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Exploring spatial patterns of acupoint indications from clinical data: A STROBE-compliant article
Every acupoint has specific indications for acupuncture treatment. These indications, primarily established based on the meridian system, have spatial patterns of symptoms on the human body. We investigated the associations between acupoints and symptom locations in 75 patients with chronic pain who...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer Health
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5413274/ https://www.ncbi.nlm.nih.gov/pubmed/28445309 http://dx.doi.org/10.1097/MD.0000000000006768 |
Sumario: | Every acupoint has specific indications for acupuncture treatment. These indications, primarily established based on the meridian system, have spatial patterns of symptoms on the human body. We investigated the associations between acupoints and symptom locations in 75 patients with chronic pain who were asked to sketch the localization of their symptoms on body schemes using the bodily sensation map (BSM) system. Combining the BSM and clinical information, we estimated the statistical parameters of relationships between acupoints and spatial information on symptoms. We further visualized spatial patterns of indications of the representative acupoints on the human body template using a Z score. Using a statistical parametric map method, we observed significant activation patterns of 12 acupoint indications with spatial patterns. The 1st group of patterns was distant from the acupoint locus and was strongly associated with the route of the corresponding meridian. The 2nd group was found around the acupoint locus, the majority of which was located at the trunk or back areas. Intensive investigations of the spatial patterns of acupoint indications would be a novel paradigm to explain point specificity of acupuncture treatment based on the original concept of the meridian system. Future studies should include more meaningful clinical data with larger sample sizes. |
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