A comparison of the Full Outline of UnResponsiveness (FOUR) score and Glasgow Coma Score (GCS) in predictive modelling in traumatic brain injury
Abstract Objectives: To compare the performance of multivariate predictive models incorporating either the Full Outline of UnResponsiveness (FOUR) score or Glasgow Coma Score (GCS) in order to test whether substituting GCS with the FOUR score in predictive models for outcome in patients after TBI is beneficial. Material and methods: A total of 162 TBI patients were prospectively enrolled in the study. Stepwise logistic regression analysis was conducted to compare the prediction of (1) in ICU mortality and (2) unfavourable outcome at 3 months post injury using as predictors either the FOUR score or GCS along with other factors that may affect patient outcome. The areas under the ROC curves (AUCs) were used to compare the discriminant ability and predictive power of the models. The internal validation was performed with bootstrap technique and expressed as accuracy rate (AcR) Results: The FOUR score, age, the CT Rotterdam score, systolic ABP and being placed on ventilator within day one (model 1: AUC: 0.906 0.024; AcR: 80.3 4.8% performed equally well in predicting in ICU mortality as the combination of GCS with the same set of predictors plus pupil reactivity (model 2: AUC: 0.913 0.022; AcR: 81.1 4.8% The CT Rotterdam score, age and either the FOUR score (model 3) or GCS (model 4) equally well predicted unfavourable outcome at 3 months post injury (AUC: 0.852 0.037 vs. 0.866 0.034; AcR: 72.3 6.6% vs. 71.9% 6.6% respectively) Adding the FOUR score or GCS at discharge from ICU to predictive models for unfavourable outcome increased significantly their performances (AUC: 0.895 0.029, p 0.05; AcR: 76.1 6.5% p 0.004 when compared with model 3; and AUC: 0.918 0.025, p 0.05; AcR: 79.6 7.2% p 0.009 when compared with model 4) but there was no benefit from substituting GCS with the FOUR score. Conclusion: Results showed that FOUR score and GCS perform equally well in multivariate predictive modelling in TBI.
British journal of neurosurgery