Browsing by Author "Rabinowitz, Amanda R."

Now showing 1 - 5 of 5
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    Aging with Traumatic Brain Injury: Deleterious Effects of Injury Chronicity Are Most Pronounced in Later Life
    (Mary Ann Liebert, 2021) Rabinowitz, Amanda R.; Kumar, Raj G.; Sima, Adam; Venkatesan, Umesh M.; Juengst, Shannon B.; O’Neil-Pirozzi, Therese M.; Watanabe, Thomas K.; Goldin, Yelena; Hammond, Flora M.; Dreer, Laura E.; Physical Medicine and Rehabilitation, School of Medicine
    Understanding the effects of age on longitudinal traumatic brain injury (TBI) outcomes requires attention to both chronic and evolving TBI effects and age-related changes in health and function. The present study examines the independent and interactive effects of aging and chronicity on functional outcomes after TBI. We leveraged a well-defined cohort of individuals who sustained a moderate/severe TBI and received acute inpatient rehabilitation at specialized centers with high follow up rate as part of their involvement in the TBI Model Systems longitudinal study. We selected individuals at one of two levels of TBI chronicity (either 2 or 10 years post-injury) and used an exact matching procedure to obtain balanced chronicity groups based on age and other characteristics (N = 1993). We found that both older age and greater injury chronicity were related to greater disability, reduced functional independence, and less community participation. There was a significant age by chronicity interaction, indicating that the adverse effects of greater time post-injury were most pronounced among survivors who were age 75 or older. The inflection point at roughly 75 years of age was corroborated by post hoc analyses, dividing the sample by age at 75 years and examining the interaction between age group and chronicity. These findings point to a need for provision of rehabilitation services in the chronic injury period, particularly for those who are over 75 years old. Future work should investigate the underlying mechanisms of this interaction towards the goal of developing interventions and models of care to promote healthy aging with TBI.
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    Anxiety Trajectories the First 10 Years After a Traumatic Brain Injury (TBI): A TBI Model Systems Study
    (Elsevier, 2022-11) Neumann, Dawn; Juengst, Shannon B.; Bombardier, Charles H.; Finn, Jacob A.; Miles, Shannon R.; Zhang, Yue; Kennedy, Richard; Rabinowitz, Amanda R.; Thomas, Amber; Dreer, Laura E.; Physical Medicine and Rehabilitation, School of Medicine
    Objective Determine anxiety trajectories and predictors up to 10 years posttraumatic brain injury (TBI). Design Prospective longitudinal, observational study. Setting Inpatient rehabilitation centers. Participants 2836 participants with moderate to severe TBI enrolled in the TBI Model Systems National Database who had ≥2 anxiety data collection points (N=2836). Main Outcome Measure Generalized Anxiety Disorder-7 (GAD-7) at 1, 2, 5, and 10-year follow-ups. Results Linear mixed models showed higher GAD-7 scores were associated with Black race (P<.001), public insurance (P<.001), pre-injury mental health treatment (P<.001), 2 additional TBIs with loss of consciousness (P=.003), violent injury (P=.047), and more years post-TBI (P=.023). An interaction between follow-up year and age was also related to GAD-7 scores (P=.006). A latent class mixed model identified 3 anxiety trajectories: low-stable (n=2195), high-increasing (n=289), and high-decreasing (n=352). The high-increasing and high-decreasing groups had mild or higher GAD-7 scores up to 10 years. Compared to the low-stable group, the high-decreasing group was more likely to be Black (OR=2.25), have public insurance (OR=2.13), have had pre-injury mental health treatment (OR=1.77), and have had 2 prior TBIs (OR=3.16). Conclusions A substantial minority of participants had anxiety symptoms that either increased (10%) or decreased (13%) over 10 years but never decreased below mild anxiety. Risk factors of anxiety included indicators of socioeconomic disadvantage (public insurance) and racial inequities (Black race) as well as having had pre-injury mental health treatment and 2 prior TBIs. Awareness of these risk factors may lead to identifying and proactively referring susceptible individuals to mental health services.
