Christopher R. Pretz

US population estimates of health and social outcomes 5 years after rehabilitation for traumatic brain injury.

Objective:To estimate the number of adults in the United States from 2006 to 2012 who manifest selected health and social outcomes 5 years following a traumatic brain injury (TBI) that required acute inpatient rehabilitation. Design:Secondary data analysis. Setting:Acute inpatient rehabilitation facilities. Participants:Patients 16 years and older receiving acute inpatient rehabilitation for a primary diagnosis of TBI. Main Outcome Measures:Mortality, functional independence, societal participation, subjective well-being, and global outcome. Results:Annually from 2001 to 2007, an average of 13 700 patients aged 16 years or older received acute inpatient rehabilitation in the United States with a primary diagnosis of TBI. Approximately 1 in 5 patients had died by the 5-year postinjury assessment. Among survivors, 12% were institutionalized and 50% had been rehospitalized at least once. Approximately one-third of patients were not independent in everyday activities. Twenty-nine percent were dissatisfied with life, with 8% reporting markedly depressed mood. Fifty-seven percent were moderately or severely disabled overall, with 39% having deteriorated from a global outcome attained 1 or 2 years postinjury. Of those employed preinjury, 55% were unemployed. Poorer medical, functional, and participation outcomes were associated with, but not limited to, older age. Younger age groups had poorer mental and emotional outcomes. Deterioration in global outcome was common and not age-related. Conclusions:Significant mortality and morbidity were evident at 5 years postinjury. The deterioration in global outcomes observed regardless of age suggests that multiple influences contribute to poorer outcomes. Public health interventions intended to reduce post–acute inpatient rehabilitation mortality and morbidity rates will need to be multifaceted and age-specific.

An introduction to applying individual growth curve models to evaluate change in rehabilitation: a National Institute on Disability and Rehabilitation Research Traumatic Brain Injury Model Systems report.

The abundance of time-dependent information contained in the Spinal Cord Injury and the Traumatic Brain Injury Model Systems National Databases, and the increased prevalence of repeated-measures designs in clinical trials highlight the need for more powerful longitudinal analytic methodologies in rehabilitation research. This article describes the particularly versatile analytic technique of individual growth curve (IGC) analysis. A defining characteristic of IGC analysis is that change in outcome such as functional recovery can be described at both the patient and group levels, such that it is possible to contrast 1 patient with other patients, subgroups of patients, or a group as a whole. Other appealing characteristics of IGC analysis include its flexibility in describing how outcomes progress over time (whether in linear, curvilinear, cyclical, or other fashion), its ability to accommodate covariates at multiple levels of analyses to better describe change, and its ability to accommodate cases with partially missing outcome data. These features make IGC analysis an ideal tool for investigating longitudinal outcome data and to better equip researchers and clinicians to explore a multitude of hypotheses. The goal of this special communication is to familiarize the rehabilitation community with IGC analysis and encourage the use of this sophisticated research tool to better understand temporal change in outcomes.

Life Expectancy after Inpatient Rehabilitation for Traumatic Brain Injury in the United States

This study characterized life expectancy after traumatic brain injury (TBI). The TBI Model Systems (TBIMS) National Database (NDB) was weighted to represent those ≥16 years of age completing inpatient rehabilitation for TBI in the United States (US) between 2001 and 2010. Analyses included Standardized Mortality Ratios (SMRs), Cox regression, and life expectancy. The US mortality rates by age, sex, race, and cause of death for 2005 and 2010 were used for comparison purposes. Results indicated that a total of 1325 deaths occurred in the weighted cohort of 6913 individuals. Individuals with TBI were 2.23 times more likely to die than individuals of comparable age, sex, and race in the general population, with a reduced average life expectancy of 9 years. Independent risk factors for death were: older age, male gender, less-than-high school education, previously married at injury, not employed at injury, more recent year of injury, fall-related TBI, not discharged home after rehabilitation, less functional independence, and greater disability. Individuals with TBI were at greatest risk of death from seizures; accidental poisonings; sepsis; aspiration pneumonia; respiratory, mental/behavioral, or nervous system conditions; and other external causes of injury and poisoning, compared with individuals in the general population of similar age, gender, and race. This study confirms prior life expectancy study findings, and provides evidence that the TBIMS NDB is representative of the larger population of adults receiving inpatient rehabilitation for TBI in the US. There is an increased risk of death for individuals with TBI requiring inpatient rehabilitation.

Descriptive Modeling of Longitudinal Outcome Measures in Traumatic Brain Injury: A National Institute on Disability and Rehabilitation Research Traumatic Brain Injury Model Systems Study

Establishing accurate mathematical models of outcome measures is essential in understanding change throughout the rehabilitation process. The goal of this study is to identify the best-fitting descriptive models for a set of commonly adopted outcome measures found within the Traumatic Brain Injury Model Systems National Database where the modeling is based on data submission through 2011 and the complete range of recorded time points since injury for each individual, where time points range from admission to rehabilitation to 20 years postinjury. The statistical methodology and the application of the methodology contained herein may be used to assist researchers and clinicians in (1) modeling the outcome measures considered, (2) modeling various portions of these outcomes by stratification and/or truncating time periods, (3) modeling longitudinal outcome measures not considered, and (4) establishing models as a necessary precursor in conducting individual growth curve analysis.

