Predicting outcome in severe traumatic brain injury using a simple prognostic model

Abstract

Background. Several studies have made it possible to predict outcome in severe traumatic brain injury (TBI) making it beneficial as an aid for clinical decision-making in the emergency setting. However, reliable predictive models are lacking for resource-limited prehospital settings such as those in developing countries like South Africa. Objective. To develop a simple predictive model for severe TBI using clinical variables in a South African prehospital setting. Methods. All consecutive patients admitted at two level-one centres in Cape Town, South Africa, for severe TBI were included. A binary logistic regression model was used, which included three predictor variables: oxygen saturation (SpO2), Glasgow Coma Scale (GCS) and pupil reactivity. The Glasgow Outcome Scale was used to assess outcome on hospital discharge. Results. A total of 74.4% of the outcomes were correctly predicted by the logistic regression model. The model demonstrated SpO2 (p=0.019), GCS (p=0.001) and pupil reactivity (p=0.002) as independently significant predictors of outcome in severe TBI. Odds ratios of a good outcome were 3.148 (SpO2 ≥90%), 5.108 (GCS 6 - 8) and 4.405 (pupils bilaterally reactive). Conclusion. This model is potentially useful for effective predictions of outcome in severe TBI.