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

Abstract

Carpal tunnel syndrome (CTS), as the most common compression neuropathy in the upper limb, can lead to upper limb dysfunction in patients. The effectiveness of acupuncture in treating CTS has been validated based on numerous clinical trials and meta-analyses, but questions remain, such as how to select the best acupoints. Our purpose is to conduct the first data mining analysis to identify the most effective acupoint selection and combinations for treating CTS. 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 March 2023. Clinical trials assessing the effectiveness of acupuncture therapy on the management of CTS will be selected. Reviews, protocols, animal trials, case reports, systematic reviews, and meta-analyses will be excluded. The primary outcome measure will be clinical result associated with CTS. 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 CTS. Our findings will provide evidence for the effectiveness and potential treatment prescriptions of acupoint application for patients with CTS, helping clinicians and patients make a more informed decision together.