Rapid Acute Physiology Score versus Rapid Emergency Medicine Score in Trauma Outcome Prediction; a Comparative Study - Nakhjavan-Shahraki, Babak; Baikpour, Masoud; Yousefifard, Mahmoud; Nikseresht, Zahra Sadat; Abiri, Samaneh; Mirzay Razaz, Jalaledin; Faridaalaee, Gholamreza; Pouraghae, Mahboob; Shirzadegan, Sahar; Hosseini, Mostafa (Archives of Academic Emergency Medicine, 2017)
Introduction: Rapid acute physiology score (RAPS) and rapid emergency medicine score (REMS) are two physiologic models for measuring injury severity in emergency settings. The present study was designed to compare the two models in outcome prediction of trauma patients presenting to emergency department (ED). Methods: In this prospective cross-sectional study, the two models of RAPS and REMS were compared regarding prediction of mortality and poor outcome (severe disability based on Glasgow outcome scale) of trauma patients presenting to the EDs of 5 educational hospitals in Iran (Tehran, Tabriz, Urmia, Jahrom and Ilam) from May to October 2016. The discriminatory power and calibration of the models were calculated and compared using STATA 11. Results: 2148 patients with the mean age of 39.50±17.27 years were studied (75.56% males). The area under the curve of REMS and RAPS in predicting in-hospital mortality were calculated to be 0.93 (95% CI: 0.92-0.95) and 0.899 (95% CI: 0.86-0.93), respectively (p=0.02). These measures were 0.92 (95% CI: 0.90-0.94) and 0.86 (95% CI: 0.83-0.90), respectively, regarding poor outcome (p=0.001). The optimum cut-off point in predicting outcome was found to be 3 for REMS model and 2 for RAPS model. The sensitivity and specificity of REMS and RAPS in the mentioned cut offs were 95.93 vs. 85.37 and 77.63 vs. 83.51, respectively, in predicting mortality. Calibration and overall performance of the two models were acceptable. Conclusion: The present study showed that adding age and level of arterial oxygen saturation to the variables included in RAPS model can increase its predictive value. Therefore, it seems that REMS could be used for predicting mortality and poor outcome of trauma patients in emergency settings