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.