Early Biochemical Markers in Predicting the Clinical Outcome of COVID-19 Patients Admitted in Tertiary Care Hospital

Abstract

Introduction An array of routinely accessible serum biomarkers was assessed to explore their overall impact on severity and mortality in coronavirus disease 2019. Materials and Methods A retrospective analysis of 1,233 adults was conducted. The study groups comprised 127 nonsurvivors and 1,106 survivors. Data for demographic details, clinical presentations, and laboratory reports were recorded from the medical record section. The predictors were analyzed for their influence on mortality. Results The mean (+ standard deviation) age of the patients in the nonsurvivor group was 58.8 (13.8) years. The mean age (56.4 years) was highest in severe grade patients. The odds ratio for death was 2.72 times for patients above the age of 40 years. About 46% of nonsurvivors died within 5 days of admission. Males were found to be more prone to death than females by a factor of 1.36. Serum urea depicted highest sensitivity (85%) for nonsurvival at 52.5 mg/dL. Serum albumin (3.23 g/dL), albumin-to-globulin ratio (0.97), and C-reactive protein-to albumin ratio (CAR) (2.08) showed a sensitivity of more than 70% for mortality outcomes. The high hazard ratio (HR) for deceased patients with hyperkalemia was 2.419 (95% confidence interval [CI] = 1.96–2.99; p < 0.001). The risk for nonsurvival was increased with elevated serum creatinine by 15.6% and uric acid by 21.7% (p < 0.001). The HR for hypoalbuminemia was 0.254 (95% CI: 0.196–0.33; p < 0.001) and CAR was 1.319 (95% CI: 1.246–1.397; p < 0.001). Saturation of oxygen (p < 0.001), lactate dehydrogenase (p = 0.006), ferritin (p = 0.004), hyperuricemia (p = 0.027), hyperkalemia (p < 0.001), hypoalbuminemia (p = 0.002), and high CAR values (0.031) served as potential predictors for mortality. Conclusion Adjusting for all the predictor variables, serum uric acid, potassium, albumin, and CAR values at the time of admission were affirmed as the potential biomarkers for mortality.

Keywords

• total clinical severity score
• serum markers
• mortality predictor
• sensitivity and specificity
• primary biomarkers.