Tai Chi for type 2 diabetes mellitus: A protocol for systematic review.

Tai Chi is gaining an increasing popularity in rehabilitation management of chronic conditions. Yet no consensus has reached on its efficacy and safety of type 2 diabetes despite that several systematic reviews (SRs) were published on this topic. Therefore, we will conduct an overview to critically evaluate current SRs and implement an updated metaanalysis with recently published randomized controlled trials (RCTs).A systematic literature search of relevant RCTs-based SRs will be conducted in electronic databases including Medline, Embase, the Cochrane Library, the Chinese National Knowledge Infrastructure, the Chinese Biomedical Literature Database from their inceptions to search date without language restrictions. Eligible SRs will be methodologically assessed by the assessment of multiple SRs 2 and Risk of Bias in SRs tool and their RCTs included will be extracted for further evidence synthesis. To update current meta-analysis on this topic, a supplementary search will be implemented for related newly emerged RCTs. Cochrane risk of bias assessment tool will be applied for RCTs quality evaluation. The grading of recommendations assessment, development and evaluation will be utilized for evidence quality assessment of outcomes. Study characteristic information on participants, interventions, outcomes, comparisons and conclusions will be described in detail. Review Manager V5.3 will be used for risk of bias assessment and Stata 14.0 for meta-analysis and sensitivity analysis.The study results will be disseminated through a peer-reviewed journal publication or conference presentation.This study finding will provide an updated evidence of Tai Chi for patients with type 2 diabetes mellitus (T2DM), thus to help inform clinical physicians, T2DM patients and their families to develop better rehabilitation plans and to draw more attention of decision-makers in exercise rehabilitation related policy-making.This study protocol has been applied for registration on PROSPERO platform (https://www.crd.york.ac.uk/PROSPERO/), with an assigned ID: CRD42019140988.