Acupoint Selection Patterns in Treating Chronic Abdominal Pain with Cheek Acupuncture Based on Data Mining.

Objective: To analyze the acupoint selection rules for cheek acupuncture in the treatment of chronic abdominal pain by data mining technology. Methods: The chronic abdominal pain medical records of Professor Ouyang Bowen in the outpatient clinic of Guangdong Provincial Hospital of Traditional Chinese Medicine from January 2019 to December 2022 were used as the data source. The medical record data (basic information, Western medicine diagnosis, Chinese medicine diagnosis, Chinese medicine syndrome type, physical examination target, acupoint prescription, VAS score results) were entered into Excel2019 software to establish a database and standardize the processing. The frequency of acupoint use was descriptively analyzed by Excel 2019; the SPSS Modeler 18.0 Apriori algorithm was used to analyze the association rules of the prescriptions and mine the frequent item sets of acupoints; the SPSS 26.0 software was used to cluster the high-frequency acupoints, draw the pedigree diagram, and mine the clustering relationship between acupoints. Results: After strict screening according to the inclusion and exclusion criteria, a total of 133 medical records, 133 prescriptions, 21 acupoints involved, and a total frequency of 863 times were obtained. The top five acupoints in terms of frequency of use are back acupoints, cervical acupoints, lumbar acupoints, sacral acupoints, and abdominal plexus acupoints. Among the acupoint combinations, cervical acupoints, lumbar acupoints, and back acupoints have the strongest correlation; acupoints used more than 10 times can be divided into three effective clusters. Conclusion: Professor Ouyang Bowen treats chronic abdominal pain by regulating the autonomic nerves, focusing on the referred pain caused by visceral nerve sensitivity, and mainly uses spinal acupoints such as cervical acupoints, back acupoints, lumbar acupoints, and sacral acupoints. [ABSTRACT FROM AUTHOR]