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.