2.6. Statistical Analysis
HD, arterial stiffness, diabetes
SENSITIVITY, SECONDARY, ARTERIAL STIFFNESS, REGRESSION, DIABETES
The sample size calculation was based on previous data from kidney transplant patients due to the absence of a previous trial in the HD population [Continuous variables with normal distribution were expressed as a mean ± standard deviation (SD). In a skewed distribution, the data were presented as median with interquartile range (IQR). Baseline comparisons between groups were obtained using a chi-square test for categorical data and a student’s The intention-to-treat (ITT) principle was applied in all analyses including all participants who were randomized and had undergone at least one follow-up cfPWV measurement. Multivariable linear mixed effect model (LMM) adjusted by baseline cfPWV with treatment and continuous time interaction-term were used to analyze the primary outcome.Sensitivity analyses for primary outcomes were performed by including only patients who completed a 24-week follow-up and by including blood-pressures and smoking status as adjusting factor using the same LMM modeling.For secondary outcomes, the chi-square test was used to determine a significant difference between the proportion of participants with progression of arterial stiffness at the end of the study. LMM with continuous-time interaction and treatment were used for all laboratory data. Subgroup analyses were explored for diabetes status, HD frequency, and baseline serum calcium level. A post-hoc analysis to determine predictors of arterial stiffness was performed using multivariable logistic regression.All reported 