The COVEG score to predict severity and mortality among hospitalized patients with COVID-19
Keywords:COVID-19, COVEG, predictors, score, severity, mortality
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-off 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 the 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.
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Science and Technology Development Fund
Grant numbers 44794