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Statistical inference of acupoint specificity: forward and reverse inference.

Ye-Chae Hwang¹, Ye-Seul Lee², Yeonhee Ryu³

¹Acupuncture & Meridian Science Research Center, College of Korean Medicine, Kyung Hee University, Seoul, Republic of Korea.

Integrative Medicine Research

|March 21, 2020

Summary

Acupoint specificity in acupuncture is crucial. This study found that while acupoints can be specific to diseases, and diseases specific to acupoints, selection and indication specificity are not always the same.

Keywords:

Acupuncture Bayesian inference Indication Specificity

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Area of Science:

Acupuncture Research
Traditional Korean Medicine

Background:

Acupoint specificity is a key issue in acupuncture research and clinical practice.
Identifying specific acupoint-disease associations is essential for effective treatment.
This study investigates acupoint specificity using virtual diagnosis.

Purpose of the Study:

To identify the specificity of acupoint selection (forward inference).
To identify the specificity of acupoint indication (reverse inference).
To analyze the relationship between acupoint selection and indication specificity.

Main Methods:

Eighty Korean Medicine doctors performed virtual diagnoses on 10 case reports.
Forward inference: quantified prescribed acupoints for diseases, normalized using Z-scores for 30 acupoints.
Reverse inference: quantified diseases for acupoints, normalized using Z-scores for 10 diseases.

Main Results:

Forward inference confirmed acupoint selection specificity for each disease.
Reverse inference identified acupoint indication specificity for each acupoint.
Specificity of acupoint indication and selection were not always identical.

Conclusions:

Acupoint selection for a disease does not guarantee specific indications for that disease.
Clinical observation should guide the inference of acupoint indication specificity.
Further research is needed to understand the nuances of acupoint specificity.