Statistical Analysis
Categorical variables were presented as absolute values and percentages and were compared using chi-square test; Fisher test was applied as appropriate. Continuous variables were analyzed as means and standard deviations if they presented normal distribution, and as medians and interquartile intervals if abnormal. The mean differences between study groups were evaluated by calculating Student’s t-test after controlling for equality of variances with the Levene’s statistic.
Logistic regression was used to detect predictors of symptoms. Odds ratio and 95% confidence interval were calculated for multivariate analysis. Classical variables such as male gender, spontaneous type-1 ECG pattern and VF/VT induction were allocated in a multivariate model using a backward stepwise selection. The number of variables that could enter the multivariate analysis was limited using the P,m/10 rule to prevent over-fitting the model.
The mean event rate per year was evaluated by the number of events occurring during the follow-up divided by the number of patients multiplied by the average duration of follow-up.
Data were analyzed with SPSS statistical package (version 20.0, SPSS, Chicago, Illinois). Significance was defined as p values <0.05.