Divergent Six Month Functional Recovery Trajectories and Predictors after Traumatic Brain Injury: Novel Insights from the Citicoline Brain Injury Treatment Trial Study

Abstract

Cross-sectional approaches to outcome assessment may not adequately capture heterogeneity in recovery after traumatic brain injury (TBI). Using latent class mixed models (LCMM), a data-driven analytic that identifies groups of patients with similar trajectories, we identified distinct 6 month functional recovery trajectories in a large cohort (n = 1046) of adults 18-70 years of age with complicated mild to severe TBI who participated in the Citicoline Brain Injury Treatment Trial (COBRIT). We used multinomial logistic fixed effect models and backward elimination, forward selection, and forward stepwise selection with several stopping rules to explore baseline predictors of functional recovery trajectory. Based on statistical and clinical considerations, the seven-class model was deemed superior. Visualization of these seven functional recovery trajectories revealed that each trajectory class started at one of three recovery levels at 1 month, which, for ease of reference we labeled groups A-C: Group A, good recovery (two classes; A1 and A2); Group B, moderate disability (two classes; B1 and B2); and Group C, severe disability (three classes; C1, C2, and C3). By 6 months, these three groups experienced dramatically divergent trajectories. Group A experienced stable good recovery (A1, n = 115) or dramatic decline (A2, n = 4); Group B experienced rapid complete recovery (B1, n = 71) or gradual recovery (B2, n = 742); Group C experienced dramatic rapid recovery (C1, n = 12), no recovery (C2, n = 91), or death (C3, n = 11). Trajectory class membership was not predicted by citicoline treatment (p = 0.57). The models identified demographic, pre-injury, and injury-related predictors of functional recovery trajectory, including: age, race, education, pre-injury employment, pre-injury diabetes, pre-injury psychiatric disorder, site, Glasgow Coma Scale (GCS) score, post-traumatic amnesia, TBI mechanism, major extracranial injury, hemoglobin, and acute computed tomographic (CT) findings. GCS was the most consistently selected predictor across all models. All models also selected at least one demographic or pre-injury medical predictor. LCMM successfully identified dramatically divergent, clinically meaningful 6 month recovery trajectories with utility to inform clinical trial design.

Keywords: TBI; functional outcome; predictors; trajectory.

FIG. 1.

Functional trajectories. (A) Mean Glasgow Outcome Scale Extended (GOSE) is shown at each time point for all patients assigned to each trajectory class. Dot size represents log count of sample size at each time point, with larger dots representing larger sample size. At 1 month post-injury, the top two (Group A: red and orange), middle two (Group B: khaki and green), and lower three (Group C: pink, teal, and purple) classes all start at similar levels of recovery or disability, but then experience dramatically divergent recovery trajectories by 6 months. (B) Randomly selected raw GOSE data are plotted for up to 16 patients in each trajectory class. Because these are raw GOSE data, all GOSE values are whole numbers ranging from 1 to 8. However, slight random jitter in GOSE (and color) was introduced to improve visualization of each individual trajectory. For example, all patients in B1 actually achieved complete recovery (GOSE = 8) by 6 months.