The exponential function transforms the Abbreviated Injury Scale, which both improves accuracy and simplifies scoring

Abstract

Purpose: We present here the exponential function which transforms the Abbreviated Injury Scale (AIS). It is called the Exponential Injury Severity Score (EISS), and significantly outperforms the venerable but dated New Injury Severity Score (NISS) and Injury Severity Score (ISS) as a predictor of mortality.

Methods: The EISS is defined as a change of AIS values by raising each AIS severity score (1-6) by 3 taking a power of AIS minus 2 and then summing the three most severe injuries (i.e., highest AIS), regardless of body regions. EISS values were calculated for every patient in two large independent data sets: 3,911 and 4,129 patients treated during a 6-year period at the Class A tertiary hospitals in China. The power of the EISS to predict mortality was then compared with previously calculated NISS values for the same patients in each of the two data sets.

Results: We found that the EISS is more predictive of survival [Zhejiang: area under the receiver operating characteristic curve (AUC): NISS = 0.932, EISS = 0.949, P = 0.0115; Liaoning: AUC: NISS = 0.924, EISS = 0.942, P = 0.0139]. Moreover, the EISS provides a better fit throughout its entire range of prediction (Hosmer-Lemeshow statistic for Zhejiang: NISS = 21.86, P = 0.0027, EISS = 13.52, P = 0.0604; Liaoning: NISS = 23.27, P = 0.0015, EISS = 15.55, P = 0.0164).

Conclusions: The EISS may be used as the standard summary measure of human trauma.

Keywords: Abbreviated Injury Scale; Exponential Injury Severity Score; Injury Severity Score; New Injury Severity Score; Prediction of mortality.