Jmp pro 16

Our primary outcome was brachial artery FMD measured on Day 10 of each condition. Secondary outcomes included TSI reperfusion slope and TSI AUC acquired from the NIRS‐VOT. An a priori power analysis determined that a sample size of 21 participants provided 95% power to detect a difference in FMD of at least 1% (effect size 0.83) at the end of the two arms using a paired samples t‐test with an alpha of 0.05 (G* Power). This difference in FMD was based on our results demonstrating that dietary potassium attenuated the effect of sodium (Smiljanec et al., 2020 (link)). An improvement of 1% in FMD is clinically significant based on a recent meta‐analysis that found a 1% improvement in FMD was associated with a decrease of 8%–10% in overall CVD risk over 4 years (Ras et al., 2013 (link)). Comparisons between the two conditions for all variables were assessed using paired t‐tests. Although not powered to detect sex differences, an exploratory analysis was conducted to examine potential differences between men and women in their response to the two conditions. Therefore, the difference score was calculated for the primary outcomes for men and women and was compared using an unpaired t‐test. Data were assessed for normality prior to analysis. JMP Pro 16.0.0 (SAS, Cary, NC) was used to carry out the analysis. Significance was set at p < 0.05.

Data were expressed as median values (range) as appropriate. Comparisons between the groups were done using the Wilcoxon signed-rank test. Receiver operating characteristic curves were constructed, and the areas under the curves were compared to test the ability to diagnose occult HCC. Optimal cut-off values for the different scales were determined the Youden’s index, which is the value that maximizes the sum of the sensitivity and specificity. Statistical significance was set at p <0.05. Statistical analyses were performed using JMP Pro 16.0.0 software (SAS Institute Inc., Cary, NC, USA).

RFS was calculated from the date of surgery until the date of the first recurrence. Overall survival (OS) was calculated from the date of surgery until the date of death. The censored was the last date of survival confirmation. These were calculated for various subsets of prognostic factors using the Kaplan–Meier method and log-rank test. The χ² test was used to estimate sensitivity. Two-sided p values of < 0.05 were considered as statistically significant. Statistical analyses were performed using JMP® Pro 16.0.0 (SAS Institute Inc., Cary, NC, USA).

JMP Pro 16.0.0 (SAS Institute, Cary, North Carolina) was used to perform the statistical analysis. Factorial analysis and standard least squares regression models were performed and the significance among treatments within a trial were determined at P ≤ 0.05. since there were significant interactions between the trials for many variables that the data within each trial were analyzed separately. Tukey’s HSD or student’s t tests were used to differentiate means in statistically significant results. A multivariate correlation analysis was also performed to determine relationships between analyzed factors.

To minimize bias for potential confounders, SGLT2 inhibitor-treated and non-treated groups were selected using propensity scores calculated by logistic regression using the baseline characteristics described above. A greedy nearest neighbor matching algorithm with a caliper width equal to 0.2 of the logit standard deviation of the propensity score was used to create matched pairs between the SGLT2 inhibitor-treated and non-treated groups. The equilibrium of the matching model was assessed using standardized differences in the means of each covariate. A threshold of 0.20 was used to identify imbalance in the baseline covariates. Matching model refinements were repeated until balance was achieved.
Data are presented as mean ± standard deviation, and Student's t-test was used to compare means between the two groups. The significance level for each test was defined as p < 0.05. All analyses were conducted using JMP software (JMP Pro 16.0.0; SAS Institute, Japan). The normality of distribution was checked using the Shapiro–Wilk normality test, followed by comparison with an unpaired Student's t-test.