Abstract

IntroductionThe TraumaRegister DGU™ (TR-DGU) has used the Revised Injury Severity Classification (RISC) score for outcome adjustment since 2003. In recent years, however, the observed mortality rate has fallen to about 2% below the prognosis, and it was felt that further prognostic factors, like pupil size and reaction, should be included as well. Finally, an increasing number of cases did not receive a RISC prognosis due to the missing values. Therefore, there was a need for an updated model for risk of death prediction in severely injured patients to be developed and validated using the most recent data.MethodsThe TR-DGU has been collecting data from severely injured patients since 1993. All injuries are coded according to the Abbreviated Injury Scale (AIS, version 2008). Severely injured patients from Europe (ISS ≥4) documented between 2010 and 2011 were selected for developing the new score (n = 30,866), and 21,918 patients from 2012 were used for validation. Age and injury codes were required, and transferred patients were excluded. Logistic regression analysis was applied with hospital mortality as the dependent variable. Results were evaluated in terms of discrimination (area under the receiver operating characteristic curve, AUC), precision (observed versus predicted mortality), and calibration (Hosmer-Lemeshow goodness-of-fit statistic).ResultsThe mean age of the development population was 47.3 years; 71.6% were males, and the average ISS was 19.3 points. Hospital mortality rate was 11.5% in this group. The new RISC II model consists of the following predictors: worst and second-worst injury (AIS severity level), head injury, age, sex, pupil reactivity and size, pre-injury health status, blood pressure, acidosis (base deficit), coagulation, haemoglobin, and cardiopulmonary resuscitation. Missing values are included as a separate category for every variable. In the development and the validation dataset, the new RISC II outperformed the original RISC score, for example AUC in the development dataset 0.953 versus 0.939.ConclusionsThe updated RISC II prognostic score has several advantages over the previous RISC model. Discrimination, precision and calibration are improved, and patients with partial missing values could now be included. Results were confirmed in a validation dataset.

Highlights

  • The TraumaRegister DGUTM (TR-German Trauma Society (DGU)) has used the Revised Injury Severity Classification (RISC) score for outcome adjustment since 2003

  • The new RISC Injury Severity Classification (II) model consists of the following predictors: worst and second-worst injury (AIS severity level), head injury, age, sex, pupil reactivity and size, pre-injury health status, blood pressure, acidosis, coagulation, haemoglobin, and cardiopulmonary resuscitation

  • A valid estimation of baseline risk allows interpretation of observed mortality rates. This is underlined by a statement from Susan Baker, who published the Injury Severity Score (ISS): ‘If you have never felt the need for any type of severity scoring system, you probably have never had to explain how it is that survival rate of 85% in your trauma center is better than the survival rate of 97% in some other hospital where the patients are much less seriously injured’ [1]

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Summary

Introduction

The TraumaRegister DGUTM (TR-DGU) has used the Revised Injury Severity Classification (RISC) score for outcome adjustment since 2003. Severe trauma has serious consequences for the victims with a still considerable mortality rate and often longlasting physical and mental problems for the survivors. A valid estimation of baseline risk allows interpretation of observed mortality rates. This is underlined by a statement from Susan Baker, who published the Injury Severity Score (ISS): ‘If you have never felt the need for any type of severity scoring system, you probably have never had to explain how it is that survival rate of 85% in your trauma center is better than the survival rate of 97% in some other hospital where the patients are much less seriously injured’ [1]

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