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.