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Commonality and Specificity of Acupuncture Point Selections
Ye-Seul Lee1, Yeonhee Ryu2, Da-Eun Yoon3
1Department of Anatomy and Acupoint, College of Korean Medicine, Gachon University, Seongnam, Republic of Korea.
Evidence-Based Complementary and Alternative Medicine : Ecam
|August 18, 2020
Summary
This study reveals common and specific acupoint selections for various diseases. Clinician-based virtual diagnoses identified patterns, suggesting a bottom-up approach for better understanding acupoint associations.
Area of Science:
- Acupuncture research
- Traditional Korean Medicine
- Medical data analysis
Background:
- Identifying specific acupoint indications for diseases is challenging.
- Classical texts and top-down approaches define acupoint selection.
- A need exists for data-driven insights into acupoint usage.
Purpose of the Study:
- To reveal commonalities and specificities in acupoint selection.
- To analyze acupoint prescriptions based on virtual diagnoses.
- To explore data-driven patterns in clinical acupoint usage.
Main Methods:
- Eighty Korean Medicine doctors prescribed acupoints for 10 virtual cases.
- Prescribed acupoints were quantified and normalized using z-scores.
- Hierarchical cluster and network analyses categorized disease-acupoint patterns.
Main Results:
- ST36, LI4, and LR3 were the most frequently prescribed acupoints.
- Cluster A (musculoskeletal) favored local acupoints.
- Cluster B (psychiatric) and C (internal medicine) showed distinct acupoint preferences.
Conclusions:
- Common and specific acupoint selection patterns were identified.
- Virtual diagnoses provide a bottom-up approach to understanding acupoint usage.
- This method complements traditional top-down approaches in acupuncture research.
