Investigating Acupoint Selection and Combinations of Acupuncture for Tic Disorders: An Association Rule Mining and Network Analysis Study

Abstract

ObjectiveTic disorders (TDs) are common mental disorders in children and adolescents, and the clinical application of acupuncture for treating TDs is becoming increasingly widespread. However, the criteria for selecting acupoint prescriptions and combinations have not been summarized. Therefore, data mining was used herein to determine the treatment principles and the most effective acupoint selection and compatibility criteria for the treatment of TDs.MethodsClinical studies and observations of the efficacy of acupuncture treatment for TDs were obtained from the PubMed, Cochrane Library, EMBASE, China National Knowledge Infrastructure (CNKI), Wanfang, VIP, and Chinese Biomedical (CBM) databases. The data on the acupoint prescriptions applied in these studies were collected, and network and association analyses were used to reveal the relationships between acupoints and to identify acupoint combinations. Additionally, the principles of acupuncture for TDs were determined through cluster analysis. Subgroup analysis of acupuncture prescriptions based on specific categorical diagnoses was performed to further assess the selection of acupoints.ResultsEighty-six trials were identified, and 257 groups of effective prescriptions involving 121 acupoints were extracted. Bai-hui (DU20), Feng-chi (GB20), Tai-chong (LR3), He-gu (LI4), and San-yin-jiao (SP6) were the most regularly used acupoints for treating TDs. The Governor Vessel, gallbladder, and large intestine meridians were more commonly used than other meridians. Moreover, most acupoint sites focused on the head and neck. Network analysis revealed potentially effective acupoint prescriptions for their commonly used acupoints, namely, Bai-hui (DU20), Si-shen-cong (EX-HN1), Feng-chi (GB20), Nei-guan (PC6), Shen-men (HT7), He-gu (LI4), Zu-san-li (ST36), San-yin-jiao (SP6) and Tai-chong (LR3). Association rule mining indicated that potential point combinations that should be prioritized in TD treatment are Bai-hui (DU20), Neiguan (PC6) and Sanyinjiao (SP6). Cluster analysis revealed the treatment principle of “coordinating yin and yang, tonifying qi and blood, dispelling pathogenic wind and eliminating phlegm”. The core acupoint prescription of TS treatment comprised He-gu (LI4), Feng-chi (GB20), Tai-chong (LR3), Bai-hui (DU20), Yin-tang (EX-HN3), Si-shen-cong (EX-HN1), San-yin-jiao (SP6), and Nei-guan (PC6). The core group included He-gu (LI4) and Feng-chi (GB20). Proximal points were usually used in TS as an additional method of point selection.ConclusionUsing data mining analysis of published studies, this study provides valuable information regarding the selection of the most effective acupoints and point combinations for clinical acupuncture practice for treating TDs.

Investigating acupoint selection and combinations of acupuncture for primary idiopathic tinnitus using data mining

“…The name of the entry acupoints was based on the World Health Organization’s Standard Acupuncture Point Location in the Western Pacific Region and the China National Standard “Naming and Positioning of Acupoints” (GB/T 12346-2006) as the standard. [ 13 ]…”

“…as the standard. [13] The revised Cochrane Risk of Bias Tool for Randomized Trials was used to assess the risk of bias of RCTs. The quality of included RCTs was assessed according to the following 5 domains: randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported result.…”

Analysis of Acupoint Selection and Combinations in Acupuncture Treatment of Carpal Tunnel Syndrome: A Protocol for Data Mining

“…Valid prescriptions will be extracted via the “a group of primary acupoints and a group of secondary acupoints constitute an acupoint prescription” strategy. 14 Referring to the “Study of Meridians and Collaterals”, 16 we will standardize the names of the acupoints included in the literature, and supplemented the attribution of meridians, site of the points, and the attribution of specific acupoints.…”

“…Data mining technology can help people find potentially useful information and knowledge in a large number of documents. 10 Based on these methods, previous studies investigated acupoint selection and combinations in acupuncture treatment of chronic stable angina pectoris, 11 obesity, 12 chemotherapy-induced peripheral neuropathy, 13 tic disorders, 14 and amyotrophic lateral sclerosis. 15 This study may provide evidence for the existence of specificity between the acupoints of different meridians and the fact that the benefits of acupuncture depend on the specificity of the acupoints.…”

Intelligent Acupuncture: Data-driven Revolution of Traditional Chinese Medicine

“…When combined with acupuncture knowledge, AI can efficiently handle large amounts of chaotic data and uncover hidden laws, patterns, and association rules that aid acupoint selection. Precision acupuncture prescriptions leveraging AI techniques are frequently used to select acupoints for a diverse range of illnesses, such as lower back pain [62] , primary osteoporosis [63] , and tic disorders [64] , as depicted in Figure 3.…”