ABSTRACT
Prognostic markers are the biomarkers used to measure the disease progression and patient outcome regardless of treatment in coronavirus disease 2019 (COVID-19). This study aimed to analyze laboratory parameters as prognostic markers for the early identification of disease severity. In this study, 165 patients attending Sukraraj Tropical and Infectious Disease Hospital with COVID-19 were enrolled and divided into severe and non-severe groups. The demographic data, underlying co-morbidities, and laboratory findings were analyzed and compared between severe and non-severe cases. The correlation between the disease criticality and laboratory parameters was analyzed. Cut-off values of parameters for severe patients were speculated through the receiver operating characteristics (ROC) curve, and regression analysis was performed to determine the risk factors. Patients with severe COVID-19 infection had significantly higher absolute neutrophil count, neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), ferritin, positive carbohydrate reactive protein (CRP), glucose, urea, creatinine, and aspartate aminotransferase, while lower absolute lymphocyte count, absolute eosinophil count (AEC), and red blood cell count in comparison to non-severe infection. ROC analysis gave a cut-off value (sensitivity, specificity) of age, AEC, NLR, PLR, and ferritin as 47.5 years (70.2, 64.7%), 335 cells/mm(3) (74, 67%) 3.3 (68.4, 63.7%), 129 (77.2, 51%), and 241 ng/mL (74.0%, 65.0%) respectively. Risk factor analysis showed higher age, low AEC, high ferritin, and positive CRP as independent risk factors associated with severe COVID-19 infection. Hematological and inflammatory markers, including novel NLR and PLR, should be assessed to aid clinicians in the early identification of severe cases, prioritization of cases, and effective management to decrease the mortality of COVID-19 patients.
ABSTRACT
Objectives: Prognostic markers used to measure the disease progression and patient outcome regardless of treatment in COVID-19. We aim to analyze and evaluate the prognostic markers for early identification of severe patients. Materials and Methods: During a 3-month period (November 2020 to January 2021), a total of 165 patients attending Sukraraj Tropical and Infectious Disease Hospital with laboratory-confirmed COVID-19 were enrolled and divided into non-severe and severe groups. The demographic data, underlying co-morbidities and laboratory findings were analyzed. Correlation, Regression analysis and ROC curve was performed to determine the risk factors and cut-off values for critically ill patients were speculated. Results: Disease severity was significantly associated with age (r = 0.359, p<0.001), RBC (r = -0.163, p = 0.037), AEC (r = -0.300, p<0.001), ALC (r = -0.239, p<0.001), ANC (r = 0.228, p<0.001), NLR (r = 0.336, p<0.001), PLR (r = 0.286, p<0.001), glucose (r = 0.155, p = 0.046), urea (r = 0.282, p<0.001), creatinine (r = 0.194, p = 0.012), AST (r = 0.169, p = 0.030), ferritin (r = 0.359, p<0.001) and CRP. Whereas Increasing age (AOR = 3.611), positive CRP (AOR = 2.930), high ferritin (AOR = 2.754), decreased AEC (AOR = 3.415) was found to be independent risk factors for COVID-19 severity. Similarly, ROC (Receiver Operating Characteristics) curve analysis showed age (AUC = 0.724), NLR (AUC = 0.710), PLR (AUC = 0.678), ferritin (AUC = 0.735), AEC (AUC = 0.661) can be used to monitor the disease severity. Conclusion: Our study revealed severe COVID-19 is associated with increased markers of innate immune response such as neutrophil count, NLR, CRP and serum ferritin;decreased markers of adaptive immune response such as lymphocyte and increased markers of major organ damage including AST, urea, and creatinine compared to COVID-19.