Mechanical Ventilation, Health, and Quality of Life Following Spinal Cord Injury

OBJECTIVE To examine differences in perceived quality of life (QOL) at 1 year postinjury between people with tetraplegia who required mechanical ventilation assistance at discharge from rehabilitation and those who did not. DESIGN Prospective cross-sectional examination of people with spinal cord injury (SCI) drawn from the SCI Model Systems National Database. SETTING Community. PARTICIPANTS People with tetraplegia (N=1635) who sustained traumatic SCI between January 1, 1994, and September 30, 2008, who completed a 1-year follow-up interview, including 79 people who required at least some use of a ventilator at discharge from rehabilitation. INTERVENTIONS Not applicable. MAIN OUTCOME MEASURES Satisfaction With Life Scale (SWLS); Craig Handicap Assessment and Reporting Technique (CHART)-Short Form Physical Independence, Mobility, Social Integration, and Occupation subscales; Patient Health Questionnaire-9 (PHQ-9), Medical Outcomes Study 36-Item Short-Form Health Survey self-perceived health status. RESULTS Significant differences were found between the ventilator-user (VU) group and non-ventilator-user (NVU) group for cause of trauma, proportion with complete injury, neurologic impairment level, and number of rehospitalizations. The NVU group had significantly higher SWLS and CHART Social Integration scores than the VU group after controlling for selected covariates. The NVU group also had more positive perceived health status compared with a year previously and a lower incidence of depression assessed by using the PHQ-9 than the VU group. There were no significant differences between groups for perceived current health status. CONCLUSIONS People in this study who did not require mechanical ventilation at discharge from rehabilitation post-SCI reported generally better health and improved QOL compared with those who required ventilator assistance at 1 year postinjury. Nonetheless, the literature suggests that perceptions of QOL improve as people live in the community for longer periods.

Longitudinal Description of the Glasgow Outcome Scale-Extended for Individuals in the Traumatic Brain Injury Model Systems National Database: A National Institute on Disability and Rehabilitation Research Traumatic Brain Injury Model Systems Study

OBJECTIVE To comprehensively describe the temporal patterns of global outcome after traumatic brain injury (TBI) in the Traumatic Brain Injury Model Systems National Database (TBIMS NDB). DESIGN Longitudinal prospective cohort study. SETTING TBI Model Systems centers. PARTICIPANTS Patients (N=3870) ≥16 years of age with moderate or severe TBI enrolled in the TBIMS NDB. INTERVENTIONS None. MAIN OUTCOME MEASURE Glasgow Outcome Scale-Extended (GOS-E). RESULTS The trajectory of the GOS-E scores is best described with a model of quadratic change, in which scores initially increase and peak approximately 10 years after the first GOS-E assessment, and then decrease. Change occurs most rapidly in the initial and final years of the timeline. There was significant variability in each growth parameter (P<.05). A reduced multilevel model was built, including all covariates (age at first GOS-E assessment, FIM, race, sex, rehabilitation length of stay) that related significantly to the growth parameters. An interactive tool was created to generate individual level trajectories based on various combinations of covariate values. Results provide an individual level account of the chronological progression of TBI outcomes, as measured by the GOS-E. CONCLUSIONS Individual growth curve analysis is a statistically rigorous approach to describe temporal change with respect to the GOS-E at the individual level for participants within the TBIMS NDB. Results indicated that, for individuals in the TBIMS NDB as a group, functional status as measured by the GOS-E initially improves, plateaus, and then begins to decline. Factors such as age at first GOS-E assessment, race, FIM score at rehabilitation admission, and rehabilitation length of stay were found to influence baseline GOS-E scores, as well as the rate and extent of both improvement and decline over time. Additional research may be required to determine the generalizability of these findings and the usefulness of this tool for clinical applications.

Ten-Year Employment Patterns of Working Age Individuals After Moderate to Severe Traumatic Brain Injury: A National Institute on Disability and Rehabilitation Research Traumatic Brain Injury Model Systems Study

