Author: Wang X, Du YH, Xiong J.
Affiliation:
Tianjin University of Chinese Medicine, Tianjin 300193, China. 2008wangxu2008@sina.com
Conference/Journal: Zhen Ci Yan Jiu.
Date published: 2011 Jun
Other:
Volume ID: 36 , Issue ID: 3 , Pages: 230-5 , Special Notes: [Article in Chinese] , Word Count: 247
To evaluate the clinical effect of acupuncture therapy for fibromyalgia syndrome (FMS) by analyzing the available studies so as to provide clinical decision-making reference.
METHODS:
The published papers on clinical trails for acupuncture treatment of FMS were widely retrieved from Chinese Biomedical Databases (1979 - 2010), www. cnki. net (1979-2010), VIP China Scientific Journal Database (1989- 2010), Digital Periodicals on Wanfang Data (1998 - 2010), PubMed (1966-2010), etc. and by using key words of fibromyalgia syndrome and acupuncture. According to criterion of evidence-based medicine, the evidence from high to low quality levels was selected to answer corresponding clinical questions, and software RevMan 5.0 was used to analyze the final results.
RESULTS:
There has been no enough clinical evidence showing definite efficacy of acupuncture for FMS. However, a Level-A study (being in line with conditions of large sample, multi-centers, randomized controlled trails) and a level-C study (having control group, but without distinct randomizing method) showed respectively that acupuncture might be superior to Amitriptyline and Brufen in relieving FMS. Moreover, a piece of evidence that acupuncture combined with western medicine was superior to western medicine alone was allocated to a level-B (having correct randomizing method and control group). Finally, only a level-C evidence proved that laser irradiation on acupoint might be superior to traditional acupuncture in improving FMS.
CONCLUSION:
Acupuncture for FMS has a positive effect, and acupuncture combined with western medicine can strengthen the curative effect. However this conclusion should be proved further by randomized controlled double blind clinical trials with large samples.
PMID: 21793391