Statistical analysis
The statistical package SPSS, version 20.0 (SPSS, Chicago, Illinois, USA) was used for statistical analyses. Continuous variables are expressed as means ± standard deviation (median). All continuous variables were checked with Kolmogorov – Smirnov normality test to show their distributions. All our continuous variables showed abnormal distributions, therefore Mann–Whitney U test to compare all of them. Chi-square test was used to compare categorical variables.P -values were considered statistically significant if smaller than .05. Subgroup analysis was done for the 104 patients with pacemakers.
We determined the sample size for the test by power/sample size formulas. The power analysis of binary logistic regression analysis at 80% power and at a .05 significance level required sample size of 150.
A multivariable logistic regression model was used to assess the independent predictors of RNRVAS. The alternative test hypothesis was built as two-sided for each statistical analysis. The tests were independent and so the experiment-wise Type 1 error did not exceed .05 alpha levels. All parameters in Table 1 were assessed using univariate analysis except for the presence of VA conduction which is mandatory for RNRVAS development. Significant univariate variables with P .05 were included in the multiple logistic regression analysis for odds ratios and 95% confidence intervals.