Data analysis and report
The normality of the data was assessed using the Kolmogorov-Smirnov test, and all data were shown to be normal. The results were displayed as mean± standard deviation (SD) for quantitative variables and number (percent) for qualitative variables. Data were compared between the study groups using an independent sample T-test. The correlation among baseline serum biomarkers with demographic and clinical parameters was measured by bivariate analysis to obtain the Pearson correlation coefficient (r) for quantitative variables, and the chi-square test was employed to analyze categorical variables. According to the longitudinal data, there are repeated outcomes within one individual; therefore, the generalized estimating equations technique (GEE) model was used with unstructured correlation to analyze a longitudinal dataset with five measurements (sex, blood group type, age, serum levels of cortisol, and serum levels of aldosterone) on a positive PCR group (52 subjects) for each of the four dichotomous outcome variables (pulmonary, general, gastrointestinal, and neurologic symptoms), separately. The odds ratio (OR) and confidence interval values (95% CI) for OR were reported for each model. All statistical analyses were performed using IBM SPSS Statistics version 26.0 and the significance level was considered as 0.05.