SynthesisFrontiers in medicine2026
Acupuncture improves anxiety and depression in patients with polycystic ovary syndrome: a systematic evaluation and meta-analysis.
Synthesis in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Acupuncture is increasingly utilized to address anxiety and depression in polycystic ovary syndrome (PCOS), yet evidence for non-pharmacological interventions remains limited. This study aimed to rigorously evaluate the efficacy and safety of acupuncture in alleviating anxiety and depression among women with PCOS, while exploring its potential mechanisms. Methods: Eight Chinese/English databases (CNKI, Web of Science, PubMed, Embase, etc.) were searched from inception to March 1, 2025. Two investigators independently screened studies, extracted data, and assessed quality via the Cochrane risk-of-bias tool. The meta-analyses were performed with RevMan 5.4. Additionally, data mining methods were used, including frequency statistics to analyze the frequency of acupuncture points and the meridians involved. Results: Twelve RCTs ( Conclusion: Acupuncture, particularly manual and short-term protocols, is a safe and effective adjunct for reducing anxiety and depression in PCOS. These benefits may be mediated via modulation of androgen levels, adiposity, and neuroendocrine pathways. Nevertheless, conclusions are limited by sample size, methodological heterogeneity, and inadequate adverse event reporting. Higher-quality RCTs are needed to confirm the safety and efficacy of these methods. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251000646, Identifier CRD420251000646.
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