PROGNOSTIC VALUE OF EARLY WARNING SCORES IN PREDICTING IN HOSPITAL MORTALITY AMONG COVID-19 PATIENTS IN AN EMERGENCY DEPARTMENT

Abstract

Aim: The emergence of a new pathogen, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a surge of new patients requiring hospitalisation. The rapid identification of patients with severe SARS-CoV-2 infection has become a key challenge for healthcare systems. The aim of the study was to assess the prognostic value of early warning scores in predicting mortality in COVID-19 patients. Material and methods: The study involved a retrospective analysis of the medical records of 2,449 patients with COVID-19 admitted to emergency care, for whom five early warning scores were calculated based on the data obtained. Results: In order to assess the usefulness of NEWS, NEWS2, MEWS, SEWS and qSOFA in predicting in-hospital mortality in COVID-19 patients, AUC (area under the ROC curve) values were calculated. They were, respectively: 0.76 (95% CI 0.72-0.79), 0.75 (95% CI 0.72-0.79), 0.64 (95% CI 0.60-0.69), 0.61 (95% CI 0.57- 0.66) and 0.55 (95% CI 0.50-0.59). Conclusions: NEWS demonstrated the highest discriminatory power, indicating that it can be used to predict in-hospital mortality in COVID-19 patients.