[Rule of Clinical Application of Auricular Acupuncture Based on Data Mining]

Zhen Ci Yan Jiu. 2017 Feb 25;42(1):90-4.
[Article in Chinese]

Abstract

Objective: To explore the rule of clinical application of auricular acupuncture therapy by data mining in order to guide clinical practice.

Methods: The data base about single auricular acupuncture therapy for different clinical diseases was established by collection, sorting, screening, recording, collation, data extraction, statistic analysis on data samples from journals, academic theses dissertations published in near 60 years. The application rules of auricular therapy including its predominant diseases, stimulus modality, therapeutic effect, and angle of needling were summarized by data mining technique.

Results: Auricular acupuncture therapy has been widely and mostly used in the internal medicine department, accounting for 48.56%. Of stimulus modalities, auricular point paste and pressure is applied with the highest frequency, accounting for 64%. The highest effective rate is found in the surgery department diseases(81.41%). Pressure is the most effective stimulus in the internal medi-cine department, and bloodletting combined with paste and pressure in the surgery department, auricular point injection in the gynecology and pediatrics departments, bloodletting in the ophthalmology and otorhinolaryngology department, and auricular point incision in the dermatology department. Auricular point injection has remarkable effect. Bloodletting combined with paste and pressure has nearly the same effect as bloodletting in the same medical department except dematology department. Otherwise, angle of needling is rarely studied.

Conclusions: Auricular therapy is widely used and has remarkable effect in treating diseases by using different stimulus modalities. Whereas the angle of needling is rarely studied and future investigation is needed.

Publication types

  • Review

MeSH terms

  • Acupuncture Points
  • Acupuncture Therapy
  • Acupuncture, Ear*
  • Data Mining
  • Databases, Factual
  • Humans