Evaluating the Cross-Sectional and Longitudinal Relationships Predicting Suicidal Ideation Following Traumatic Brain Injury

Suicide Attempts and Ideation Among Veterans/Service Members and Non-Veterans Over 5 Years Following Traumatic Brain Injury: A Combined NIDILRR and VA TBI Model Systems Study

OBJECTIVE

This study compared rates of suicide attempt (SA) and suicidal ideation (SI) during the first 5 years after traumatic brain injury (TBI) among veterans and service members (V/SMs) in the Veterans Affairs (VA) and the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR) Model Systems National Databases to each other and to non-veterans (non-Vs) in the NIDILRR database.

SETTING

Twenty-one NIDILRR and 5 VA TBI Model Systems (TBIMS) inpatient rehabilitation facilities in the United States.

PARTICIPANTS

Participants with TBI were discharged from rehabilitation alive, had a known military status recorded (either non-V or history of military service), and successful 1-, 2-, and/or 5-year follow-up interviews completed between 2009 and 2021. The year 1 cohort included 8737 unique participants (8347 with SA data and 3987 with SI data); the year 2 (7628 participants) and year 5 (4837 participants) cohorts both had similar demographic characteristics to the year 1 cohort.

DESIGN

Longitudinal design with data collected across TBIMS centers at 1, 2, and 5 years post-injury.

MAIN OUTCOMES AND MEASURES

History of SA in past year and SI in past 2 weeks assessed by the Patient Health Questionnaire-9 (PHQ-9). Patient demographics, injury characteristics, and rehabilitation outcomes were also assessed.

RESULTS

Full sample rates of SA were 1.9%, 1.5%, and 1.6%, and rates of SI were 9.6%, 10.1%, and 8.7% (respectively at years 1, 2, and 5). There were significant differences among groups based on demographic, injury-related, mental/behavioral health, and functional outcome variables. Characteristics predicting SA/SI related to mental health history, substance use, younger age, lower functional independence, and greater levels of disability.

CONCLUSIONS

Compared with participants with TBI in the NIDILRR system, higher rates of SI among V/SMs with TBI in the VA system appear associated with risk factors observed within this group, including mental/behavioral health characteristics and overall levels of disability.

Using Machine Learning to Examine Suicidal Ideation After Traumatic Brain Injury: A Traumatic Brain Injury Model Systems National Database Study

OBJECTIVE

The aim of the study was to predict suicidal ideation 1 yr after moderate to severe traumatic brain injury.

DESIGN

This study used a cross-sectional design with data collected through the prospective, longitudinal Traumatic Brain Injury Model Systems network at hospitalization and 1 yr after injury. Participants who completed the Patient Health Questionnaire-9 suicide item at year 1 follow-up ( N = 4328) were included.

RESULTS

A gradient boosting machine algorithm demonstrated the best performance in predicting suicidal ideation 1 yr after traumatic brain injury. Predictors were Patient Health Questionnaire-9 items (except suicidality), Generalized Anxiety Disorder-7 items, and a measure of heavy drinking. Results of the 10-fold cross-validation gradient boosting machine analysis indicated excellent classification performance with an area under the curve of 0.882. Sensitivity was 0.85 and specificity was 0.77. Accuracy was 0.78 (95% confidence interval, 0.77-0.79). Feature importance analyses revealed that depressed mood and guilt were the most important predictors of suicidal ideation, followed by anhedonia, concentration difficulties, and psychomotor disturbance.

CONCLUSIONS

Overall, depression symptoms were most predictive of suicidal ideation. Despite the limited clinical impact of the present findings, machine learning has potential to improve prediction of suicidal behavior, leveraging electronic health record data, to identify individuals at greatest risk, thereby facilitating intervention and optimization of long-term outcomes after traumatic brain injury.

Cytokine Profiles Differentiate Symptomatic from Asymptomatic PTSD in Service Members and Veterans with Chronic Traumatic Brain Injury

Traumatic brain injuries (TBI) and posttraumatic stress disorder (PTSD) are commonly observed comorbid occurrences among military service members and veterans (SMVs). In this cross-sectional study, SMVs with a history of TBI were stratified into symptomatic and asymptomatic PTSD groups based on posttraumatic stress checklist-civilian (PCL-C) total scores. Blood-based biomarkers were assessed, and significant differential markers were associated with scores from multiple neurobehavioral self-report assessments. PCL-C cutoffs were total scores >50 (PTSD symptomatic) and <25 (asymptomatic). Cytokines IL6, IL8, TNFα, and IL10 were significantly elevated (p < 0.05−0.001) in the TBI+/PTSD symptomatic group compared to the TBI+/asymptomatic group. Cytokine levels of IL8, TNFα, and IL10 were strongly associated with PCL-C scores (0.356 < r > 0.624 for all, p < 0.01 for all), while TNFα and IL10 were additionally associated with NSI totals (r = 0.285 and r = 0.270, p < 0.05, respectively). This is the first study focused on PTSD symptom severity to report levels of circulating pro-inflammatory IL8, specifically in SMVs with TBI. These data suggest that within the military TBI population, there are unique cytokine profiles that relate to neurobehavioral outcomes associated with TBI and PTSD.