OBJECTIVE To describe the 10-year patterns of employment for individuals of working age discharged from a Traumatic Brain Injury Model Systems (TBIMS) center between 1989 and 2009. DESIGN Secondary data analysis. SETTING Inpatient rehabilitation centers. PARTICIPANTS Patients aged 16 to 55 years (N=3618) who were not retired at injury, received inpatient rehabilitation at a TBIMS center, were discharged alive between 1989 and 2009, and had at least 3 completed follow-up interviews at postinjury years 1, 2, 5, and 10. INTERVENTIONS Not applicable. MAIN OUTCOMES MEASURE Employment. RESULTS Patterns of employment were generated using a generalized linear mixed model, where these patterns were transformed into temporal trajectories of probability of employment via random effects modeling. Covariates demonstrating significant relations to growth parameters that govern the trajectory patterns were similar to those noted in previous cross-sectional research and included age, sex, race/ethnicity, education, preinjury substance misuse, preinjury vocational status, and days of posttraumatic amnesia. The calendar year in which the injury occurred also greatly influenced trajectories. An interactive tool was developed to provide visualization of all postemployment trajectories, with many showing decreasing probabilities of employment between 5 and 10 years postinjury. CONCLUSIONS These results highlight that postinjury employment after moderate to severe traumatic brain injury (TBI) is a dynamic process, with varied patterns of employment for individuals with specific characteristics. The overall decline in trajectories of probability of employment between 5 and 10 years postinjury suggests that moderate to severe TBI may have unfavorable chronic effects and that employment outcome is highly influenced by national labor market forces. Additional research targeting the underlying drivers of the decline between 5 and 10 years postinjury is recommended, as are interventions that target influencing factors.

Global outcome trajectories after TBI among survivors and nonsurvivors: a National Institute on Disability and Rehabilitation Research Traumatic Brain Injury Model Systems Study

Objective:To compare long-term functional outcome trajectories of individuals with traumatic brain injury (TBI) who survive with those who expire more than 5 years postinjury, using individual growth curve analysis. Design:Secondary analysis of data from a multicenter longitudinal cohort study. Setting:Acute inpatient rehabilitation facilities that are current or former TBI Model Systems. Participants:Individuals 16 years and older with a primary diagnosis of TBI. Main Outcome Measures:Glasgow Outcome Scale–Extended; Disability Rating Scale. Results:Individuals in the TBI Model Systems who expire several years after injury demonstrate worse functional status at baseline and a steeper rate of decline over time as measured by both the Glasgow Outcome Scale–Extended and the Disability Rating Scale. There was significant variability in each growth parameter (P < .05) for both instruments. A reduced model was built for each outcome, including all covariates that related significantly to the growth parameters. An interactive tool was created for each outcome to generate individual-level trajectories based on various combinations of covariate values. Conclusion:Individuals with TBI who die several years after injury demonstrate functional trajectories that differ markedly from those of survivors. Opportunities should be sought for health management interventions to improve health and longevity after TBI.

Components of Traumatic Brain Injury Severity Indices

The purpose of this study was to determine whether there are underlying dimensions common among traditional traumatic brain injury (TBI) severity indices and, if so, the extent to which they are interchangeable when predicting short-term outcomes. This study had an observational design, and took place in United States trauma centers reporting to the National Trauma Data Bank (NTDB). The sample consisted of 77,470 unweighted adult cases reported to the NTDB from 2007 to 2010, with International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) TBI codes. There were no interventions. Severity indices used were the Emergency Department Glasgow Coma Scale (GCS) Total score and each of the subscales for eye opening (four levels), verbal response (five levels), and motor response (six levels); the worst Abbreviated Injury Scale (AIS) severity score for the head (six levels); and the worst Barell index type (three categories). Prediction models were computed for acute care length of stay (days), intensive care unit length of stay (days), hospital discharge status (alive or dead), and, if alive, discharge disposition (home versus institutional). Multiple correspondence analysis (MCA) indicated a two dimensional relationship among items of severity indexes. The primary dimension reflected overall injury severity. The second dimension seemed to capture volitional behavior without the capability for cogent responding. Together, they defined two vectors around which most of the items clustered. A scale that took advantage of the order of items along these vectors proved to be the most consistent index for predicting short-term health outcomes. MCA provided useful insight into the relationships among components of traditional TBI severity indices. The two vector pattern may reflect the impact of injury on different cortical and subcortical networks. Results are discussed in terms of score substitution and the ability to impute missing values.

Longitudinal Description of the Disability Rating Scale for Individuals in the National Institute on Disability and Rehabilitation Research Traumatic Brain Injury Model Systems National Database

OBJECTIVE To develop a detailed understanding of temporal change (ie, estimated trajectories) at the individual level as measured by the Disability Rating Scale (DRS). DESIGN Individual growth curve (IGC) analysis of retrospective data obtained from the National Institute on Disability and Rehabilitation Research Traumatic Brain Injury (TBI) Model Systems National Database. SETTING Multicenter longitudinal database study. PARTICIPANTS Individuals with TBI (N=8816) participating in the TBI Model Systems National Database project. INTERVENTIONS Not applicable. MAIN OUTCOME MEASURE DRS RESULTS The negative exponential consisting of 3 growth parameters (pseudointercept, asymptote, rate) was successfully used to predict trajectory of recovery on the DRS qualified by the following covariates: race, sex, level of education and age at admission, rehabilitation length of stay, and cognitive and motor FIM scores at rehabilitation admission. Based on these results, an interactive tool was developed to allow prediction of the trajectory of recovery for individuals and subgroups with specified characteristics on the selected covariates. CONCLUSIONS With the use of IGC analysis, the longitudinal trajectory of recovery on the DRS for individuals sharing common characteristics and traits can be described. This methodology allows researchers and clinicians to predict numerous individual-level trajectories through use of a web-based computer automated interactive tool.