Validation of the Covid-19 Severity Index: A Retrospective Study among Egyptian Patients, KAMAL A.H. ELGHORORY, DALIA A.M. NASR, JOHN N.N. BESTAROUS and MOHAMMED A.A. TOLBA
Background: The COVID-19 Severity Index is a predictive tool that aims to identify hospitalized patients with COVID-19 who are at risk of clinical deterioration and intensive care unit (ICU) admission. However, its validity and applicability in dif-ferent settings and populations remain uncertain. Aim of Study: To evaluate the performance of the COV-ID-19 Severity Index in predicting ICU admission among Egyptian patients diagnosed with COVID-19 infection. Patients and Methods: This was a retrospective cohort study of 100 patients with confirmed COVID-19 who were ad-mitted to Ain Shams University Hospital from October to De-cember 2021. The patients were divided into two groups: ICU (n=30) and non-ICU (n=70). The COVID-19 Severity Index was calculated based on clinical, laboratory and radiological parameters at hospital admission (day 0), 48 hours and 24 hours prior to ICU admission for ICU group, and the same corre-sponding days for non-ICU group. The predictive performance of the index was assessed using receiver operating characteris-tic (ROC) curve analysis. Results: The COVID-19 Severity Index had a high sensi-tivity and specificity for predicting ICU admission 24 hours and 48 hours before the actual admission, with area under the curve (AU-ROC) of 0.998 and 0.997 at 48 hours and 24 hours prior to ICU admission, respectively. The index had poor predictive value at admission day, with (AU-ROC) of 0.575. Conclusion: The COVID-19 Severity Index showed a good prediction and high discriminatory ability to detect patients at ward level of care who are at risk of clinical deterioration 48 and 24 hours prior to the need of ICU admission. It can be used as a prognostic index for ICU admission among Egyptian pa-tients with COVID-19 infection. However, further validation studies are needed to confirm its applicability and utility in dif-ferent settings and populations.