Statistical methods:
Continuous variables were expressed as mean ± standard deviation (SD) or median ± inter-quartile range (IQR) (depending on distribution of data) and comparison between groups was performed using t test/ Mann-Whitney test. Categorical variables were expressed as percentages and compared using Chi-square/Fisher exact test as appropriate.
A multiple logistic regression model was used to identify the predictors of early mortality and Cox regression was applied to identify the best predictors of late mortality including all the significant variables listed in annexed tables (cut-off at p < 0.05) (Tables 1-5). The results were expressed as odds ratios (OR) and hazard ratios (HR) with corresponding 95 % confidence intervals (CI).
As the two groups were significantly different with respect to their baseline characteristics, propensity score matching (with a match tolerance of 0.05) was performed (including the preoperative characteristic except echocardiographic parameters) using SPSS. The matched groups were analyzed using the methods described above.
Kaplan-Meier survival analysis was applied; curves were built for each group and were compared using the log-rank statistic.
SPSS 22.0 was used to analyze the data.