Prognostic Value of Clinical Variables in Moderate and Severe Head Injury

Abstract

Introduction: Craniocerebral injury is a leading cause of mortality and morbidity among predominantly young population. Outcome prediction after head injury can be useful as an aid to clinical decision making, to explore possible pathological mechanisms and as part of the clinical audit process. Many studies have constructed predictive models for survival after traumatic brain injury, but these have often used expensive, time consuming or highly specialized measurements. The aim of this study was to develop a simple, yet easy to use, model involving only variables which are rapidly and easily clinically achievable in routine practice. Patients and methods: All consecutive patients older than 14 years with moderate or severe isolated head injury admitted to our department in period between 01.01.2007. and 30.06.2008. were enrolled in the study. Basic demographic and clinical data (Glasgow coma score, pupil size and reactivity, revised trauma score) were recorded. Outcome at 1 and 3 months after injury graded by GOS was used to construct a simple predictive model. Results: We analyzed records 82 patients with moderate or severe head injury according to GCS. Multiple logistic regression resulted in a model containing age (p=0.0001 ), GCS (p < 0.0001), systolic blood pressure of the RTS (p < 0.0001; t=7.388) and pupil reactivity (p < 0.0001; t=-5.605) at admission as fair independent outcome predictors, with motor component of the GCS scale exhibiting greater predictive value over the entire GCS score (p < 0.0001; t=5.732). Conclusion: All four variables have previously been shown to be related to survival. All variables in the model are clinically simple and easy to measure rapidly resulting in a model that is clinically useful.