Two-by-two meta-analysis will be conducted using STATA15.0, and The odds ratio will be used as the effect indicator for the dichotomous variable, MD as the effect indicator for the continuous variable, and a 95% CI will be given for each effect index. Heterogeneity between studies was assessed by Cochrane Q and X2, and the size of heterogeneity was assessed by I2.

We will use Stata14.2 and WinBUGS1.4.3 software to perform Bayesian network meta-analysis and merge the data in the random effects model. We will map the evidence network to represent comparisons between studies, with the thickness of the edges representing the number of comparisons made, and the size of the points representing the number of participants. Bayesian network algorithm USES Markov chain Monte Carlo method for reasoning. Inconsistencies between direct and indirect comparisons will be assessed by the node-splitting method.[23] By comparing the deviation information standards of each model, consistent and inconsistent models, fixed-effect models, and random-effect models were selected. The ranking of the effects of different acupuncture treatments will be presented by the surface under the cumulative ranking curve.

If I2 < 50% and P > .1, we will use the random-effects model; If I2≥50% or P < .1, we will use the fixed-effects model.

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