Introduction: COVID-19 severity and mortality predictors could determine admission criteria and reduce mortality. We aimed to evaluate the clinical-laboratory features of hospitalized patients with COVID-19 to develop a novel score of severity and mortality. Methodology: This retrospective cohort study was conducted using data from patients with COVID-19 who were admitted to five Egyptian university hospitals. Demographics, comorbidities, clinical manifestations, laboratory parameters, the duration of hospitalization, and disease outcome were analyzed, and a score to predict severity and mortality was developed. Results: A total of 1308 patients with COVID-19, with 996 (76.1%) being moderate and 312 (23.9%) being severe cases, were included. The mean age was 46.5 ± 17.1 years, and 61.6% were males. The overall mortality was 12.6%. Regression analysis determined significant predictors, and a ROC curve defined cut-o ff values. The COVEG severity score was defined by age ≥ 54, D - dimer ≥ 0.795, serum ferritin ≥ 406, C- reactive protein ≥ 30.1, and neutrophil: lymphocyte ratio ≥ 2.88. The COVEG mortality score was based on COVEG severity and t he presence of cardiac diseases. Both COVEG scores had high predictive values (area under the curve 0.882 and 0.883, respectively). Conclusions: COVEG score predicts the severity and mortality of patients with COVID-19 accurately.

Coronavirus Pandemic The COVEG score to predict severity and mortality among hospitalized patients with COVID-19

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Coronavirus Pandemic The COVEG score to predict severity and mortality among hospitalized patients with COVID-19