Performance of injury severity measures in trauma research: a literature review and validation analysis of studies from low-income and middle-income countries.

introductionCharacterisation of injury severity is an important pillar of scientific research to measure and compare the outcomes. Although majority of injury severity measures were developed in high-income countries, many have been studied in low-income and middle-income countries (LMICs). We conducted this study to identify and characterise all injury severity measures, describe how widely and frequently they are used in trauma research from LMICs, and summarise the evidence on their performance based on empirical and theoretical validation​ analysis.

methodsFirst, a list of injury measures was identified through PubMed search. Subsequently, a systematic search of PubMed, Global Health and EMBASE was undertaken on LMIC trauma literature published from January 2006 to June 2016, in order to assess the application and performance of injury severity measures to predict in-hospital mortality. Studies that applied one or more global injury severity measure(s) on all types of injuries were included, with the exception of war injuries and isolated organ injuries.

resultsOver a span of 40 years, more than 55 injury severity measures were developed. Out of 3862 non-duplicate citations, 597 studies from 54 LMICs were listed as eligible studies. Full-text review revealed 37 studies describing performance of injury severity measures for outcome prediction. Twenty-five articles from 13 LMICs assessed the validity of at least one injury severity measure for in-hospital mortality. Injury severity score was the most commonly validated measure in LMICs, with a wide range of performance (area under the receiver operating characteristic curve (AUROC) between 0.9 and 0.65). Trauma and Injury Severity Score validation studies reported AUROC between 0.80 and 0.98.

conclusionEmpirical studies from LMICs frequently use injury severity measures, however, no single injury severity measure has shown a consistent result in all settings or populations and thus warrants validation studies for the diversity of LMIC population.