Role of Inflammation in Traumatic Brain Injury-Associated Risk for Neuropsychiatric Disorders: State of the Evidence and Where Do We Go From Here

In the past decade, there has been an increasing awareness that traumatic brain injury (TBI) and concussion substantially increase the risk for developing psychiatric disorders. Even mild TBI increases the risk for depression and anxiety disorders such as posttraumatic stress disorder by two- to threefold, predisposing patients to further functional impairment. This strong epidemiological link supports examination of potential mechanisms driving neuropsychiatric symptom development after TBI. One potential mechanism for increased neuropsychiatric symptoms after TBI is via inflammatory processes, as central nervous system inflammation can last years after initial injury. There is emerging preliminary evidence that TBI patients with posttraumatic stress disorder or depression exhibit increased central and peripheral inflammatory markers compared with TBI patients without these comorbidities. Growing evidence has demonstrated that immune signaling in animals plays an integral role in depressive- and anxiety-like behaviors after severe stress or brain injury. In this review, we will 1) discuss current evidence for chronic inflammation after TBI in the development of neuropsychiatric symptoms, 2) highlight potential microglial activation and cytokine signaling contributions, and 3) discuss potential promise and pitfalls for immune-targeted interventions and biomarker strategies to identify and treat TBI patients with immune-related neuropsychiatric symptoms.

Identifying group-based patterns of suicidal ideation over the first 10 years after moderate-to-severe TBI

OBJECTIVE

To identify group-based patterns in suicidal ideation (SI) over the first 10 years after traumatic brain injury (TBI).

METHODS

Participants included 9539 individuals in the TBI Model Systems National Database who responded to Patient Health Questionnaire-9 Item 9 assessing SI at 1, 2, 5, and/or 10 years post-injury. A k-means cluster analysis was conducted to determine group-based patterns of SI, and pre-injury variables were compared with ANOVAs and chi-square tests.

RESULTS

SI and attempts decreased over time. Four group-based patterns emerged: Low, increasing, moderate, and decreasing SI. The low SI group comprised 89% of the sample, had the highest pre-injury employment, fewer mental health vulnerabilities, least severe injuries, and were oldest. The increasing SI group had the most severe TBIs, were youngest, and disproportionately Black or Asian/Pacific Islander.

CONCLUSION

These findings reinforce the importance of mental health and suicide risk assessment during chronic recovery from TBI.

Application of neuropsychology and imaging to brain injury and use of the integrative cognitive rehabilitation psychotherapy model

BACKGROUND

An early approach to cognitive rehabilitation therapy (CRT) was developed based on A. R. Luria's theory of brain function. Expanding upon this approach, the Integrative Cognitive Rehabilitation Psychotherapy model (ICRP) was advanced.

OBJECTIVE

To describe the ICRP approach to treatment of clients post brain injury and provide a comprehensive list of evaluation tools to determine the client's abilities and needs. Finally, to provide a link between CRT and functional imaging studies designed to improve rehabilitation efforts.

METHODS

History of cognitive rehabilitation and neuropsychological testing is reviewed and description of cognitive, academic, psychiatric, and substance abuse tools are provided. Cognitive and emotional treatment techniques are fully described. Additionally, a method of determining the client's stage of recovery and pertinent functional imaging studies is detailed.

RESULTS

Authors have been able to provide a set of tools and techniques to use in comprehensive treatment of clients with brain injury.

CONCLUSIONS

Inclusive treatment which is outlined in the ICRP model is optimal for the client's recovery and return to a full and satisfying life post brain injury. The model provides a framework for neuropsychologists to integrate issues that tend to co-occur in clients living with brain injury into a unified treatment plan.

Relations among Suicidal Ideation, Depressive Symptoms, and Functional Independence during the Ten Years after Traumatic Brain Injury: A Model Systems Study

OBJECTIVE

To investigate relative causality in relations among suicidal ideation (SI), depressive symptoms, and functional independence over the first 10 years after traumatic brain injury (TBI).

DESIGN

Prospective longitudinal design with data collected through the TBI Model Systems (TBIMS) network at acute rehabilitation hospitalization, as well as 1, 2, 5, and 10 years after injury.

SETTING

United States Level I/II trauma centers and inpatient rehabilitation centers with telephone follow-up.

PARTICIPANTS

Individuals enrolled into the TBIMS National Database (N=9539) with at least one SI score at any follow-up data collection (72.1% male, mean age = 39.39 years).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURE

Patient Health Questionnaire-9 and Functional Independence Measure at years 1, 2, 5, and 10 post-injury.

RESULTS

A cross-lagged panel structural equation model (SEM), which is meant to indirectly infer causality through longitudinal correlational data, suggested that SI, depressive symptoms, and functional independence each significantly predicted themselves over time. Within the model, bivariate correlations among variables were all significant within each time point. Between years 1 and 2 and between years 2 and 5, depressive symptoms had a larger effect on SI than SI had on depressive symptoms. Between years 5 and 10, there was reciprocal causality between the two variables. Functional independence more strongly predicted depressive symptoms than the reverse between years 1 and 2 as well as years 2 and 5, but its unique effects on SI over time were extremely marginal or absent after controlling for depressive symptoms.

CONCLUSIONS

A primary goal for rehabilitation and mental health providers should be to monitor and address elevated symptoms of depression as quickly as possible before they translate into SI, particularly for individuals with TBI who have reduced functional independence. Doing so may be a key to breaking the connection between low functional independence and SI.