Statistical analysis
Paired and unpaired t tests were used for comparison of normally distributed and Wilcoxon rank sum test used for non-normally distributed variables. Where necessary, log transformations were employed. Data are presented as mean (standard deviation) or median (Q1–Q3). Dichotomous variables were compared using χ2 test or Fisher’s exact test, as appropriate. The Kaplan-Meier survival methods with log-rank tests were used. The patients were divided into 2 groups; (1) preoperative SR group, and (2) preoperative AF group. To investigate the relationship between preoperative AF and long-term mortality, univariate and multivariable hazard regression models of Cox were used. The bootstrap technique using one thousand samples was used as a way to account for final multivariable model uncertainty. All study variables were first analysed with univariate analysis and those that showed a significant interaction (P< 0.1) were entered into the final multivariable analysis. Furthermore, we performed propensity score matching analysis with 1:1 matching followed by logistic regression analysis to estimate the average treatment effect adjusted for baseline differences (namely age, gender, hypertension, diabetes mellitus, chronic pulmonary disease, peripheral vascular disease, previous myocardial infarction, perioperative creatinine level and left ventricular function) between the two groups of interest. The coefficients were converted to odds ratios for interpretation. A P‐value of <0.05 was considered statistically significant. Analyses were performed with Stata V.15 (StataCorp, College Station, Texas).