Predictors of Severity and Mortality in COVID-19: A Retrospective Study from Batman, Turkey

Area of Science:

• Epidemiology
• Infectious Diseases
• Public Health

Background:

• The COVID-19 pandemic poses a significant global health challenge.
• Identifying risk factors for severe disease and mortality is essential for timely intervention and treatment.

Purpose of the Study:

• To investigate the association between COVID-19 severity and patient demographics and laboratory data.
• To identify predictors of mortality in hospitalized COVID-19 patients.

Main Methods:

• Retrospective, single-center study analyzing data from 1298 hospitalized COVID-19 patients.
• Patients categorized into mild-moderate, severe, and critical groups based on clinical severity.
• Demographic characteristics, comorbidities, and laboratory findings were compared across groups.

Main Results:

• Male gender, advanced age, diabetes mellitus, coronary artery disease, cerebrovascular events, malignancy, COPD, chronic renal failure, chronic hepatitis B, and neurological diseases were independently associated with increased severe disease and mortality.
• Multivariate logistic and ordinal logistic regression identified these factors as significant predictors.

Conclusions:

• Several demographic factors and pre-existing medical conditions are significant predictors of severe COVID-19 and mortality.
• These findings aid in early risk stratification and targeted treatment strategies for COVID-19 patients.