Network-Based Identification of Core Acupoints for Primary Dysmenorrhea: A Synthesis of Randomized Trial Prescriptions.

Primary dysmenorrhea is one of the most common gynecological conditions affecting women worldwide and a major indication for acupuncture treatment. Although numerous randomized controlled trials and systematic reviews have demonstrated the clinical effectiveness of acupuncture for primary dysmenorrhea, limited attention has been paid to how acupoint prescriptions are structured and which acupoints consistently play central roles across studies. In this paper, we present a network-based synthesis of acupoint prescription data extracted from 116 randomized controlled trials identified from three systematic reviews (2014-2024). These reviews were selected through a systematic search of PubMed, EMBASE, and the Cochrane Library, specifically filtering for studies that provided granular acupoint prescriptions for primary dysmenorrhea to ensure data quality for network analysis. Using multiple network analytical approaches, including centrality measures, influence maximization, community detection, and structural role analysis, we identify a set of acupoints, CV4, CV6, SP8, ST36, and BL32, as core acupoints, with SP6 functioning as a central hub linking multiple functional clusters. This finding suggests that, despite substantial heterogeneity in individual acupuncture prescriptions, treatment for PD consistently converges on a relatively stable and structurally influential set of acupoints over time. We argue that network-based synthesis of existing trial data can complement conventional evidence by clarifying core treatment structures and reducing unwarranted variability in clinical practice. Because structural centrality does not inherently guarantee therapeutic superiority, future studies should integrate symptom severity, trial quality, and patient-level outcomes with structural analyses to better translate these network-based insights into standardized clinical guidelines.