Correlation of biochemical profile at admission with severity and outcome of COVID-19

Area of Science:

• Biochemistry
• Infectious Diseases
• Clinical Medicine

Background:

• The COVID-19 pandemic, originating in China in late 2019, rapidly escalated into a global health crisis.
• The novelty and rapid spread of SARS-CoV-2 necessitated the identification of prognostic markers for disease severity and patient outcomes.

Purpose of the Study:

• To identify specific biochemical parameters detectable at the time of hospital admission.
• To establish these parameters as predictors for categorizing the severity and forecasting the outcome of COVID-19 infections.

Main Methods:

• A cross-sectional study involving 128 confirmed COVID-19 patients.
• Analysis of biochemical profiles including liver enzymes (ALT, AST), kidney function markers (urea, creatinine), electrolytes (sodium, potassium, chloride), and bilirubin.
• Statistical correlation of biochemical data with disease severity and outcomes using t-tests and ANOVA.
• Receiver Operating Characteristic (ROC) curve analysis to determine predictive cut-off values.

Main Results:

• Critical COVID-19 cases showed significantly elevated urea levels (p < 0.000).
• Severe and critical cases exhibited higher alanine aminotransferases (ALT) (p=0.030) and aspartate aminotransferases (AST) (p=0.004).
• Critical illness was associated with decreased sodium (p=0.001) and chloride (p=0.026) levels.
• Expired patients had significantly increased urea (p=0.000), ALT (p=0.040), and AST (p=0.002).
• Predictive cut-off values for critical COVID-19 included urea >42.7 mg/dL, AST >43.5 IU/L, and sodium <136.9 mmol/L.

Conclusions:

• Elevated urea, AST, and ALT, coupled with decreased sodium levels upon admission, are indicative of severe COVID-19 illness.
• These biochemical markers can aid in identifying patients at high risk for poor outcomes, facilitating timely clinical intervention.