Spss version 24.0 statistical software for windows

All continuous variables were reported as mean ± standard deviation (M ± SD), and categorical variables were presented as counts and percentages. The Kolmogorov–Smirnov test was used for the normality assumption. Pearson’s chi-squared test was used to investigate the categorical variables. For the analyses of continuous variables with normal distribution, a t-test was used to examine the differences between the normal cognition and impaired cognition patients. Kruskal–Wallis with post hoc Mann–Whitney U-test was used to analyze the continuous variables with non-normal distribution. Correlations between nocturnal BP fall and MMSE were evaluated using linear regression. Cox regression and Kaplan–Meier curves were used for survival analysis. All statistical analyses were performed using SPSS statistical software version 24.0 for Windows (SPSS Inc.), and a p-value < 0.05 was considered statistically significant.

Descriptive statistics were used for baseline characteristics. Differences between the two patient groups (Groups Ia and Ib), and between Group I and the controls (Group II), were examined using independent samples t-tests (Mann-Whitney U tests) or Chi-square (or Fisher’s exact) tests on the baseline data, depending on the type of variable and the normality of the data. Analyses of variance for repeated measures were performed between all groups to examine the effect of the training over time on fatigue (FAS), submaximal exercise capacity (6MWD), and maximal exercise capacity (SRT). The interaction with time would indicate whether both groups of patients differ or not concerning their scores across time. In our study, we first examined whether there was a difference between the two groups at baseline. Since this was not the case, no adjustment was deemed necessary. A difference between the two groups at follow-up indicates a difference in time between the two groups. This difference between the groups at follow-up is a difference that occurred in time.
To avoid gender as well as age bias, the outcome measures of physical performance were also expressed as percentage of predicted. This equation took age and sex into account.All statistical analyses were performed using SPSS statistical software (version 24.0 for Windows) (SPSS Inc., Chicago, IL, USA).