Predicting outcome in traumatic brain injury: Sharing experience of pilot traumatic brain injury registry

BACKGROUND A reliable prediction of outcome for the victims of traumatic brain injury (TBI) on admission is possible from concurrent data analysis from any systematic real-time registry. OBJECTIVE To determine the clinical relevance of the findings from our TBI registry to develop prognostic futuristic models with readily available traditional and novel predictors. MATERIALS AND METHODS Prospectively collected data using predesigned pro forma were analyzed from the first phase of a trauma registry from a South Indian Trauma Centre, compatible with computerized management system at electronic data entry and web data entry interface on demographics, clinical, management, and discharge status. STATISTICAL ANALYSIS On univariate analysis, the variables with P < 0.15 were chosen for binary logistic model. On regression model, variables were selected with test of coefficient 0.001 and with Nagelkerke R2 with alpha error of 5%. RESULTS From 337 cases, predominantly males from rural areas in their productive age, road traffic injuries accounted for two-thirds cases, one-fourths occurred during postmonsoon while two-wheeler was the most common prerequisite. Fifty percent of patients had moderate to severe brain injury; the most common finding was unconsciousness followed by vomiting, ear bleed, seizures, and traumatic amnesia. Fifteen percent required intracranial surgery. Patients with severe Glasgow coma scale score were 4.5 times likely to have the fatal outcome (P = 0.003). Other important clinical variables accountable for fatal outcomes were oral bleeds and cervical spine injury while imperative socio-demographic risk correlates were age and seasons. CONCLUSION TBI registry helped us finding predictors of clinical relevance for the outcomes in victims of TBI in search of prognostic futuristic models in TBI victims.