Retrospective Analysis of COVID-19 Patients Admitted to a Tertiary Care Center

Area of Science:

• Infectious Diseases
• Epidemiology
• Clinical Medicine

Background:

• COVID-19 poses significant mortality risks for hospitalized patients.
• Identifying accessible risk factors for mortality prediction is crucial, especially in resource-limited settings.

Purpose of the Study:

• To identify key risk factors for mortality in hospitalized COVID-19 patients.
• To develop and validate a simple, memorable predictive model (ABC-CDE score) for COVID-19 mortality.

Main Methods:

• Retrospective analysis of epidemiological, clinical, and laboratory data from 399 hospitalized COVID-19 patients.
• Evaluation of six parameters: Age, Blood Urea Nitrogen (BUN), Cardiac comorbidity, Lung comorbidity, Diabetes Mellitus, and elevated White Blood Cell (WBC) count.
• Development of the ABC-CDE risk score and assessment of its predictive performance.

Main Results:

• Overall mortality among hospitalized COVID-19 patients was 7.8%.
• The ABC-CDE risk score demonstrated a negative predictive value (NPV) of 96.9% and a specificity of 83.5% for predicting mortality at a cutoff score of 4.
• The model identified key predictors including age, BUN, cardiac and lung comorbidities, diabetes, and elevated WBC count.

Conclusions:

• The ABC-CDE risk score is a simple, accessible, and economically viable tool for predicting mortality in hospitalized COVID-19 patients.
• This score can be easily monitored and remembered, making it suitable for low-resource and rural settings.
• The ABC-CDE score aids in risk stratification and clinical decision-making for COVID-19 patients.