Spss statistics software version 24

Statistical analyses were performed using SPSS Statistics software version 24.0 (IBM Corporation, Tokyo, Japan). The Kruskal–Wallis test was used to compare BL (end of the placebo period) and evaluation parameters (HR and HRV) for the whole 24 h period and for the feeding and sleeping time periods, with parameters recorded during each of the third (and last) 24 h period of the administration of both drugs. If a significant difference was observed the Steel–Dwass test was used to compare all pairs of medians. The same statistical analysis was used to compare differences for the BL/placebo period, in terms of HR and HRV, comparing the whole 24 h period with the feeding and sleeping periods.
A paired t‐test was used to compare the evaluation parameters between BL and day 7 of the wash‐out period to check if the parameters had returned to their BL values during the wash‐out period. Data are presented as median (minimum–maximum). A p‐value of <0.05 was considered statistically significant.

We estimated the numbers and fractions of each cell subtype within the different regions and for each patient. These results were compared using IBM SPSS Statistics software (version 24.0), with Student’s t-test applied for normally distributed data and the Wilcoxon rank-sum test applied for non-normally distributed data. Differences were considered statistically significant at P-values of <0.05.

Data were analysed using descriptive statistics. Categorical variables are presented as absolute values and frequencies (%), while mean with standard deviation (SD) or median and interquartile range (IQR) were used for continuous variables. T-tests and Mann–Whitney U-tests were used for continuous variables to make comparisons between the MIS and CS groups, while Fisher’s exact or Chi-square tests were used for comparisons of categorical variables. Kaplan–Meier curves were used for survival analyses. Hazard ratios (HR) were calculated using Cox regression. Odds ratios (OR) were calculated by logistic regression and adjusted for procedural differences between the two groups (MV repair, MV replacement, cryoablation, left atrial appendage closure [LAA] and concomitant tricuspid valve repair [TVR]). A two-tailed p-value of < 0.05 was considered to be statistically significant. We used IBM SPSS Statistics software version 24.0 (IBM Corporation, Armonk, NY, USA) for all statistical tests.

The data considered categorical were presented in proportion, using the Chi-square test and Fisher's exact test. The normality of the distribution of numerical variables was assessed by the Kolmogorov–Smirnov test. For the numerical variables, Student's t-test was used to verify the differences between the means of the groups evaluated. The results obtained provided their distribution in two groups: with coinfection (HIV+/HPV+) and without coinfection (HIV+/HPV–). A 95% confidence interval and a significance level of p ≤ 0.05 were adopted for the analysis performed. All tests were applied using IBM SPSS® Statistics software version 24.0.

Continuous variables are described as the means, medians, and ranges. Comparisons between groups were performed using independent Student’s t-tests, Welch’s t-tests, or 1-way ANOVA. Categorical data were analyzed with chi-square tests. Survival of the cup was calculated using life tables with 95% confidence intervals (CIs). For comparison of the survival of cups with and without screw holes, the log-rank test was used. Adjusted hazard ratios (HRs) with CIs were calculated using multivariable Cox regression models.
The total observation time comprised 18 years (2000–2017). However, the number of cups at risk for revision after 10 years was only 1,846, and the distribution of cups with and cups without screw holes was unequal between cup design (Table 4, see Supplementary data); therefore, the risk for revision was not calculated beyond 10 years.
The E-value was calculated to define the minimum strength of association of the HR that an unmeasured confounder would need to have with both the treatment and the outcome to fully explain away the association between screw holes and cup revision on the measured covariates (VanderWeele and Ding 2017 (link)).
A p-value < 0.05 was considered statistically significant. Statistical analysis was performed using SPSS Statistics software, version 24.0 (IBM Corp, Armonk, NY, USA).