Observational studyEuropean journal of trauma and emergency surgery : official publication of the European Trauma Society2026
Mortality prediction in older adults with earthquake-related trauma: a model combining MEWS and laboratory biomarkers.
Observational study in European journal of trauma and emergency surgery : official publication of the European Trauma Society, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeThis study aimed to identify laboratory parameters and clinical scores that can predict in-hospital mortality among patients aged 65 years and older who presented to the emergency department (ED) with earthquake-related trauma following the February 6 and 20, 2023 earthquakes.
methodsIn this retrospective observational study, 362 patients with earthquake-related trauma between February 6-21, 2023, were included. Demographic characteristics, laboratory results, and clinical scores such as the Modified Early Warning Score (MEWS), Injury Severity Score (ISS), and Shock Index (SI) were analyzed.
resultsOf the included patients, 53.9% (n = 195) were female, and the median age was 73 years (IQR: 69-80). The overall mortality rate was 9.4%. Multivariable logistic regression analysis identified MEWS (OR: 3.535; 95% CI: 2.397-5.212; p < 0.001), urea (OR: 1.009; 95% CI: 1.002-1.015; p = 0.008), and hs-Troponin I (OR: 1.001; 95% CI: 1.000-1.002; p = 0.016) as independent predictors of mortality. Receiver operating characteristic (ROC) analysis demonstrated an AUC of 0.936 for the combined model including MEWS, urea, and hs-Troponin I (95% CI: 0.875-0.996; p < 0.001). Among the variables, MEWS showed the highest AUC (0.903; 95% CI: 0.829-0.976). The optimal cutoff value for MEWS was determined as 1.5, with a sensitivity of 70.6% and a specificity of 97.6%.
conclusionsIn older adults with earthquake-related trauma, integrating laboratory parameters-particularly urea and hs-Troponin I-with MEWS substantially improves mortality prediction. These findings underscore the importance of early laboratory-based evaluation for accurate risk stratification in disaster settings.
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