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Seven Criteria of Severe Covid-19 (Scsc): A New Pre-Hospital Prognostic Scoring Tool Suggested for Screening of Probable/Confirmed Covid-19 Patients With Severe Outcomes Publisher



Saberian P1, 2 ; Tavakoli N3 ; Hasanisharamin P4 ; Kheyrati L5 ; Younesian S1 ; Rafiemanesh H6
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Authors Affiliations
  1. 1. Prehospital and Hospital Emergency Research Center, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Department of Anesthesiology, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Trauma and Injury Research Center, Iran University of Medical Sciences, Tehran, Iran
  4. 4. Tehran Emergency Medical Service Center, Tehran, Iran
  5. 5. National Emergency Medical Organization, Ministry of Health and Medical Education, Tehran, Iran
  6. 6. Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Source: Frontiers in Emergency Medicine Published:2021


Abstract

Introduction: COVID-19 pandemic led to various consequences in medical care that had been long provided for the patients referred to the hospitals. Objective: We conducted this study to derive and validate a new scoring system that can accurately differentiate COVID-19 patients who may have a worse outcome from others at the prehospital stage. Methods: This study was performed on probable/confirmed COVID-19 patients, who were transferred to the hospitals by Tehran emergency medical services (EMS). Occurrence of one of the items including: in-hospital death, intensive care unit (ICU) admission, or hospitalization for more than 20 days was considered to indicate a “severe disease”. Univariate and multivariate logistic regression were used for assessment of the relationship between all independent variables and the outcome. In the validity assessment step, area under the receiver operating characteristic (ROC) curve was calculated for a data set independent from the data based on which the model was designed. The sensitivity and specificity were also presented based on the best suggested cut-off point. Results: In this study, the data of 557 cases were analyzed in the derivation step and 356 cases were assessed in the validation step. The univariate logistic regression showed that age, weakness and fatigue, disease history, systolic blood pressure, SpO2, respiratory rate, and Glasgow coma scale (GCS) were statistically significant in severe disease group. The area under the ROC curve (AUC-ROC) of the tool was 0.808 (95% CI: 0.779, 0.834). The best cut-off point for screening was the score of ≥4, in which the sensitivity and specificity of the tool for the best cut-off point were 71.87% and 78.06%, respectively. In the validation step, the AUC-ROC of the tool was 0.723. Conclusions: Seven criteria of severe COVID-19 (SCSC) tool could properly differentiate probable/confirmed COVID-19 patients with severe outcomes in the pre-hospital stage. © 2021 Tehran University of Medical Sciences.