Prediction of outcomes after injury has traditionally incorporated measures of injury severity, but recent studies suggest that including physiologic and shock measures can improve accuracy of anatomic-based models. A recent single-institution study described a mortality predictive equation [f(x) = 3.48 − .22 (GCS) − .08 (BE) + .08 (Tx) + .05 (ISS) + .04 (Age)], where GSC is Glasgow Coma Score, BE is base excess, Tx is transfusion requirement, and ISS is Injury Severity Score, which had 63% sensitivity, 94% specificity, (receiver operating characteristic [ROC] 0.96), but did not provide comparative data for other models. We have previously documented that the Physiologic Trauma Score, including only physiologic variables (systemic inflammatory response syndrome, Glasgow Coma Score, age) also accurately predicts mortality in trauma. The objective of this study was to compare the predictive abilities of these statistical models in trauma outcomes.

Area under the ROC curve of sensitivity versus 1-specificity was used to assess predictive ability and measured discrimination of the models.

The study cohort consisted of 15,534 trauma patients (80% blunt mechanism) admitted to a Level I trauma center over a 3-year period (mean age 37 ± 18 years; mean Injury Severity Score 10 ± 10; mortality 4%). Sensitivity of the new predictive model was 45%, specificity was 96%, ROC was 0.91, validating this new trauma outcomes model in our institution. This was comparable with area under the ROC for Revised Trauma Score (ROC 0.88), Trauma and Injury Severity Score (ROC 0.97), and Physiologic Trauma Score (ROC 0.95), but superior compared with admission Glasgow Coma Score (ROC 0.79), Injury Severity Score (ROC 0.79), and age (ROC 0.60).

The predictive ability of this new model is superior to anatomic-based models such as Injury Severity Score, but comparable with other physiologic-based models such as Revised Trauma Score, Physiologic Trauma Score and Trauma, and Injury Severity Score.