2.6. Statistical Analysis
diabetes
DIABETES
The sample size estimation was to detect a sizeable effect size of reduction in adverse health outcomes by the intervention. Based on previous literature on the incidence of adverse outcomes in diabetes patients and elderly populations [Continuous variables were expressed in the mean (±standard deviation) while categorical variables were presented as a percentage. Changes in continuous variables, including the quantities of bacteria, were compared by the Wilcoxon rank-sum test, whereas changes in categorical variables were compared using the Chi-square test or Fisher’s exact test. A two-sided Fold change (month 3/baseline) of species abundance within each subject was calculated first and then Wilcoxon rank-sum tests (two sides) were performed to compare differences between different groups. Paired Wilcoxon rank-sum tests (two sides) were performed to compare the alpha diversity, and COVID (Long COVID)-positive correlation bacterial species of baseline and month 3 samples within each treatment group. Pairwise multilevel comparisons among the baseline and month 3 samples of the placebo and SIM01 treatment group were carried out on the JSD distance matrix using the pairwise Adonis test, which was assessed using permutational multivariate analysis of variance (PERMANOVA). The differential species between baseline and month 3 samples within each treatment group were evaluated with MaAsLin2 analyses, considering subject ID as a random effect. The significance threshold for these analyses was a false discovery rate (FDR)-corrected 