@article {Zhoue031043, author = {Jing Zhou and Junlong Li and Jiwei Yang and Jianliang Li and Chongxin Wang}, title = {Acupuncture methods for acute migraine attack: a Bayesian network meta-analysis protocol}, volume = {9}, number = {10}, elocation-id = {e031043}, year = {2019}, doi = {10.1136/bmjopen-2019-031043}, publisher = {British Medical Journal Publishing Group}, abstract = {Introduction Migraine is a primary cause of disability worldwide, particularly affecting young adults and middle-aged women. Although multiple clinical trials and systematic reviews have suggested that acupuncture could be effective in treating acute migraine attacks, the methodologies in academic studies and commonly applied practices vary greatly. This study protocol outlines a plan to assess and rank the effectiveness of the different acupuncture methods in order to develop a prioritised acupuncture-based treatment regimen for acute migraine attacks.Objective To compare the efficacy of different acupuncture methods and conventional medicinal methods in the treatment of acute migraine attacks.Methods and analysis Six databases will be searched, including MEDLINE, EMBASE, the Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, Chinese Science and Technology Periodical Database and Wanfang Database from inception to 31 August 2019. The primary outcomes will be assessed using metrics for intensity and duration (in hours) of pain post-treatment. Bayesian network meta-analysis will be conducted using WinBUGS V.1.4.3. Finally, we will use the Grading of Recommendations Assessment, Development and Evaluation System to assess the quality of evidence.Ethics and dissemination The results will be disseminated through peer-reviewed publication. Since no private and confidential patient data will be contained in the reporting, there are no ethical considerations associated with this protocol.PROSPERO registration number CRD42019126472.}, issn = {2044-6055}, URL = {https://bmjopen.bmj.com/content/9/10/e031043}, eprint = {https://bmjopen.bmj.com/content/9/10/e031043.full.pdf}, journal = {BMJ Open} }