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KMID : 1129720210380020100
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Korean Journal of Acupuncture
2021 Volume.38 No. 2 p.100 ~ p.109
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Characteristics of Source Acupoints: Data Mining of Clinical Trials Database
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Choi Dha-Hyun
Lee Seo-Young
Lee In-Seon
Ryu Yeon-Hee
Chae Youn-Byoung
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Abstract
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Objectives : Source acupoint is one of the representative acupoints to treat various diseases in each meridian. We aimed to identify the patterns of selection of Source acupoints and their associations with diseases using clinical trials data.
Methods : We extracted the frequency of Source acupoints across 30 diseases from clinical trials database. Acupuncture treatment regimens were retrieved from the Cochrane Database of Systematic Reviews. The frequency of Source acupoint use was calculated as the number of studies using a certain acupoint divided by the total number of included studies. Using hierarchical clustering and multidimensional scaling, the characteristics of Source acupoints were analyzed based on the similarity of the relationships between the Source acupoints and the diseases.
Results : A total of 421 clinical trials were included for this analysis. LR3, HT7, KI3, and LI4 acupoints were most frequently used for the treatment of 30 diseases. Cluster analysis showed that LR3 and LI4 acupoints were grouped together and HT7 and KI3 acupoints were grouped together. Multidimensional scaling revealed that LR3, LI4, HT7, and KI3 acupoints have intrinsic properties in the two-dimensional space.
Conclusions : The present study identified the selection patterns of the Source acupoints using clinical trials data. Our finding will provide the understanding of the characteristics of Source acupoints.
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KEYWORD
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clustering, data mining, indication, multidimensional scaling, Source acupoints
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