Acupoint Selection in Postoperative Ophthalmic Pain Management: A Data Mining Protocol

Abstract

Background Postoperative ophthalmic pain not only induces anxiety and depression among patients, but also prolongs the recovery cycle. However, the management of postoperative pain in ophthalmology is still not standardized. The effectiveness of acupuncture in treating postoperative pain has been validated based on numerous clinical trials and meta-analysis. Our study is to conduct the first data mining analysis to identify the most effective acupoints selection and combinations for treating postoperative ophthalmic pain, inform. Methods We will search bibliographic databases from inception to November 2023. Clinical trials evaluating the effectiveness of acupuncture therapy in the management of postoperative ophthalmic pain will be selected. Reviews, protocols, animal studies, case reports, systematic evaluations and Meta-analyses will be excluded. Primary outcome indicators will be clinical outcomes related to postoperative ophthalmic pain. 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 25.0. Results This study will investigate the most effective point selection and combination of acupuncture points for the treatment of postoperative ophthalmic pain. Conclusion Our findings will provide evidence for the effectiveness and potential therapeutic prescription of acupuncture for postoperative ophthalmologic pain, helping clinicians and patients work together to make more informed decisions.