Rapid Scoring Systems for Predicting Adverse Outcomes in Patients with COVID-19: A Systematic Review and Meta-Analysis

OBJECTIVES. To assess the prognostic value of rapid scoring systems in predicting mortality and adverse outcomes in patients with COVID-19 (COronaVIrus Disease 2019).
MATERIALS AND METHODS. A literature search was conducted in PubMed, eLibrary, and Science Gate. The prognostic value was evaluated via meta-analysis of AUROC (Area Under the Receiver Operating Characteristic Curve) for mortality and adverse outcomes (ICU admission, organ support, or death). Statistical analysis was performed using MedCalc 20.027 and Microsoft Excel 2019.
RESULTS. Sixty studies with 619,494 patients were included. Five scoring systems –NEWS, NEWS2, REMS, qSOFA, and SIRS were analyzed for predicting hospital mortality. REMS showed the highest prognostic value (AUC 0.808; 95% CI 0.776–0.839), while SIRS had the lowest (AUC 0.662; 95% CI 0.596–0.728). NEWS, NEWS2, and qSOFA demonstrated good predictive performance (AUC 0.722–0.782). High heterogeneity (I² > 96%, P < 0,1) was observed across studies.
Same scoring systems were assessed for predicting severe disease, NEWS and NEWS2 were most effective (AUC 0.778; 95% CI 0.707–0.849 and 0.738–0.819, respectively). REMS had an AUC of 0.733 (95% CI 0.708–0.757) with minimal heterogeneity (I² = 0%, P > 0,1), while qSOFA and SIRS showed lower accuracy. High heterogeneity remained for NEWS, NEWS2, and qSOFA.
CONCLUSIONS. The systematic review and meta-analysis showed that the REMS, NEWS, NEWS2, and qSOFA scores have sufficient prognostic value for predicting mortality and severe outcomes in COVID-19 patients. The REMS scale was most effective for predicting in-hospital mortality, while NEWS and NEWS2 were superior for assessing the risk of severe disease. These findings support the use of rapid scoring systems for risk stratification in clinical practice.