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      Rapid Acute Physiology Score versus Rapid Emergency Medicine Score in Trauma Outcome Prediction; a Comparative Study

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          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 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.

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          Most cited references23

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          Rapid Emergency Medicine score: a new prognostic tool for in-hospital mortality in nonsurgical emergency department patients.

          To evaluate the predictive accuracy of the scoring system Rapid Acute Physiology score (RAPS) in nonsurgical patients attending the emergency department (ED) regarding in-hospital mortality and length of stay in hospital (LOS), and to investigate whether the predictive ability of RAPS could be improved by extending the system. Prospective cohort study. An adult ED of a 1200-bed university hospital. A total of 12 006 nonsurgical patients presenting to the ED during 12 consecutive months. For all entries to the ED, RAPS (including blood pressure, respiratory rate, pulse rate and Glasgow coma scale) was calculated. The RAPS system was extended by including the peripheral oxygen saturation and patient age (Rapid Emergency Medicine score, REMS) and this new score was calculated for each patient. The statistical associations between the two scoring systems and in-hospital mortality as well as LOS in hospital were examined. The REMS was superior to RAPS in predicting in-hospital mortality [area under receiver operating characteristic (ROC) curve 0.852 +/- 0.014 SEM for REMS compared with 0.652 +/- 0.019 for RAPS, P < 0.05]. An increase of 1-point in the 26-point REMS scale was associated with an OR of 1.40 for in-hospital death (95% CI: 1.36-1.45, P < 0.0001). Similar results were obtained in the major patient groups (chest pain, stroke, coma, dyspnoea and diabetes), in all age groups and in both sexes. The association between REMS and LOS was modest (r = 0.47, P = 0.0001). The REMS was a powerful predictor of in-hospital mortality in patients attending the ED over a wide range of common nonsurgical disorders.
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            Comparison of the rapid emergency medicine score and APACHE II in nonsurgical emergency department patients.

            To improve the Rapid Acute Physiology Score (RAPS) as a predictor of in-hospital mortality in the nonsurgical emergency department (ED) by including age and oxygen saturation, and to compare this new system, Rapid Emergency Medicine Score (REMS), with the Acute Physiology and Chronic Health Examination (APACHE II) with reference to predictive accuracy. This was a prospective cohort study. One hundred sixty-two critically ill patients consecutively admitted to the intensive care unit (ICU) during the period of one year, and 865 nonsurgical patients presenting to an adult emergency department (ED) and admitted to a medical department of a 1200-bed university hospital during two months, were enrolled. For all entries to the ED, RAPS was calculated and developed to include noninvasive peripheral oxygen saturation and patient age (REMS), as well as laboratory tests (APACHE II). These scores were calculated for each patient. REMS was found to be superior to RAPS in predicting in-hospital mortality both in the critically ill patients admitted to the ICU and in the total sample (area under receiver-operating characteristic curve [AUC] 0.910 +/- 0.015 for REMS compared with 0.872 +/- 0.022 for RAPS, p < 0.001). An increase of 1 point in the 26-point REMS scale was associated with an odds ratio of 1.40 for in-hospital death (95% confidence interval = 1.36 to 1.45, p < 0.0001). The more advanced APACHE II was not found to be superior to REMS (AUC: 0.901 +/- 0.015, p = 0.218). RAPS could be improved as a predictor of in-hospital mortality in the nonsurgical ED by including oxygen saturation and patient age to the system. This new scoring system, REMS, had the same predictive accuracy as the well-established, but more complicated, APACHE II.
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              From the Help Desk: Comparing Areas under Receiver Operating Characteristic Curves from Two or more Probit or Logit Models

              Occasionally, there is a need to compare the predictive accuracy of several fitted logit (logistic) or probit models by comparing the areas under the corresponding receiver operating characteristic (ROC) curves. Although Stata currently does not have a ready routine for comparing two or more ROC areas generated from these models, this article describes how these comparisons can be performed using Stata's roccomp command.
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                Author and article information

                Journal
                Emerg (Tehran)
                Emerg (Tehran)
                Emerg
                Emergency
                Shahid Beheshti University of Medical Sciences (Tehran, Iran )
                2345-4563
                2345-4571
                2017
                10 January 2017
                : 5
                : 1
                : e30
                Affiliations
                [1 ]Sina Trauma and Surgery Research Center, Tehran University of Medical Sciences, Tehran, Iran.
                [2 ]Department of Medicine, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
                [3 ]Physiology Research Center and Department of Physiology, Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran.
                [4 ]Department of Emergency Medicine, Jahrom University of Medical Sciences, Jahrom, Iran.
                [5 ]Department of Community Nutrition, Faculty of Nutrition and Food Technology, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
                [6 ]Department of Emergency Medicine, Maragheh University of Medical Sciences, Maragheh, Iran.
                [7 ]Emergency Medicine Research Team, Tabriz University of Medical Sciences, Tabriz, Iran.
                [8 ]Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
                Author notes
                [* ]Corresponding author: Mostafa Hosseini, Department of Epidemiology and Biostatistics School of Public Health, Tehran University of Medical Sciences, Poursina Ave, Tehran, Iran; Email: mhossein110@yahoo.com; Tel: +982188989125; Fax: +982188989127
                Article
                emerg-5-e30
                5325900
                28286837
                e50eca57-dc8e-40ba-8612-44463bec250a
                © Copyright (2017) Shahid Beheshti University of Medical Sciences

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License, ( http://creativecommons.org/licenses/by/3.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : November 2016
                : November 2016
                Categories
                Original Research

                multiple trauma,trauma severity indices,decision support techniques,prognosis,patient outcome assessment

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