Figure 2. Curves of biochemical blood parameter of COVID-19 patients who were died
Biochemical blood parameters found to be significant as a result of univariate analyzes were included in the multivariate logistic regression model. First, VIF (Variance Inflation Factor) analysis was performed to detect multiple linear correlation. VIF is calculated to determine the degree of relationship of an independent variable with other independent variables (17). If VIF is greater than or equal to 10, there is a multicollinearity problem (18-20). In the study, the VIF value of T. Bilirubin and D. Bilirubin parameters was found to be above 10. T. Bilirubin and D. Bilirubin were removed from the model and the model was re-established. The result of the established multivariate logistic regression analysis model, the mean increases in Glucose (OR:1.01, p <0.05), Urea (OR:1.03,p <0.05), ALP (OR:1.01, p <0,05), LDH (OR: 1.01, p <0.05) parameters were found to increase the risk of death. On the other hand the mean increases in Albumin (OR:0,22, p <0,05), Calcium (OR:0,73,p <0,05) and Potasium (OR:0,38, p <0,05) parameters were found to decrease the risk of death (Table 4).
Table 4. Evaluation of Risk Factors Affecting Ex with Multivariate Logistic Regression Analysis