Statistics for windows version 26.0

Statistical analyses of all outcomes were conducted using IBM Statistics for Windows (version 26.0) (SPSS, INC 2010, IBM Company, Armonk, NY). An independent-sample t-test was applied to compare the baseline data between the two groups (HIIT and MICT). One-way repeated measures ANOVA with Bonferroni’s post-hoc tests were conducted to evaluate the weekly effect of HIIT exercise on the selected parameters during the 4-week intervention. A two-way mixed analysis of variance (ANOVA) with repeated measures was used to test for main effects of time (pre- vs. post- intervention) and group (HIIT and MICT) as well as interaction of time and group. Partial eta-squared (ηp²) was used to estimate effect size with the classifications small (0.01), medium (0.06), large (0.14) and very large (2.0; Richardson, 2011 (link)). All results were presented as mean ± standard deviation (M ± SD), and p values <0.05 were considered significant.

Data were analyzed using SPSS software Statistics for Windows, version 26.0 (IBM SPSS Statistics for Macintosh). Continuous variables are described as medians and were analyzed using Mann‐Whitney U test due to skewed distribution. Categorical variables are expressed as frequencies and percentages and were analyzed by using Chi square test or Fisher’s exact test (when counts <5). Spearman correlations between virus load and cytokine levels and between transcription factors (RORC and FOXP3) and type 3 interferons were computed. Before regression analyses, cytokine and transcription factor values were log‐transformed because of positively skewed distributions of the data. Clinical, viral, and immunological differences between study groups were analyzed using unadjusted and multivariable linear model analysis. The adjustments for immunologic analyses included clinical factors and virus infections, which significantly differed between the groups, and age. The backward stepwise method was used for the final adjustment model separately for each cytokine and transcription factor. Only statistically significant factors were kept in the model. Statistical significance was established at the level of p < 0.05.