ArticleMedicina (Kaunas, Lithuania)2023
Evaluation of Early Warning Scores on In-Hospital Mortality in COVID-19 Patients: A Tertiary Hospital Study from Taiwan.
Article in Medicina (Kaunas, Lithuania), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Determining a Clinically Applicable Cutoff in AI Algorithms for Predicting Clinical Deterioration: A Workload-Constrained, Alarm-Based Approach.Journal of clinical medicine · 2026Article
- Respiratory and Pleural Pathogens in Octogenarians Hospitalized with COVID-19: Impact of Secondary Bacterial Pneumonia on Day-5 SOFA and Mortality.Microorganisms · 2026Article
- Comparing the predictive power of the National Early Warning Score (NEWS) and Modified Early Warning Score (MEWS) for ICU admission in respiratory patients during the COVID-19 pandemic: A multicenter cross-sectional study.International journal of emergency medicine · 2025Article
- The Predictive Value of Risk Factors and Prognostic Scores in Hospitalized COVID-19 Patients.Diagnostics (Basel, Switzerland) · 2023Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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