[Rules of acupoint selection for diabetic peripheral neuropathy based on data mining technology]

Area of Science:

• Traditional Chinese Medicine (TCM)
• Data Mining
• Neurology

Background:

• Diabetic peripheral neuropathy (DPN) is a common complication of diabetes.
• Acupuncture is a frequently used therapy for DPN management.
• Standardized acupoint selection protocols for DPN are lacking.

Purpose of the Study:

• To analyze acupoint selection rules for DPN using data mining.
• To identify frequently used acupoints and combinations for DPN acupuncture.
• To understand the underlying principles of acupoint selection in DPN treatment.

Main Methods:

• Literature retrieval from CNKI and Wanfang databases (2005-2014).
• Establishment of an acupuncture prescription database using TCM Inheritance Platform software.
• Application of data mining techniques, including rule analysis and revised mutual information.

Main Results:

• Zusanli (ST 36), Sanyinjiao (SP 6), Quchi (LI 11), Yanglingquan (GB 34), Hegu (LI 4), and Shenshu (BL 23) were the most frequently selected acupoints.
• Nineteen distinct acupoint combinations were identified.
• Reinforcing methods, blood, and qi circulation promotion were primary treatment rules.

Conclusions:

• Acupoint selection for DPN predominantly targets Yangming meridians and back-shu points.
• Data mining provides insights into evidence-based acupoint selection for DPN.
• Findings can inform standardized acupuncture protocols for DPN treatment.