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    Depression, Anxiety, and Suicidality in Individuals With Chronic Traumatic Brain Injury Before and During the COVID-19 Pandemic: A National Institute on Disability, Independent Living, and Rehabilitation Research Traumatic Brain Injury Model Systems Study
    (Elsevier, 2023) Katta-Charles, Sheryl; Adams, Leah M.; Chiaravalloti, Nancy D.; Hammond, Flora M.; Perrin, Paul B.; Rabinowitz, Amanda R.; Venkatesan, Umesh M.; Weintraub, Alan H.; Bombardier, Charles H.; Physical Medicine and Rehabilitation, School of Medicine
    Objective: To examine the prevalence, severity, and correlates of depression, anxiety, and suicidal ideation in people with traumatic brain injury (TBI) assessed before and during the COVID-19 pandemic. Design: Retrospective cohort study using data collected through the Traumatic Brain Injury Model Systems (TBIMS) network at 1, 2, 5, 10, 15, 20, 25, or 30 years post TBI. Setting: United States-based TBIMS rehabilitation centers with telephone assessment of community residing participants. Participants: Adults (72.4% male; mean age, 47.2 years) who enrolled in the TBIMS National Database and completed mental health questionnaires prepandemic (January 1, 2017 to February 29, 2020; n=5000) or during pandemic (April 1, 2022 to June 30, 2021; n=2009) (N=7009). Interventions: Not applicable. Main outcome measures: Patient Health Questionnaire-9 and Generalized Anxiety Disorder-7 questionnaire. Results: Separate linear and logistic regressions were constructed with demographic, psychosocial, injury-related, and functional characteristics, along with a binary indicator of COVID-19 pandemic period (prepandemic vs during pandemic), as predictors of mental health outcomes. No meaningful differences in depression, anxiety, or suicidal ideation were observed before vs during the COVID-19 pandemic. Correlations between predictors and mental health outcomes were similar before and during the pandemic. Conclusions: Contrary to our predictions, the prevalence, severity, and correlates of mental health conditions were similar before and during the COVID-19 pandemic. Results may reflect generalized resilience and are consistent with the most recent findings from the general population that indicate only small, transient increases in psychological distress associated with the pandemic. While unworsened, depression, anxiety, and suicidal ideation remain prevalent and merit focused treatment and research efforts.
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    Societal Participation of People With Traumatic Brain Injury Before and During the COVID-19 Pandemic: A NIDILRR Traumatic Brain Injury Model Systems Study
    (Elsevier, 2023) Venkatesan, Umesh M.; Adams, Leah M.; Rabinowitz, Amanda R.; Agtarap, Stephanie; Bombardier, Charles H.; Bushnik, Tamara; Chiaravalloti, Nancy D.; Juengst, Shannon B.; Katta-Charles, Sheryl; Perrin, Paul B.; Pinto, Shanti M.; Weintraub, Alan H.; Whiteneck, Gale G.; Hammond, Flora M.; Physical Medicine and Rehabilitation, School of Medicine
    Objective: To examine the effect of the COVID-19 pandemic on societal participation in people with moderate-to-severe traumatic brain injury (TBI). Design: Cross-sectional retrospective cohort. Setting: National TBI Model Systems centers, United States. Participants: TBI Model Systems enrollees (N=7003), ages 16 and older and 1-30 years postinjury, interviewed either prepandemic (PP) or during the pandemic (DP). The sample was primarily male (72.4%) and White (69.5%), with motor vehicle collisions as the most common cause of injury (55.1%). Interventions: Not applicable. Main outcome measure: The 3 subscales of the Participation Assessment with Recombined Tools-Objective: Out and About (community involvement), Productivity, and Social Relations. Results: Out and About, but not Productivity or Social Relations, scores were appreciably lower among DP participants compared to PP participants (medium effect). Demographic and clinical characteristics showed similar patterns of association with participation domains across PP and DP. When their unique contributions were examined in regression models, age, self-identified race, education level, employment status, marital status, income level, disability severity, and life satisfaction were variably predictive of participation domains, though most effects were small or medium in size. Depression and anxiety symptom severities each showed small zero-order correlations with participation domains across PP and DP but had negligible effects in regression analyses. Conclusions: Consistent with the effect of COVID-19 on participation levels in the general population, people with TBI reported less community involvement during the pandemic, potentially compounding existing postinjury challenges to societal integration. The pandemic does not appear to have altered patterns of association between demographic/clinical characteristics and participation. Assessing and addressing barriers to community involvement should be a priority for TBI treatment providers. Longitudinal studies of TBI that consider pandemic-related effects on participation and other societally linked outcomes will help to elucidate the potential longer-term effect the pandemic has on behavioral health in this population.
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    Using Machine Learning to Examine Suicidal Ideation After TBI: A TBI Model Systems National Database Study
    (Wolters Kluwer, 2023) Fisher, Lauren B.; Curtiss, Joshua E.; Klyce, Daniel W.; Perrin, Paul B.; Juengst, Shannon B.; Gary, Kelli W.; Niemeier, Janet P.; McConnell Hammond, Flora; Bergquist, Thomas F.; Wagner, Amy K.; Rabinowitz, Amanda R.; Giacino, Joseph T.; Zafonte, Ross D.; Physical Medicine and Rehabilitation, School of Medicine
    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.