Norwegian survival prediction model in trauma: modelling effects of anatomic injury, acute physiology, age, and co-morbidity

Abstract

Introduction

Anatomic injury, physiological derangement, age, and injury mechanism are well-founded predictors of trauma outcome. We aimed to develop and validate the first Scandinavian survival prediction model for trauma.

Methods

Eligible were patients admitted to Oslo University Hospital Ullevål within 24 h after injury with Injury Severity Score ≥ 10, proximal penetrating injuries or received by a trauma team. The derivation dataset comprised 5363 patients (August 2000 to July 2006); the validation dataset comprised 2517 patients (August 2006 to July 2008). Exclusion because of missing data was < 1%. Outcome was 30-day mortality. Logistic regression analysis incorporated fractional polynomial modelling and interaction effects. Model validation included a calibration plot, Hosmer–Lemeshow test and receiver operating characteristic (ROC) curves.

Results

The new survival prediction model included the anatomic New Injury Severity Score (NISS), Triage Revised Trauma Score (T-RTS, comprising Glascow Coma Scale score, respiratory rate, and systolic blood pressure), age, pre-injury co-morbidity scored according to the American Society of Anesthesiologists Physical Status Classification System (ASA-PS), and an interaction term. Fractional polynomial analysis supported treating NISS and T-RTS as linear functions and age as cubic. Model discrimination between survivors and non-survivors was excellent. Area (95% confidence interval) under the ROC curve was 0.966 (0.959–0.972) in the derivation and 0.946 (0.930–0.962) in the validation dataset. Overall, low mortality and skewed survival probability distribution invalidated model calibration using the Hosmer–Lemeshow test.

Conclusions

The Norwegian survival prediction model in trauma (NORMIT) is a promising alternative to existing prediction models. External validation of the model in other trauma populations is warranted.