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Physiologic Scoring Systems in Predicting the Covid-19 Patients’ One-Month Mortality; a Prognostic Accuracy Study Publisher



Heydari F1 ; Zamani M1 ; Masoumi B1 ; Majidinejad S1 ; Nasresfahani M1 ; Abbasi S2 ; Shirani K3 ; Tehrani DS4 ; Sadeghialiabadi M5 ; Arbab M6
Authors
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Authors Affiliations
  1. 1. Department of Emergency Medicine, Faculty of Medicine, Isfahan University ofMedical Sciences, Isfahan, Iran
  2. 2. Anesthesiology and Critical Care Research Center, Nosocomial Infection Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
  3. 3. Department of Infectious Diseases, Isfahan University of Medical Sciences, Isfahan, Iran
  4. 4. Department of IT, Shahid Beheshti University, Tehran, Iran
  5. 5. Department of Genetics, Faculty of Advanced Science and Technology, Tehran Medical Sciences, Islamic Azad University, Tehran, Iran
  6. 6. Department of Biology, Faculty of Science, Yazd University, Yazd, Iran

Source: Archives of Academic Emergency Medicine Published:2022


Abstract

Introduction: It is critical to quickly and easily identify severe coronavirus disease 2019 (COVID-19) patients and predict their mortality. This study aimed to determine the accuracy of the physiologic scoring systems in predicting the mortality of COVID-19 patients. Methods: This prospective cross-sectional study was performed on COVID-19 patients admitted to the emergency department (ED). The clinical characteristics of the participants were collected by the emergency physicians and the accuracy of the Quick Sequential Failure Assessment (qSOFA), Coronavirus Clinical Characterization Consortium (4C) Mortality, National Early Warning Score-2 (NEWS2), and Pandemic Respiratory Infection Emergency System Triage (PRIEST) scores for mortality prediction was evaluated. Results: Nine hundred and twenty-one subjectswere included. Of whom, 745 (80.9%) patients survived after 30 days of admission. The mean age of patients was 59.13 ± 17.52 years, and 550 (61.6%) subjects weremale. Non-Survived patients were significantly older (66.02 ± 17.80 vs. 57.45 ± 17.07, P< 0.001) and hadmore comorbidities (diabetes mellitus, respiratory, cardiovascular, and cerebrovascular disease) in comparison with survived patients. For COVID-19 mortality prediction, the AUROCs of PRIEST, qSOFA, NEWS2, and 4C Mortality score were 0.846 (95% CI [0.821-0.868]), 0.788 (95% CI [0.760-0.814]), 0.843 (95% CI [0.818-0.866]), and 0.804 (95% CI [0.776-0.829]), respectively. All scores were good predictors of COVID-19 mortality. Conclusion: All studied physiologic scores were good predictors of COVID-19 mortality and could be a useful screening tool for identifying high-risk patients. The NEWS2 and PRIEST scores predicted mortality in COVID-19 patients significantly better than qSOFA. © 2022, Archives of Academic Emergency Medicine. All Rights Reserved.
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