Title of article :
Rapid Acute Physiology Score versus Rapid Emergency Medicine Score in Trauma Outcome Prediction; a Comparative Study
Author/Authors :
Nakhjavan-Shahraki ، Babak - Tehran University of Medical Sciences , Baikpour ، Masoud - Tehran University of Medical Sciences , Yousefifard ، Mahmoud - Iran University of Medical Sciences , Nikseresht ، Zahra Sadat - Tehran University of Medical Sciences , Abiri ، Samaneh - Jahrom University of Medical Sciences , Mirzay Razaz ، Jalaledin - Shahid Beheshti University of Medical Sciences , Faridaalaee ، Gholamreza - Maragheh University of Medical Sciences , Pouraghae ، Mahboob - Tabriz University of Medical Sciences , Shirzadegan ، Sahar - Tabriz University of Medical Sciences , Hosseini ، Mostafa - Tehran University of Medical Sciences
Abstract :
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 cross-sectional study, the two models of RAPS and REMS were compared regarding prediction of mor- tality and poor outcome (severe disability) of trauma patients presenting to the EDs of 5 educational hospitals. 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 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.
Keywords :
Multiple trauma , trauma severity indices , decision support techniques , prognosis , patient outcome assessment
Journal title :
Emergency
Journal title :
Emergency