Statistical analysis
Traditional pairwise meta-analysis with Review Manager 5.4.1For binary data, odds ratio (OR) and 95% CI are used as effect size indicators. OR<1 indicates that one intervention may be worse than another intervention; OR>1 indicates that one intervention may be better than another intervention; 95%CI containing 1 means that the difference is not statistically significant. For continuous data, standard mean difference (SMD) and 95% CI were used as effect size indicators. SMD<0 means that one intervention may be worse than another; SMD>0 means that one intervention may be better than another; 95%CI containing 0 means that the difference is not statistically significant. In direct Meta analysis, Q test and I2 index are used to evaluate the heterogeneity of each effect size. If P>0.1 and I2<50%, it indicates that the results of each study have good homogeneity, then the fixed effects model is used. If P≤0.1 and/or I2≥50%, the results of the study are statistically heterogeneous, and a random effects model is used.
Network meta-analysis with software ADDIS 1.16.8
The Node-split model is used to test the consistency in the network meta-analysis. If there is no statistical difference between the studies within the subgroup (P>0.05), it indicates that the heterogeneity of the included studies is small, so the consistency model is used for analysis; otherwise, an inconsistency model is used for analysis. A ranking probability table is used to rank the pros and cons of intervention measures (the value indicates the probability of intervention measures in the nth position). Regarding the main indicators of this article, the higher the ranking, the better.