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

Abstract

Piriformis syndrome (PS) is a neuromuscular condition characterized by discomfort in the gluteal region. The efficacy of acupuncture as a treatment modality for PS has been substantiated through a multitude of clinical trials. However, certain queries persist, such as the optimal approach for identifying the most efficacious acupoints. The objective of this study is to perform an initial data mining analysis aimed at identifying the optimal acupoint selection and combinations for the treatment of PS. We will search 7 electronic bibliographic databases (PubMed, Embase, Cochrane Library, China National Knowledge Infrastructure, Wanfang Database, Chinese Biomedical Literature Database and Chongqing VIP Database) from inception to June 2023. We will select clinical trials that evaluate the efficacy of acupuncture therapy in the management of PS. Exclusions will be made for reviews, protocols, animal trials, case reports, systematic reviews, and meta-analyses. The primary outcome measure will be clinical outcomes associated with PS. Descriptive statistics will be performed in Excel 2019. Association rule analysis will be performed in SPSS Modeler 18.0. Exploratory factor analysis and cluster analysis will be performed in SPSS Statistics 26.0. This study will investigate the most effective acupoint selection and combinations for patients with PS. Our findings will provide evidence for the effectiveness and potential treatment prescriptions of acupoint application for patients with PS, helping clinicians and patients make a more informed decision together.