Statistical analysis
Data was analyzed using the R program. Previously proposed and widely
used algorithms described by former investigators were used to convert
median and quartile into means and SDs, if necessary. DerSimonian and
Laird’s generic inverse variance technique was used to calculate
adjusted point estimates from each study, which assigned a weight to
each study based on its variance [23] . The Cochran’s Q test
was used to examine and quantify variation in prevalence across studies.
The DerSimonian and Laird technique was used if there was heterogeneity
(P < 0.1 or I2 > 25%); otherwise, an inverse
variance fixed-effect model was used [24] . Afterward,
meta-regression and subgroup analysis were performed to identify sources
of heterogeneity, such as clinical and methodological variations. The
Egger test was used to determine whether there is publication bias[25] .