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

Peyman Saberian; Nader Tavakoli; Parisa  Hasani-Sharamin; Leila Kheyrati; Somaye Younesian; Hosein Rafiemanesh

doi:10.18502/fem.v5i3.5891

Peyman Saberian Prehospital and Hospital Emergency Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Nader Tavakoli Trauma and Injury Research Center, Iran University of Medical Sciences, Tehran, Iran.
Parisa Hasani-Sharamin Tehran Emergency Medical Service Center, Tehran, Iran.
Leila Kheyrati National Emergency Medical Organization, Ministry of Health and Medical Education, Tehran, Iran.
Somaye Younesian Prehospital and Hospital Emergency Research Center, Tehran University of Medical Sciences, Tehran, Iran.
Hosein Rafiemanesh Department of Epidemiology, School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

DOI: https://doi.org/10.18502/fem.v5i3.5891

Keywords: Clinical Decision Rules; COVID-19; Emergency Medical Services; Patient Outcome Assessment

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 cutoff 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 AUCROC 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.