauma Programs

© 2020 Objectives: To identify areas of most restricted self-reported participation among veterans with traumatic brain injury (TBI), explore associations among participation restriction and clinical characteristics, and examine differences in participation restrictions by sex. Design: Retrospective cross-sectional design. Setting: National VA Polytrauma System of Care outpatient settings. Participants: Veterans with a confirmed TBI event (N=6065). Interventions: Not applicable. Main Outcome Measure(s): Mayo-Portland Participation Index (M2PI), a 5-point Likert-type scale with 8 items. Total score was converted to standardized T score for analysis. Results: The sample consisted of 5679 male and 386 female veterans with ≥1 clinically confirmed TBI events (69% white; 74% with blast exposure). The M2PI items with greatest perceived restrictions were social contact, leisure, and initiation. There were no significant differences between men and women on M2PI standardized T scores. Wilcoxon rank-sum analyses showed significant differences by sex on 4 items: leisure, residence, employment, and financial management (all P\u3c.01). In multinomial logistic regression on each item controlling for demographics, injury characteristics, and comorbidities, female veterans had significantly greater relative risk for part-time work and unemployment on the employment item and significantly less risk for impairment on the residence and financial management item. Conclusions: There was no significant difference between men and women. Veterans on M2PI standardized T scores, which masks differences in response patterns to individual items. Clinical teams should be encouraged to discuss perceived restrictions with patients and target these areas in treatment planning. Future work is needed to investigate the psychometric properties of the M2PI by biological sex

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

BackgroundAlthough concern exists regarding the adverse effects and rate of zolpidem use, especially long-term use, limited information is available concerning patterns of zolpidem use.ObjectiveTo examine the prevalence and correlates of zolpidem exposure in Iraq and Afghanistan Veterans (IAVs).MethodsA 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.ResultsOf 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.ConclusionThe 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

Plein ciel journal / Paul Louis Weiller, directeur

septembre 19381938/09 (N62,A11)-1938/10

Derivation of study cohort of Iraq and Afghanistan veterans with zolpidem exposure in fiscal year 2014.

<p>Derivation of study cohort of Iraq and Afghanistan veterans with zolpidem exposure in fiscal year 2014.</p

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

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