Objectives: To examine functional gains during inpatient rehabilitation for individuals with a pre-injury history of illicit drug use who were receiving neurostimulants as part of their clinical care, focusing on differences between those with and without a positive drug screen for cocaine or amphetamines upon hospital admission.

Methods: Retrospective cohort study including patients with TBI between 2006 and 2023 at an inpatient rehabilitation facility. All patients were enrolled in the TBI Model System (TBIMS) National Database. Based on information in the TBIMS database, patients reporting history of illicit drug use were selected for retrospective chart review to determine toxicology screening results and medications administered during rehabilitation stay. Charts were reviewed for 191 patients. After excluding those with interruptions in rehabilitation stay or length of stay (LOS) outliers (greater than 2 standard deviations above the mean), patients were divided into groups regarding neurostimulant administration. A total of 147 patients received neurostimulants and 25 did not. The group receiving neurostimulants was further divided based on admission toxicology screen results for amphetamines and/or cocaine. A total of 46 patients were positive for amphetamines/cocaine and 101 patients were negative. The primary outcome of this study was the FIM(TM), a standardized tool used to assess levels of disability and function during and following rehabilitation. FIM scores can be divided into motor and cognitive subcategories. To account for variation in rehabilitation LOS, a FIM Efficiency score can be calculated (FIM discharge score subtracted by FIM admission score, divided by rehabilitation LOS). Covariates included in data analysis were: length of post traumatic amnesia (PTA), age at injury, alcohol use, acute care LOS, education level, and sedative administration during rehabilitation.

Results: A significant difference (p=0.031) between those with and without positive amphetamine/cocaine screens was found for Total FIM Efficiency, even after controlling for the effects of covariates (M=3.30, SD=1.66 and M=2.47, SD=1.61 for negative and positive screens, respectively). A similar finding (p=0.013) was noted for FIM Motor Efficiency (M=2.54, SD=1.33 and M=1.86, SD=1.26 for negative and positive screens, respectively). No significant difference (p=0.51) was found between groups for FIM Cognitive Efficiency. Significant covariates in the models included acute care LOS for Total FIM and FIM Motor Efficiency and Length of PTA for FIM Cognitive Efficiency. Those with positive toxicology screens had longer acute stays and PTA compared with those with negative screens.

Conclusions: The prescription of neurostimulants for patients with a pre-injury history of drug use is common in brain injury rehabilitation. Regardless of toxicology results, patients showed positive functional gains during inpatient rehabilitation. However, those in the positive toxicology group made gains in a less efficient manner than those in the negative group. Admission toxicology reports can provide useful information to providers in planning rehabilitative care.

Background: Intimate partner violence related traumatic brain injury (IPV-TBI) is prevalent and understudied in the United States, and injury surveillance in the clinical setting is limited. Understanding data limitations is critical to understanding the importance of the issue to inform resource allocation and future advancements for violence-related traumatic brain injuries.

Objectives and Methods: This current study utilized a cross-sectional design to explore the prevalence of IPV-TBI in adults utilizing ICD 9/10 external cause of injury codes across the Traumatic Brain Injury Model Systems (TBIMS) and the National Trauma Data Bank (NTDB) from 2007-2021. The primary outcome was prevalence of IPV using International Classification of Diseases (ICD) external cause of injury codes. Secondary outcomes were prevalence of any violence-related TBI, strangulation, and rape using ICD external cause of injury codes. Demographic and injury characteristics were stratified by individuals with and without IPV, and significant testing was performed to determine statistical differences.

