Several studies have characterized comorbidities among individuals with traumatic brain injury (TBI); however, there are few validated TBI comorbidity indices. Widely used indices (e.g., Elixhauser Comorbidity Index [ECI]) were developed in other patient populations and anchor to mortality or healthcare utilization, not functioning, and notably exclude conditions known to co-occur with TBI. The objectives of this study were to develop and validate a functionally relevant TBI comorbidity index (Fx-TBI-CI) and to compare prognostication of the Fx-TBI-CI with the ECI. We used data from the eRehabData database to divide the sample randomly into a training sample (N = 21,292) and an internal validation sample (N = 9166). We used data from the TBI Model Systems National Database as an external validation sample (N = 1925). We used least absolute shrinkage and selection operator (LASSO) regression to narrow the list of functionally relevant conditions from 39 to 12. In internal validation, the Fx-TBI-CI explained 14.1% incremental variance over an age and sex model predicting the Functional Independence Measure (FIM) Motor subscale at inpatient rehabilitation discharge, compared with 2.4% explained by the ECI. In external validation, the Fx-TBI-CI explained 4.9% incremental variance over age and sex and 3.8% over age, sex, and Glasgow Coma Scale score,compared with 2.1% and 1.6% incremental variance, respectively, explained by the ECI. An unweighted Sum Condition Score including the same conditions as the Fx-TBI-CI conferred similar prognostication. Although the Fx-TBI-CI had only modest incremental variance over demographics and injury severity in predicting functioning in external validation, the Fx-TBI-CI outperformed the ECI in predicting post-TBI function.
Keywords: comorbidities; functioning; prognostication; traumatic brain injury.