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Acupoint selection pattern of chronic atrophic gastritis based on data mining methods of latent structure model and frequency item set

Abstract

OBJECTIVE:
To explore the acupoint selection pattern of chronic atrophic gastritis and provide reference for clinical treatment of chronic atrophic gastritis.

METHODS:
The literature regarding acupuncture for chronic atrophic gastritis published before September 5th of 2016 was searched in the databases of CNKI, CBM, PubMed, etc. The information of symptoms and acupoint selection was extracted to establish medical database of chronic atrophic gastritis. The data mining methods of latent structure model and frequency item set were applied to analyze the acupoint selection pattern of chronic atrophic gastritis.

RESULTS:
A total of 42 papers were collected in preliminary screening, and 32 papers were included, involving 604 medical cases. The data mining indicated 215 symptoms were involved in medical cases, including 16 high-frequency symptoms (stomach pain, stomach distension and hiccup, etc.), and the latent structure model of chronic atrophic gastritis symptoms was established. Fifty-two acupoints were identified, and high-frequency acupoints included Zusanli (ST 36), Zhongwan (CV 12), Neiguan (PC 6) and Weishu (BL 21), etc. Five frequency item sets of symptom-acupoint were identified, including stomach pain+stomach distension+Zusanli (ST 36)+Zhongwan (CV 12), etc. Six frequency item sets of symptom-syndrome-acupoint were identified, including stomach distension+dry mouth+dry defecation+insufficiency of stomach yin+Sanyinjiao (SP 6).

CONCLUSION:
Acupuncture for chronic atrophic gastritis selected Zusanli (ST 36), Zhongwan (CV 12) and Neiguan (PC 6) as main acupoints, and selected other acupoints based on clinical symptoms. This could provide reference for clinical treatment of chronic atrophic gastritis.

Autoren: Liu Y1, Gong H2, Liu J1, Zhang H1.

Publiziert in: Zhongguo Zhen Jiu. 2018 Jun 12;38(6):667-71. doi: 10.13703/j.0255-2930.2018.06.028.

Quelle: https://www.ncbi.nlm.nih.gov/pubmed/29972013

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