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] .