PREDICTING MORTALITY IN AMBULANCE-TRANSPORTED EMERGENCY DEPARTMENT PATIENTS: A COMPARATIVE RETROSPECTIVE COHORT STUDY

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Introduction: Accurate and timely triage in emergency departments facilitates the identification of critically ill patients, thereby improving the quality of care and promoting the efficient use of healthcare resources. In this study, we aimed to assess the utility of selected scoring systems calculated using prehospital data obtained in the ambulance setting, with a focus on their applicability before hospital arrival. Methods: This retrospective cohort study was conducted at a single center and included 1,676 patients who were brought to the emergency department via ambulance over the course of June 2024. For each patient, the Rapid Emergency Medicine Score (REMS), Rapid Acute Physiology Score (RAPS), Shock Index (SI), and the revised Shock Index multiplied by the Glasgow Coma Scale (rSIGCS) were calculated. To evaluate the predictive accuracy of each scoring system, receiver operating characteristic (ROC) curve analysis was employed. Additionally, multivariable logistic regression analysis was conducted to determine independent risk factors associated with mortality. Results: The REMS demonstrated the highest discriminatory power for predicting 24-hour mortality, with c-statistics value of 0.897 (95% CI: 0.881–0.911). The rSIGCS also showed good performance, with c-statistics value of 0.843 (95% CI: 0.824–0.860). No statistically significant difference was observed between REMS and rSIGCS (p = 0.2166, DeLong test), suggesting that both scoring systems may serve as effective tools for early mortality prediction in the prehospital setting. Conclusion: This study found that both REMS and rSIGCS are effective tools for predicting early mortality among non-trauma patients transported to the emergency department by ambulance.

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