Study on the Pattern of Acupoint Selection for Treating Post-Stroke Hiccups Based on Data Mining
Year: 2024
Type: conference-paper
Abstract: Purpose: To analyze the acupuncture point selection patterns for treating hiccups after stroke based on data mining. Method: We searched three major Chinese databases, China National Knowledge Infrastructure (CNKI), Wanfang Data, and VIP Chinese Science and Technology Journals Database since their establishment for published literature on acupuncture treatment of post-stroke hiccups. Literature was screened according to inclusion and exclusion criteria, and Python programming language was used for data analysis of selected acupoints. Results: A total of 144 articles meeting the criteria were selected, involving 81 acupoints with a total frequency of 774 uses. The top ten acupoints, each used more than five times, are Neiguan (121 times), Zusanli (107 times), Zhongwan (84 times), Cuanzhu (45 times), Danzhong (44 times), Taichong (41 times), Geshu (41 times), Hegu (21 times), Sanyinjiao (20 times), Baihui (19 times); there were 20 acupoint combinations with usage frequencies of 28 or more; nine strong association rules were obtained, among which "Zusanli-Neiguan" had the highest support. Conclusion: The thought process behind selecting meridians and points for acupuncture treatment of post-stroke hiccups centers on regulating the spleen and stomach Qi, supplemented by methods like nourishing Yang and supplementing deficiency, relieving chest tightness and depression. The Stomach Meridian, Conception Vessel, and Bladder Meridian are the primary channels, with acupoint selection based on Zusanli, Neiguan, and Zhongwan as the foundational combination, adjusted according to syndrome differentiation, and limb acupoints are commonly used.
Authors: Kaikai Jia, Qi Xiong, Qifeng Lou, Wanxu Pu, Xitao Yue, Li Su, Yuanjun Zou
Institution: Changchun University of Chinese Medicine
Language: English
Subfield: Physiology
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W4411028901