Spss statistical software version 16

Statistical analysis was conducted using SPSS statistical software version 16.0 (Chicago, IL, USA). Distribution of data related to normality was checked using Kolmogorov–Smirnov test. Continuous variables were compared among the three groups by one-way ANOVA with Tukey's post hoc test for normal distribution or Kruskal–Wallis test for nonnormal distribution. The within-group comparison was analyzed using the paired t-test or Wilcoxon test. The Chi-square test or the Fisher's exact test was applied for categorical variables. P < 0.05 was considered statistically significant. Associations between variables were evaluated using Pearson's correlation coefficients.

Statistical analysis was performed using SPSS Statistical Software, version 16.0 (SPSS Inc., Chicago, IL, USA). Normally distributed and skewed continuous data were presented as mean±SD and median±interquartile range, respectively, whereas percentages were used for categorical data. Differences in baseline clinical and echocardiographic characteristics among patients stratified by their status of incident AF at follow-up were tested with the unpaired Student’s t-test for normally distributed variables, Mann–Whitney U test for non-normally distributed variables, and chi-squared test for categorical variables. Cox proportional hazards regression model was performed to explore the association between risk factors and the risk of new-onset AF. All variables with a p value of <0.10 by means of univariate regression were entered into the multiple cox model. Relative risks were expressed as hazard ratios (HRs) with 95% confidence intervals (CIs). New-onset AF-free survival at 6 years was analyzed with Kaplan–Meier statistics, and differences between the survival curves were assessed using the log-rank test. The predictive value of HbA1c variability for the risk of new-onset AF was analyzed using receiver operating characteristic (ROC) curve. All the above analyses were considered significant at a p-value of <0.05.

All statistical analyses were conducted with SPSS statistical software version 16.0 (SPSS, Inc., Chicago, IL, USA). Data are expressed as means ± standard error of the mean. The statistical significance of differences between groups was determined by one-way analysis of variance followed by Tukeys post hoc multiple comparison tests, or Student t-test for two means comparisons. P<0.05 was considered to indicate a statistically significant difference. Each experiment consisted of at least three replicates per condition.