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Acupuncture methods for acute migraine attack: a Bayesian network meta-analysis protocol
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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797392/ https://www.ncbi.nlm.nih.gov/pubmed/31601592 http://dx.doi.org/10.1136/bmjopen-2019-031043 |
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author | Zhou, Jing Li, Junlong Yang, Jiwei Li, Jianliang Wang, Chongxin |
author_facet | Zhou, Jing Li, Junlong Yang, Jiwei Li, Jianliang Wang, Chongxin |
author_sort | Zhou, Jing |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6797392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-67973922019-10-31 Acupuncture methods for acute migraine attack: a Bayesian network meta-analysis protocol Zhou, Jing Li, Junlong Yang, Jiwei Li, Jianliang Wang, Chongxin BMJ Open Complementary Medicine 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. BMJ Publishing Group 2019-10-10 /pmc/articles/PMC6797392/ /pubmed/31601592 http://dx.doi.org/10.1136/bmjopen-2019-031043 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/. |
spellingShingle | Complementary Medicine Zhou, Jing Li, Junlong Yang, Jiwei Li, Jianliang Wang, Chongxin Acupuncture methods for acute migraine attack: a Bayesian network meta-analysis protocol |
title | Acupuncture methods for acute migraine attack: a Bayesian network meta-analysis protocol |
title_full | Acupuncture methods for acute migraine attack: a Bayesian network meta-analysis protocol |
title_fullStr | Acupuncture methods for acute migraine attack: a Bayesian network meta-analysis protocol |
title_full_unstemmed | Acupuncture methods for acute migraine attack: a Bayesian network meta-analysis protocol |
title_short | Acupuncture methods for acute migraine attack: a Bayesian network meta-analysis protocol |
title_sort | acupuncture methods for acute migraine attack: a bayesian network meta-analysis protocol |
topic | Complementary Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6797392/ https://www.ncbi.nlm.nih.gov/pubmed/31601592 http://dx.doi.org/10.1136/bmjopen-2019-031043 |
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