Abstract

Perimenopausal insomnia (PMI) is a relatively common menopausal symptom that can cause serious problems for the women themselves and their families. Today, the world is facing the trend and challenges of an aging population. It is reported that about 1.5 million women worldwide enter menopause every year, with sleep disorder identified as a core symptom. The efficacy of acupuncture combined with traditional Chinese medicine for treating PMI has been recognized by patients and doctors. We searched 8 databases to identify 15 randomized controlled trials evaluating the effects of acupuncture combined with traditional Chinese medicine on sleep in patients with PMI compared with Western medicine alone. Subsequently, data extraction and analysis were performed to assess the quality and risk of bias of the study method design, and a meta-analysis of the data was performed. This study included 15 randomized controlled trials involving 1188 patients with PMI. The results show that acupuncture combined with traditional Chinese medicine seems to be more effective than Western medicine in the treatment of PMI: efficiency (RR: 1.18; 95% CI: 1.08, 1.29; P = .001); the Pittsburgh Sleep Quality Index (PSQI) (WMD: -2.77; 95% CI: 4.15-1.39; P < .0001); follicle-stimulating hormone (FSH) (WMD: -31.45; 95% CI: 42.7-20.2; P < .001) and the Hamilton Anxiety Score (HAMA) (WMD: -2.62, 95% CI: -3.93, -1.32; P < .0001). Compared with western medicine, E2 (WMD: 5.07; 95% CI: 5.78-15.92; P = .36) and LH (WMD: -4.86; 95% CI: 11.5-1.78; P = .151) had no difference. The current analysis results show that acupuncture combined with Chinese medicine seems to have a more positive effect than western medicine alone in improving sleep and FSHF in PMI patients, but no difference has been found in improving E2 and LH. This study provides a basis for acupuncture combined with Chinese medicine to treat PMI. However, due to the higher risk of evaluation in included studies, more rigorous randomized controlled trials and higher quality studies are needed to validate included studies.

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