Results: Of 11,824 subjects in the TBIMS, 878 (7.4%) had violence-related TBI, of which, n=125 (14.2%) were women and n=752 (85.6%) men. There were <5 subjects with IPV (all women), 0 subjects with strangulation, and <5 subjects with rape codes. Researchers were unable to perform statistical testing in the TBIMS dataset due to low prevalence of IPV. Out of 3,305,827 subjects in the NTDB, n=332,886 (10.1%) had a violence-related TBI, of which n=50,311 (15.1%) were women and n=281,756 (84.6%) men. There were n=3,392 (0.1%) subjects with IPV (n=3,012 (88.8%) women and n=375 (11.1%) men); n=427 (0.0%) subjects with strangulation (n=260 (60.9%) women and 166 (38.9%) men); and n=684 (0.0%) with rape codes (n=530 (77.5%) women and n=154 (22.5%) men). Within the NTDB, all demographic (age, race, ethnicity, sex, payer) and injury characteristics (length of acute hospitalization, Glasgow Coma Scale, discharge disposition) differed significantly between those with IPV and those without IPV, and a large effect size was noted with age. IPV, strangulation, and rape external cause of injury codes were low across all years in the NTDB and negligible in the TBIMS dataset, with strangulation and rape coding rates declining in 2016-2021 after the ICD-10 transition.


Discussion: Injury surveillance using external cause of injury codes for the overlap of IPV and TBI are likely underutilized in the clinical setting, and prevalence of IPV-TBI was low in two large national datasets. ICD external cause of injury categorization for TBI and IPV is an inexpensive and widely available approach for prevalence estimation. Interdisciplinary (clinical, legal, and community) collaborators should examine federal and state policies for IPV-related TBI injury surveillance, identify best practices, and generate recommendations for screening, treating and documentation. ICD coding guidance to improve injury surveillance could be separated from mandatory reporting laws to improve uptake of IPV coding documentation.

Rates of TBI and opioid overdose are higher among homeless and precariously housed individuals. It is unclear whether traumatic brain injury (TBI) influences non-prescribed opioid use.

Objectives: To assess whether non-prescribed opioid use changes after incident TBI in an impoverished urban sample of people living in precarious housing.

Methods: A subset of participants of The Hotel Study, a naturalistic cohort study of health in adult residents of Vancouver’s poorest downtown neighbourhood (N>500, c. 2008), who participated in a nested study focused on the consequences of TBIs, were monitored monthly for TBI via the Ohio State University screening questionnaire. Eighty-five sub-study participants who acquired 1+ TBI (2016–2019), were each matched to 2 other Hotel Study participants without a record of TBI (N = 170 ‘controls’), based on age, gender, subjective health status at baseline, and opioid use in the pre-injury months (total N = 255). All participants attended monthly self-report (Time-Line-Follow-Back) substance use assessments in the year surrounding the captured TBIs.

Analysis: We used a mixed effects model to assess change in frequency of non-prescription opioid use (days used per week) after incident TBI. Assessments in the 6 months before and after TBI were modelled, using a zero-inflated binomial distribution. A group (injured vs. ‘controls’) by time (relative to injury) term was included to index differential change in opioid use after the time of the injured participant’s TBI, between injured participants and their controls.

Results: Opioid use increased uniquely after TBI, as indicated by significant group-by-time interactions (ps<.044). Results indicate those with TBI were uniquely more likely to use opioids in any given week in the 6 months after their injury versus before (odds ratio / OR for group(TBI)-time(after TBI), zero-component: 0.18 [0.04–0.83]), OR: time, zero-component: 0.80 [0.22–2.91]). Moreover, opioids were used around 32% more frequently per week after one’s TBI versus before (OR: group-time, conditional component: 4.01 [1.04–15.36], OR: time, conditional component: 0.33 [0.09–1.14]). Opioid use did not change significantly over time in the year surrounding injuries for the non-injured ‘matched controls’, nor was it different overall between groups (injured vs. controls; ps: .079–.742). Gender differences in opioid use were not apparent (ps: .378–.799), although older age was associated with less use (OR: age, conditional component: 0.92 [0.86–0.99], OR: age, zero-component: 1.06 [0.99–1.14]). Data from participants in the sub-study indicate largely substantial concordance of self-reported opioid use with urine drug screen results, with the exception of fentanyl (κ morphine = 0.63, κ methadone = 0.92, κ fentanyl = 0.12).

