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