AnHong Da, Chunhong Luo, Yihao Zhou, Gan Huang, Zhilin Huang, Xuelian Zhang, Meifang Liu, Jing Shi, Youlong Xiong
{"title":"Acupoint selection rules for acupoint application in lung diseases in the post-epidemic era","authors":"AnHong Da, Chunhong Luo, Yihao Zhou, Gan Huang, Zhilin Huang, Xuelian Zhang, Meifang Liu, Jing Shi, Youlong Xiong","doi":"10.53388/tmrim202206002","DOIUrl":null,"url":null,"abstract":"Objective: To summarize the rules of acupoint selection of acupoint application to prevent and treat lung diseases under the background the post-epidemic era using data-mining technology. Method: The CNKI, Wanfang database, and VIP database were searched for clinical study articles on lung diseases treated by acupoint application published in the past 5 years. Data-eligible papers were extracted to establish a database of acupoint application for lung disease using Microsoft Excel 2019, with the goal of analyzing the frequency of acupoints, acupoint-meridian association, acupoint-location association, specific acupoint frequency, and cluster analysis. Association rules, consisting of acupoints with an application frequency of ≥ 10, were devised by the Apriori algorithm to explore the correlation between acupoint groups and to analyze the rules of the compatibility of acupoint prescriptions. Results: A total of 229 eligible papers met our inclusion criteria. Forty-seven acupoints were applied, for a total frequency of acupoints of 1,035 times. Among these, acupoints for lung diseases were primarily distributed in the back-and-waist and chest-and-abdomen areas. From the analysis of the association rules, we obtained four groups of acupoint association rules based on acupoint clusters with a frequency ≥ 10 and found that Feishu (BL 13), Tiantu (CV 22), Dazhui (GV 14), Dingchuan (EX-B1), and Danzhong (CV 17) constitute the core acupoints of prescriptions for clinical acupoint application to prevent and treat lung diseases. Conclusion: It is clearly shown that the core acupoints are relatively concentrated and that the selected acupoints were mainly locally selected, which could be a matching reference for the long-term prevention and treatment of lung diseases, including COVID-19.","PeriodicalId":70680,"journal":{"name":"TMR整合医学","volume":"100 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"TMR整合医学","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.53388/tmrim202206002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: To summarize the rules of acupoint selection of acupoint application to prevent and treat lung diseases under the background the post-epidemic era using data-mining technology. Method: The CNKI, Wanfang database, and VIP database were searched for clinical study articles on lung diseases treated by acupoint application published in the past 5 years. Data-eligible papers were extracted to establish a database of acupoint application for lung disease using Microsoft Excel 2019, with the goal of analyzing the frequency of acupoints, acupoint-meridian association, acupoint-location association, specific acupoint frequency, and cluster analysis. Association rules, consisting of acupoints with an application frequency of ≥ 10, were devised by the Apriori algorithm to explore the correlation between acupoint groups and to analyze the rules of the compatibility of acupoint prescriptions. Results: A total of 229 eligible papers met our inclusion criteria. Forty-seven acupoints were applied, for a total frequency of acupoints of 1,035 times. Among these, acupoints for lung diseases were primarily distributed in the back-and-waist and chest-and-abdomen areas. From the analysis of the association rules, we obtained four groups of acupoint association rules based on acupoint clusters with a frequency ≥ 10 and found that Feishu (BL 13), Tiantu (CV 22), Dazhui (GV 14), Dingchuan (EX-B1), and Danzhong (CV 17) constitute the core acupoints of prescriptions for clinical acupoint application to prevent and treat lung diseases. Conclusion: It is clearly shown that the core acupoints are relatively concentrated and that the selected acupoints were mainly locally selected, which could be a matching reference for the long-term prevention and treatment of lung diseases, including COVID-19.