Frontiers in neurology · 2026
Data mining of acupoint selection and combination patterns for dysphagia with sialorrhea: a literature-based study.
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Zhang Haihan, Liu Yizhou, Loong Shikay, Wei Shangyu, Wang Yuze, Li Wei, Feng Yu, Pan Weidong
Аннотация
BACKGROUND: Dysphagia accompanied by sialorrhea/drooling is clinically challenging, and acupuncture is frequently applied; however, standardized summaries of acupoint selection and combination patterns remain limited.
METHODS: Eight databases were searched from inception to May 2025. Clinical publications reporting acupuncture prescriptions for dysphagia with sialorrhea/drooling were included. One representative prescription was extracted from each eligible article (124 articles; 124 prescriptions). Acupoint names were normalized according to the GB/T standard terminology. Descriptive statistics were used to summarize acupoint frequency, meridian distribution, and commonly used acupoint categories. Association rule mining was performed using the Apriori algorithm (SPSS Modeler 18.0), and a co-occurrence network was visualized in Cytoscape to identify core nodes and stable combinations.
RESULTS: A total of 124 prescriptions containing 179 unique acupoints were extracted (1,070 total acupoint occurrences). The most frequently used acupoints included CV23, GB20, EX-HN12, EX-HN13, GV20, LI4, and ST36. Association rules and network analysis revealed stable co-occurrence structures, highlighting several high-connectivity acupoints and recurring pairs/sets (e.g., CV23-GB20; EX-HN12-EX-HN13; ST4-ST6, where applicable).
CONCLUSION: Literature-based prescription data mining identified commonly used acupoints and reproducible co-occurrence patterns for dysphagia with sialorrhea. These findings provide a quantitative basis for acupoint selection and may inform the development of standardized clinical protocols, as well as future prospective validation.
METHODS: Eight databases were searched from inception to May 2025. Clinical publications reporting acupuncture prescriptions for dysphagia with sialorrhea/drooling were included. One representative prescription was extracted from each eligible article (124 articles; 124 prescriptions). Acupoint names were normalized according to the GB/T standard terminology. Descriptive statistics were used to summarize acupoint frequency, meridian distribution, and commonly used acupoint categories. Association rule mining was performed using the Apriori algorithm (SPSS Modeler 18.0), and a co-occurrence network was visualized in Cytoscape to identify core nodes and stable combinations.
RESULTS: A total of 124 prescriptions containing 179 unique acupoints were extracted (1,070 total acupoint occurrences). The most frequently used acupoints included CV23, GB20, EX-HN12, EX-HN13, GV20, LI4, and ST36. Association rules and network analysis revealed stable co-occurrence structures, highlighting several high-connectivity acupoints and recurring pairs/sets (e.g., CV23-GB20; EX-HN12-EX-HN13; ST4-ST6, where applicable).
CONCLUSION: Literature-based prescription data mining identified commonly used acupoints and reproducible co-occurrence patterns for dysphagia with sialorrhea. These findings provide a quantitative basis for acupoint selection and may inform the development of standardized clinical protocols, as well as future prospective validation.