Characterizing Profiles of TBI Severity: Predictors of Functional Outcomes and Well-Being.

ABSTRACT

OBJECTIVE: To identify profiles of acute traumatic brain injury (TBI) severity and relate profiles to functional and well-being outcomes. SETTING: Acute inpatient rehabilitation and general community settings. PARTICIPANTS: Three hundred and seventy-nine individuals with moderate-severe TBI participating in the Traumatic Brain Injury Model Systems. DESIGN: Longitudinal observational study. MAIN MEASURES: At discharge-length of stay, Functional Independence Measure (FIM), and Disability Rating Scale (DRS). One-year post-injury-Glasgow Outcome Scale-Extended (GOS-E), FIM, and Satisfaction with Life Scale (SWLS). RESULTS: Latent profile analysis (LPA) was used to identify subgroups with similar patterns across 12 indicators of acute injury severity, including duration of posttraumatic amnesia, Glasgow Coma Scale, time to follow commands, and head CT variables. LPA identified 4 latent classes, least to most severe TBI (Class 1 n = 75, 20.3%; Class 2 n = 124, 33.5%; Class 3 n = 144, 38.9%; Class 4 n = 27, 7.3%); younger age, lower education, rural residence, injury in motor vehicle accidents, and earlier injury years were associated with worse acute severity. Latent classes were related to outcomes. Compared with Class 1, hospital stays were longer, FIM scores lower, and DRS scores larger at discharge among individuals in Class 3 and Class 4 (all P s < .01). One-year post-injury, GOS-E and FIM scores were significantly lower among individuals in Class 3 and Class 4 than those in Class 1 ( P s < .01). SWLS scores were lower only among individuals in Class 3 ( P = .036) compared with Class 1; other comparisons relative to Class 1 were not significant. CONCLUSIONS: Meaningful profiles of TBI severity can be identified from acute injury characteristics and may suggest etiologies, like injury in motor vehicle accidents, and premorbid characteristics, including younger age, rural residence, and lower education, that heighten risk for worse injuries. Improving classification may help focus on those at elevated risk for severe injury and inform clinical management and prognosis.