• Zahra Rahmatinejad, Hamidreza Reihani, Fariba Tohidinezhad, Fatemeh Rahmatinejad, Samira Peyravi, Ali Pourmand, Ameen Abu-Hanna, and Saeid Eslami.
• Student Research Committee, Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
• Am J Emerg Med. 2019 Jul 1; 37 (7): 1237-1241.

BackgroundThe Sequential Organ Failure Assessment (SOFA) and modified SOFA (mSOFA) are risk stratification systems which incorporate respiratory, coagulatory, liver, cardiovascular, renal, and neurologic systems to quantify the overall severity of acute disorder in the intensive care unit.ObjectiveTo evaluate the prognostic performance of the SOFA and mSOFA scores at arrival for predicting in-hospital mortality in the emergency department (ED).MethodsAll adult patients with an Emergency Severity Index (ESI) of 1-3 in the ED of Imam Reza Hospital, northeast of Iran were included from March 2016 to March 2017. The predictive performance of the SOFA or mSOFA scores were expressed in terms of accuracy (Brier Score, BS and Brier Skill Score, BSS), discrimination (Area Under the Receiver Operating Characteristic Curve, AUC), and calibration.ResultsA total of 2205 patients (mean age 61.8 ± 18.5 years, 53% male) were included. The overall in-hospital mortality was 19%. For SOFA and mSOFA the BS was 0.209 and 0.192 and the BSS was 0.11 and 0.09, respectively. The estimated AUCs of SOFA and mSOFA models were 0.751 and 0.739, respectively. No significant difference was observed between the AUCs (P = 0.186). The Hosmer-Lemeshow test did not show that the predictions deviated from the true probabilities. Also, the calibration plots revealed good agreement between the actual and predicted probabilities.ConclusionThe SOFA and mSOFA scores demonstrated fair discrimination and good calibration in predicting in-hospital mortality when applied to ED. However, further external validation studies are needed before their use in routine clinical care.Copyright © 2018 Elsevier Inc. All rights reserved.

21 keywords...

hide…