2026-10-14T17:15:46Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33961405 2026-09-22T04:18:14Z category_363 portal_316 item_type_3 month_year_09_2026

Data Sheet 1_Data mining of acupoint selection and combination patterns for dysphagia with sialorrhea: a literature-based study.zip Haihan Zhang (299392) Yizhou Liu (1623016) Shikay Loong (25087195) Shangyu Wei (25087198) Yuze Wang (8408283) Wei Li (7081) Yu Feng (445691) Weidong Pan (1427614) Neurology and Neuromuscular Diseases acupuncture data mining dysphagia excessive salivation sialorrhea Background<p>Dysphagia accompanied by sialorrhea/drooling is clinically challenging, and acupuncture is frequently applied; however, standardized summaries of acupoint selection and combination patterns remain limited.</p>Methods<p>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.</p>Results<p>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).</p>Conclusion<p>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.</p> 2026-09-22T04:18:14Z Dataset Dataset 10.3389/fneur.2026.1849484.s001 https://figshare.com/articles/dataset/Data_Sheet_1_Data_mining_of_acupoint_selection_and_combination_patterns_for_dysphagia_with_sialorrhea_a_literature-based_study_zip/33961405 CC BY 4.0