Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/68646
Title: What predicts a positive response to acupuncture? A secondary analysis of three randomised controlled trials of insomnia
Authors: Yeung, WF 
Chung, KF
Yu, YMB
Lao, LX
Issue Date: 2017
Publisher: BMJ Publishing Group
Source: Acupuncture in medicine, 2017, v. 35, no. 1, 24 How to cite?
Journal: Acupuncture in medicine 
Abstract: Objective Few studies have investigated the predictors of the specific and non-specific effects of acupuncture. The aim of this secondary analysis was to determine patient characteristics that may predict a better treatment response to acupuncture for insomnia.Methods We pooled the data of three randomised, double-blind, placebo-controlled trials of acupuncture for insomnia to examine sociodemographic variables, clinical characteristics, baseline sleep-wake variables, and treatment expectancy in relation to acupuncture response. Subjects with an improvement in insomnia severity index (ISI) scores of >= 8 points from baseline to 1 week post-treatment were classified as responders. Factors were compared between responders and non-responders, and also by univariate and multivariate logistic regression analysis.Results A total of 116 subjects who received traditional needle acupuncture were included, of which 37 (31.9%) were classified as responders. Acupuncture responders had a higher educational level (p<0.01) and higher baseline ISI score (p<0.05), compared to non-responders. In the multivariate logistic regression analysis, only the number of years spent in full-time education remained significant as a predictor of treatment response (OR 1.21, 95% CI 1.06 to 1.38, p<0.01).Conclusions Consistent with previous studies, our data suggest that the response to acupuncture is difficult to predict. Although the predictive power of educational level is weak overall, our findings provide potentially valuable information that could be built upon in further research (including a larger sample size), and may help to inform patient selection for the treatment of chronic insomnia with acupuncture in the future.
URI: http://hdl.handle.net/10397/68646
ISSN: 0964-5284
EISSN: 1759-9873
DOI: 10.1136/acupmed-2016-011058
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