Statistical analysis
SECONDARY
Numerical data were expressed by mean ± standard deviation (SD), while categorical variables were reported as numbers and percentages. Because most of the analyzed variables were not normally distributed, as verified by the Kolmogorov-Smirnov test, a non-parametric approach was applied. The Mann-Whitney test was used for the numerical data comparison between groups, while the Chi-Square test was applied for the comparisons between categorical variables. The single patient was set as a test unit. For intragroup comparisons, the Friedman test was applied to compare numerical variables over four-time intervals (baseline, 30, 90, and 180 days), whereas the Wilcoxon test was used for two-by-two comparisons across dependent groups. Bonferroni’s correction was applied for multiple comparisons, and the alpha level of 0.050 was set and was divided by the number of potential comparisons (baseline, 3 months, 6 months) to get an adjusted significance level of 0.017 (0.050/3). The Spearman’s correlation test was used to examine a potential substantial dependency between GDF-15, GPx-1, hs-CRP, and SP-D and all analyzed variables at a 6-month follow-up.To analyze the effect of the treatment protocols on GDF-15, GPx-1, hs-CRP, and SP-D (continuous variables), a two-way ANOVA was used to estimate whether the mean of the quantitative variable (GDF-15, GPx-1, hs-CRP, and SP-D) changes based on the levels of two categorical variables, treatment and timing of treatment. Specifically, it was evaluated how the two independent variables (treatment protocols and timing), alone and in combination, influenced serum GDF-15 concentration changes. The same models were applied for the secondary outcomes GPx-1, hs-CRP, and SP-D changes. Statistical analyses were performed using IBM SPSS version 22 Statistical software for Windows (Armonk, NY, IBM corp). A significant P-value was set as < 0.05.