Exploration of the Application Rules and Clinical Significance of Acupoints in Acupuncture Treatment of Migraine Based on Data Mining.

Abstract

Background: Abundant clinical investigations have attested to the efficacy of acupuncture in treating migraines. However, as each acupoint elicits distinct analgesic pathways and acupuncturists vary in their acupoint selection, there is currently an absence of evidence-based guidance for determining the optimal acupoint selection.

Objective: The aim of this study was to conduct an initial comprehensive data mining analysis to identify the most effective acupoints and their combinations for migraine treatment.

Methods: A comprehensive search was carried out in eight electronic bibliographic databases (PubMed, Embase, Cochrane Library, Web of Science, China National Knowledge Infrastructure, Wanfang Database, Chinese Biomedical Literature Database, and Chongqing VIP Database) from their inception up to May 2025. Studies evaluating the effectiveness of acupuncture in treating migraines were selected. The literature was rigorously evaluated according to predefined inclusion and exclusion criteria, and relevant data were then extracted for analysis. Excel 2021 was used for descriptive statistical analysis. Association rule analysis was performed using SPSS Modeler 14.1. Exploratory factor analysis, cluster analysis, and decision tree analysis were conducted using SPSS Statistics 26.0.

Results: A total of 911 trials were identified, from which 1610 groups of effective prescriptions involving 181 acupoints were extracted. The most commonly used acupoints were Feng-chi (GB20), Tai-yang (EX-HN5), Shuai-gu (GB8), Bai-hui (GV20), and He-gu (LI4). The gallbladder meridian was the most frequently utilized meridian. Specific points, mainly crossing points, were predominantly used, with head and neck acupoints being the most common. The combination of "Feng-chi (GB20), Tai-yang (EX-HN5), and Shuai-gu (GB8)" was frequently used as the core acupoints group. Additionally, several acupoint combinations were obtained through exploratory factor analysis, cluster analysis, and decision tree analysis.

Conclusion: This research provides evidence-based support for the effectiveness of acupoint selection in migraine treatment and offers potential therapeutic recommendations, thereby facilitating collaborative decision-making between healthcare providers and patients.