[The rules of acupoint selection of acupuncture and moxibustion for scrofula in ancient times]

Abstract

Based on data mining technology, the rules of acupoint selection of acupuncture-moxibustion for scrofula in ancient times were analyzed. The relevant articles of acupuncture and moxibustion for scrofula were searched in the Chinese Medical Code, and the original article, acupoint name, acupoint characteristic, and acupoint meridian tropism, etc. were screened and extracted. The Microsoft Excel 2019 was used to establish a acupoint prescription database, and the frequency of acupoints as well as their meridian tropism and characteristics were analyzed. The SPSS21.0 was applied to perform cluster analysis of acupuncture prescriptions; the SPSS Modeler 18.0 was used to perform the association rules analysis of the neck and the chest-armpit acupoints, respectively. As a result, 314 acupuncture prescriptions were extracted, including 236 single-acupoint prescriptions and 78 multiple-acupoints prescriptions (53 for neck and 25 for chest-armpit). A total of 54 acupoints were involved, with a total frequency of 530. The top 3 commonly-used acupoints were Tianjing (TE 10), Zulinqi (GB 41) and Taichong (LR 3); the most commonly-used meridians were hand shaoyang meridian, foot shaoyang meridian, hand yangming meridian and foot yangming meridian; the most commonly-used special acupoints were he-sea points and shu-stream points. The cluster analysis obtained 6 clusters, and the association rule analysis obtained that the core prescriptions of the neck were Quchi (LI 11), Jianyu (LI 15), Tianjing (TE 10) and Jianjing (GB 21), while the core prescriptions of the chest-armpit were Daling (PC 7), Yanglingquan (GB 34), Danzhong (CV 17), Jianjing (GB 21), Waiguan (TE 5), Zhigou (TE 6), Yuanye (GB 22) and Zhangmen (LR 13). The core prescriptions obtained from association rule analysis by difference areas were basically consistent with those by cluster analysis of total prescriptions.

Keywords: acupoint selection rules; acupuncture and moxibustion; data mining; scrofula.