Yujun He,1,* Lu Li,1,* Miao Zhou,1,* Yi Xu,1 Jie Tang,1 Yachao Wu,1 Minhui Liu,1 Bowen Xing,2 Xiaojun Li,1 Xiaoyi Wang1 

1Department of Traditional Chinese Medicine, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou City, People’s Republic of China; 2The First People’s Hospital of Chenzhou City, Chenzhou City, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Xiaojun Li, Department of Traditional Chinese Medicine, Taizhou Hospital of Zhejiang Province, Taizhou city, People’s Republic of China, Email lixj@enzemed.com Xiaoyi Wang, Department of Traditional Chinese Medicine, Taizhou Hospital of Zhejiang Province, 150 Ximen Street, Linhai City, Taizhou City, Zhejiang Province, 317000, People’s Republic of China, Email 984437045@qq.com

Background: Trigeminal neuralgia is a prevalent neurological disorder within neuropathic pain. It severely impairs patients’ quality of life, disrupting daily activities with intense facial pain. While acupuncture has proven effective in treating it, there’s no consensus on acupoint selection. Different acupuncturists use various acupoints based on personal theories and experiences, and the optimal acupoints remain unclear due to varied analgesic mechanisms. This lack of clarity obstructs the standardization of acupuncture treatment, emphasizing the need for further research.
Objective: Our purpose is to conduct the first thorough data mining analysis to identify the most effective acupoint selection and combinations for treating trigeminal neuralgia from published clinical trials.
Methods: We will search 8 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 inception to May 2025. Clinical trials assessing the effectiveness of acupuncture therapy on the management of trigeminal neuralgia will be selected. We will strictly screen literature according to inclusion and exclusion criteria, and then extract relevant data for analysis. Descriptive statistics will be performed in Excel 2021. Association rule analysis will be performed in SPSS Modeler 14.1. Exploratory factor analysis, cluster analysis, and decision tree analysis will be performed in SPSS Statistics 26.0. Since the study was based on published studies, no ethical approval was required.
Results: This study will investigate the most effective acupoint selection and combinations for patients with trigeminal neuralgia.
Conclusion: Our findings will provide evidence for the effectiveness and potential treatment prescriptions of acupoint application for patients with trigeminal neuralgia, helping clinicians and patients make a more informed decision together.

Keywords: acupuncture, trigeminal neuralgia, data mining, descriptive statistics, association rule analysis, exploratory factor analysis, cluster analysis, decision tree analysis