Conclusions: Traumatic brain injury is associated with increased non-prescription opioid use in the subsequent 6 months and may represent a modifiable risk factor for opioid use disorder and overdose.

Introduction: Brain Injury is a chronic condition where recovery and support needs are lifelong. Historically, the care system has focussed on ensuring persons get the required acute care after brain injury. This focus leaves many persons with lived experience (PWLE) and their families left to find needed supports on their own, often discovering that supports do not exist or are inaccessible. To date, there has been poor characterization of PWLE in the decades following injury.

Methods: The Ontario Brain Injury Association (OBIA) conducts a comprehensive longitudinal electronic survey to examine the long-term effects of acquired brain injury (ABI) on persons across the province of Ontario (Canada). The survey was originated more than 30 years ago and revised in 2020 to ensure relevance to the experience of PWLE. OBIA recruits persons through membership in local brain injury associations, brain injury public service providers, social media, association websites and public communications. Once enrolled in the study, participants complete the survey yearly.

Results: To date, 1,576 participants (1026 (65.1%) female, with a mean age of 50.8 (SD 14.3) have completed the revised survey. This diverse group, representing various ethnic and economic backgrounds and mechanisms of injury (MOI; motor vehicle collision (697 (44.3%), falls (496 (31.4%), sporting related (315 (20.0%), bike-related (142 (9.0%), assault (189 (20.0%), neurological illness (246 (15.6%), anoxia (72 (4.6%), other (589 (37.4%) from all regions of Ontario, provides a unique dataset to better understand the ongoing challenges faced by individuals post-injury. With an average duration of 20.3 (SD 17.4) years since injury, the findings reveal enduring impacts on mental health (85.7% with depression and 85.8% with anxiety post-injury, and approximately 80% requiring mental health treatment), activities of daily living, employment, and overall quality of life with work and social activities the most affected by their current symptoms. Symptoms such as headache, fatigue, and perceived memory and attention impairments were endorsed by more than 80% of participants with no effect of time since injury on endorsement (p-values ranged from 0.1 – 0.9). Participants with lower income were between 8% and 42% less likely to access fee-for-service (e.g. neuropsychology, psychological therapy, occupational therapy, outpatient rehabilitation, etc.) and single-payer health services (neurology, physiatry, etc.). Participants involved in litigation resulting from their brain injury, regardless of MOI, accessed services more (15 – 67%) than those without litigation involved despite having similar symptom burden and no sex differences.

Conclusions: Survey findings create a picture of ongoing unmet needs, underscoring critical need for comprehensive long-term medical and community support systems to address the ongoing challenges faced by individuals with brain injuries. This research will inform policy and practice, ultimately enhancing the care pathway and optimizing recovery for individuals living with the long-term consequences of brain injury.

Introduction: Traumatic brain injury (TBI) is a significant public health concern resulting in hospitalizations, morbidity and mortality globally. While it is well-established that older adults are at high risk of sustaining a TBI and are vulnerable to its effects, there is a dearth of research on the impact of TBI on healthy aging. Limited outcome data exist at the population level to evaluate care quality and equity for people aging with this injury.

Objective: To study the impact of TBI on aging and healthcare utilization by implementing Quality Indicators that examine TBI care quality and equity for 1) people who were injured as an older adult (i.e., 65 years or older at time of injury; cohort 1) and 2) people who were injured at a younger age and have aged with their injury (cohort 2).

Methods: Provincial administrative health services data from publicly funded healthcare databases were used. 13 Quality Indicators were co-developed with healthcare partners and persons with lived experience to measure care quality for both target populations. A variety of data were collected for cohort 1 (2016-2022), including, risk-adjusted incidence and mortality rates, healthcare utilization, admission to rehabilitation, primary care follow-up, and rate of discharge by disposition (e.g., long-term care). For cohort 2, mortality and healthcare utilization data were analyzed for a 10-year period (2012-2022) and hard-matching was applied to compare data between cases and controls. Quality Indicator performance was explored using sociodemographic variables such as age group, sex, geographic region, and income.

