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已发表论文
耳穴选穴规律用于膝骨关节炎疼痛缓解：系统综述和数据挖掘分析
Authors Li Y , Zhang X, Liu M, Wang Y, Shen Z, Shan Y
Received 17 September 2025
Accepted for publication 13 January 2026
Published 21 January 2026 Volume 2026:19 568124
DOI https://doi.org/10.2147/JPR.S568124
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Houman Danesh
Yawen Li,1,2 Xinyue Zhang,2 Mengnan Liu,1,2 Yin Wang,2 Zhongming Shen,1 Yawei Shan1,2
1Department of Nursing, Guanghua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China; 2School of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
Correspondence: Yawei Shan, Department of Nursing, Guanghua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 1508, Yan’an West Road, Shanghai, 200050, People’s Republic of China, Tel +86 17601260156, Email yaweishan78280@163.com Zhongming Shen, Department of Nursing, Guanghua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 1508, Yan’an West Road, Shanghai, 200050, People’s Republic of China, Tel +86 13918892898, Email 2585527314@qq.com
Objective: To systematically evaluate randomized controlled trials of auricular therapy for knee osteoarthritis pain and to explore acupoint selection patterns using data mining techniques.
Methods: Eleven Chinese and English databases were searched from inception to September 1, 2025. Eligible randomized controlled trials were screened and assessed for methodological quality. Descriptive statistics, frequency analysis, association rule mining, and hierarchical cluster analysis were applied to identify commonly used auricular points and their combinations.
Results: Thirty-six studies involving 3,105 participants were included. Study quality was moderate, with frequent shortcomings in blinding and allocation reporting. The most frequently used acupoints were Shenmen (TF4), Xi (AH4), Jiaogan (AH6a), Pizhixia (AT4), Gan (CO12), and Shen (CO10). Association rule analysis showed Shenmen (TF4)–Pizhixia (AT4) as the most frequent co-occurring pair (support = 97.22%), while Neifenmi (CO18)–Shenshangxian (TG2p) and Shenmen (TF4)–Shenshangxian (TG2p) exhibited the strongest association (lift = 3.15). Cluster analysis identified three synergistic groups: Cluster 1: Shenmen (TF4), Xi (AH4), Jiaogan (AH6a), and Pizhixia (AT4), linked to nerve regulation; Cluster 2: Gan (CO12) and Shen (CO10), associated with zang-fu organ function; and Cluster 3: Yidan (CO11), Xin (CO15), Fei (CO14), Pi (CO13), and Sanjiao (CO17), functioning as adjunctive regulators.
Conclusion: Auricular therapy for knee osteoarthritis pain relief shows promising patterns in acupoint selection that align with both Traditional Chinese Medicine and neurophysiological mechanisms. Despite encouraging results, interpretation should be cautious due to methodological limitations, protocol heterogeneity, and the exploratory nature of data mining. Future research should include rigorously designed, preregistered RCTs with standardized intervention protocols and transparent reporting to validate these findings and evaluate clinical effectiveness.
Keywords: osteoarthritis of knee, auricular therapy, acupoint selection, traditional Chinese medicine, pain management, systematic review, data mining
1Department of Nursing, Guanghua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China; 2School of Nursing, Shanghai University of Traditional Chinese Medicine, Shanghai, People’s Republic of China
Correspondence: Yawei Shan, Department of Nursing, Guanghua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 1508, Yan’an West Road, Shanghai, 200050, People’s Republic of China, Tel +86 17601260156, Email yaweishan78280@163.com Zhongming Shen, Department of Nursing, Guanghua Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 1508, Yan’an West Road, Shanghai, 200050, People’s Republic of China, Tel +86 13918892898, Email 2585527314@qq.com
Objective: To systematically evaluate randomized controlled trials of auricular therapy for knee osteoarthritis pain and to explore acupoint selection patterns using data mining techniques.
Methods: Eleven Chinese and English databases were searched from inception to September 1, 2025. Eligible randomized controlled trials were screened and assessed for methodological quality. Descriptive statistics, frequency analysis, association rule mining, and hierarchical cluster analysis were applied to identify commonly used auricular points and their combinations.
Results: Thirty-six studies involving 3,105 participants were included. Study quality was moderate, with frequent shortcomings in blinding and allocation reporting. The most frequently used acupoints were Shenmen (TF4), Xi (AH4), Jiaogan (AH6a), Pizhixia (AT4), Gan (CO12), and Shen (CO10). Association rule analysis showed Shenmen (TF4)–Pizhixia (AT4) as the most frequent co-occurring pair (support = 97.22%), while Neifenmi (CO18)–Shenshangxian (TG2p) and Shenmen (TF4)–Shenshangxian (TG2p) exhibited the strongest association (lift = 3.15). Cluster analysis identified three synergistic groups: Cluster 1: Shenmen (TF4), Xi (AH4), Jiaogan (AH6a), and Pizhixia (AT4), linked to nerve regulation; Cluster 2: Gan (CO12) and Shen (CO10), associated with zang-fu organ function; and Cluster 3: Yidan (CO11), Xin (CO15), Fei (CO14), Pi (CO13), and Sanjiao (CO17), functioning as adjunctive regulators.
Conclusion: Auricular therapy for knee osteoarthritis pain relief shows promising patterns in acupoint selection that align with both Traditional Chinese Medicine and neurophysiological mechanisms. Despite encouraging results, interpretation should be cautious due to methodological limitations, protocol heterogeneity, and the exploratory nature of data mining. Future research should include rigorously designed, preregistered RCTs with standardized intervention protocols and transparent reporting to validate these findings and evaluate clinical effectiveness.
Keywords: osteoarthritis of knee, auricular therapy, acupoint selection, traditional Chinese medicine, pain management, systematic review, data mining