Data extraction and quality assessment
Data extraction and presentation for the preparation of this manuscript
followed the recommendations of the Preferred Reporting Items for
Systematic Reviews and Meta-Analyses.Data abstraction was conducted by
three authors (Qianwei Huang,Tian Zheng, Qianghui Huang), who
independently used a predefined, standardized protocol, and data
collection instrument. The following study-, patient-, and
procedure-related data were extracted from the main paper. Any
discrepancies were resolved by discussion among the authors. The
Newcastle Ottawa Quality Assessment Scale (NOS) for observational trials
was used to evaluate the quality of the included studies.
The odds ratio (OR) with 95% confidence intervals (CIs) was used to
analyze dichotomous data, whereas weighted mean differences were used to
analyze continuous variables. The Cochran Q test was used to assess the
presence of heterogeneity among studies, and the Higgins I2 test was used to assess the extent of the observed
heterogeneity, which suggests 0-25%, 25-50%, and 50-75% as low,
moderate, and high heterogeneity, respectively. Given the inherent
differences in study design and demographics, we used a random-effects
model to estimate the pooled effects of our meta-analyses.
For the primary endpoints, prespecified sensitivity analyses were
performed by iteratively removing one study at a time to confirm that no
single study had a significant impact on our results. To further test
the stability of our meta analysis, we performed multiple subgroup
analyses (based on study group,different surgical methods). A
random-effects meta-regression analysis was performed to examine the
effect of preselected covariates on the overall effect. In both groups,
the logarithm of OR for the primary endpoints was regressed against age,
percentage of hypertension, diabetes mellitus, stroke, left ventricular
ejection fraction (LVEF), and size of left atrial (LA) diameter.
We examined the asymmetry of the funnel plots in detail and further
assessed them using the Begg adjusted rank correlation test and the
Egger regression asymmetry test to detect any publication bias in the
primary endpoints. All statistical analyses were carried out using the
RevMan software package (Review Manager, Version 5.3) and STATA software
12.0. P-values were two-tailed, with 0.05 considered statistically
significant.