Background: Knee osteoarthritis (KOA) is a major public health issue because it causes pain and functional limitation in patients. Many studies have reported that moxibustion, a treatment in traditional Chinese medicine, is effective in treating KOA. The aim of this protocol is to develop a standard in advance for synthesize and assess the efficacy and safety of thunder-fire moxibustion for KOA from these randomized controlled trial.
Methods: The 2 commentators will screen 7 databases (PubMed, EMBASE, the Cochrane Library, Chinese National Knowledge Infrastructure, Chinese VIP Information, Wanfang Database, and Chinese Biomedical Literature Database) for randomized controlled trials that can be included from the time the database is built up until publication in December 2020. The original study that randomized control trials of thunder-fire moxibustion for patients with KOA will be selected and is not limited by country or language. In addition, researches in progress, the reference lists, and the citation lists of identified publications will be retrieved similarly. Study selection, data extraction, and assessment of the quality will be performed independently by 2 reviewers who have been trained before data extraction. A meta-analysis will be conduct if the quantity and quality of the original studies included are satisfactory; otherwise, a descriptive analysis will be conducted. Review Manager 5.4 software (The Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen, Denmark) will be using for data synthesis and assessment the risk of bias according to Cochrane Handbook.
Result: This study will provide a comprehensive review of current evidence for the treatment of thunder-fire moxibustion on KOA.
Conclusion: The conclusion of this study will provide a judging basis that whether the treatment of KOA with thunder-fire moxibustion is effective.
Registration Number: INPLASY2020100012.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8036098 | PMC |
| http://dx.doi.org/10.1097/MD.0000000000025384 | DOI Listing |
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