Coronavirus disease 2019 (COVID-19) remains a global pandemic. Early warning scores (EWS) are used to identify potential clinical deterioration, and this study evaluated the ability of the Rapid Emergency Medicine score (REMS), National Early Warning Score (NEWS), and Modified EWS (MEWS) to predict in-hospital mortality in COVID-19 patients. This study retrospectively analyzed data from COVID-19 patients who presented to the emergency department and were hospitalized between 1 May and 31 July 2021. The area under curve (AUC) was calculated to compare predictive performance of the three EWS. Data from 306 COVID-19 patients (61 ± 15 years, 53% male) were included for analysis. REMS had the highest AUC for in-hospital mortality (AUC: 0.773, 95% CI: 0.69–0.85), followed by NEWS (AUC: 0.730, 95% CI: 0.64–0.82) and MEWS (AUC: 0.695, 95% CI: 0.60–0.79). The optimal cut-off value for REMS was 6.5 (sensitivity: 71.4%; specificity: 76.3%), with positive and negative predictive values of 27.9% and 95.4%, respectively. Computing REMS for COVID-19 patients who present to the emergency department can help identify those at risk of in-hospital mortality and facilitate early intervention, which can lead to better patient outcomes.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.