Analysis of Acupoint Selection and Combinations in Acupuncture Treatment of Migraine: A Protocol for Data Mining.

Abstract

Background: Migraine is a prevalent neurological condition that causes significant disability and has a profound impact on sufferers' ability to work and their overall quality of life. The efficacy of acupuncture in the treatment of migraines has been confirmed via extensive clinical research. However, because each acupoint generates various analgesic processes, and different acupuncture physicians select different acupoints, there is still uncertainty regarding the optimal acupoint selection.

Objective: Our purpose is to conduct the initial thorough data mining analysis to determine the optimal acupoint selection and combinations for the treatment of migraines.

Methods: We will conduct a search of 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 the inception of the databases to July 2024. Clinical trials that evaluate the efficacy of acupuncture therapy in migraine management will be chosen. Literature will be rigorously reviewed in accordance with inclusion and exclusion criteria, and pertinent data will be extracted for analysis. Excel 2021 will be utilized to conduct descriptive statistics. SPSS Modeler 14.1 will be employed to conduct the association rule analysis. SPSS Statistics 26.0 will be employed to conduct exploratory factor analysis, cluster analysis, and decision tree analysis.

Results: This study aims to investigate the optimal acupoint selection and combinations for people suffering from migraines.

Conclusion: Our research will offer empirical support for the efficacy and possible therapeutic recommendations of acupoint application in treating migraine patients, facilitating collaborative decision-making between physicians and patients.