Results: For cohort 1, the incidence rate for all severities of TBI increased with age. Older adults were more likely to be admitted to general rehab than specialized TBI rehab (8.35% vs 3.04% for persons with moderate to severe TBI). Emergency visit rates in years 1 and 2 increased with age (156.8 per 100 PY in 80+ age group vs. 114.9 per 100 PY in 65-79 years age). The rate of fall-related healthcare usage in the first two years after moderate-severe TBI was also higher among elderly people (43.7 per 100 PY in 80+ age group vs. 30.6 per 100 PY in 65–79-year group). For the matched cohort, cause of injury and admission to rehab significantly influenced survival probability. People who sustained their injury by falling had the lowest survival probability; people with TBI who received inpatient rehab had higher survival probability than those who did not.

Conclusion: This work establishes a foundation for quality-of-care assessments and monitoring disparity in care for older adults with TBI at a population level, while examining the impact of aging with TBI on mortality and healthcare utilization. Ensuring that older people receive appropriate rehabilitation and support to reduce falls is necessary to maintain independence in the community.

Objectives: Cardiovascular disease is the leading cause of death in the United States. Prior research suggests that individuals with traumatic brain injury (TBI) have an elevated risk of death from cardiovascular disease compared with the general population. The purpose of this project is to characterize the factors associated with death due to cardiovascular causes following complicated mild to severe TBI.

Methods: This study included 16,166 participants with complicated mild to severe TBI enrolled in the TBI Model Systems database. The TBI Model Systems enrolls individuals aged 16-years and older during inpatient rehabilitation admission following complicated mild to severe TBI, and completes follow-up interviews at 1-year, 2-years, 5-years, and every 5 years thereafter post-injury up to 30 years post-injury. Cause of death was determined using primary cause of death listed on death certificates. Primary cause of death was identified as being due to cardiovascular causes if the primary cause of death was coded with ICD-9 codes 390-459 or ICD-10 codes I00-I99, which correspond to diseases of the circulatory system. Individuals who died with unknown primary cause of death were excluded. A competing risk regression analysis was completed to identify demographic and injury related factors associated with increased risk of mortality due to cardiovascular-related causes.

Results: Overall, 2,767 (17.1%) individuals died, of which 596 (21.5%) died due to cardiovascular related causes and 2,171 (78.5%) died due to other causes. Those who died due to cardiovascular causes were older (sub distribution hazard ratio [SHR] 1.060, 95% 1.051 – 1.068, p < 0.001), more likely to be male (SHR 1.399, 95% CI 1.124 – 1.741, p = 0.003) or divorced at time of injury (SHR 1.567, 95% CI 1.091 – 2.250, p = 0.015), and had lower functional independence measure (FIM) motor scores at inpatient rehabilitation discharge (SHR 0.991, 95% CI 0.985 – 0.998, p = 0.015). Conversely, individuals who identified as Asian/Pacific Islander (SHR 0.359, 95% CI 0.146 – 0.885, p = 0.026) and had at least a high school education (SHR 0.749, 95% CI 0.593 – 0.946, p = 0.015) were less likely to die due to cardiovascular causes. Pre-morbid alcohol or drug use, duration of PTA, FIM cognitive score at inpatient rehabilitation discharge, payor source for inpatient rehabilitation admission, and region lived at time of injury were not significantly associated with death due to cardiovascular causes.

Conclusions: Cardiovascular related diseases accounted for over one-fifth of deaths following complicated mild to severe TBI. Males, individuals of older age, those who are divorced, and with lower mobility at discharge from inpatient rehabilitation are at increased risk for cardiovascular related death. These findings highlight the need for early screening for cardiovascular risk factors after TBI, particularly for those with increased risk of cardiovascular-related mortality.