In-Seon Lee

In Traditional East Asian Medicine, acupoints are selected based on clinical symptoms and pattern identification. Since treatment plans target specific diseases and patterns, acupoints may be selected based on clinical indications or pattern-related considerations. This study aimed to examine the associations between acupoint use and deficiency–excess, cold–heat, and dryness–dampness pattern scores. Data were collected from the medical records of 423 outpatients with various pain disorders. Clinicians assigned semi-quantitative scores for deficiency–excess, cold–heat, and dryness–dampness on a −5 to +5 scale as part of the study assessment. Mean scores across the 3 pattern dimensions were calculated for the 30 most frequently prescribed acupoints, followed by hierarchical clustering. Two- to six-cluster solutions were compared using silhouette scores, and a five-cluster partition was retained for descriptive interpretation and further assessed for bootstrap stability. Across the 423 cases, ST36, LR3, and LI4 were the most commonly used acupoints for pain management. These 30 acupoints showed heterogeneous profiles across the 3 pattern dimensions. Hierarchical clustering provided an exploratory five-group representation, although no uniquely optimal cluster solution was identified. Commonly used acupoints showed heterogeneous profiles across clinician-assigned deficiency–excess, cold–heat, and dryness–dampness scores. These findings provide an exploratory description of pattern-related tendencies in real-world acupoint selection. Further prospective studies using standardized pattern assessment and adjustment for disease- and clinician-related factors are required to validate these associations.

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.