[Acupoint selection rules of acupuncture for cervical spondylotic radiculopathy based on data mining].

Objective: To analyze the rules of acupoint selection in the acupuncture treatment of cervical spondylotic radiculopathy by data mining.

Methods: The randomized controlled trials (RCTs) regarding acupuncture for cervical spondylotic radiculopathy published from July 15 of 2009 to July 15 of 2019 were retrieved from databases of CNKI, VIP, Wanfang, SinoMed, PubMed and EMbase. A database was established with Microsoft Excel 2016. The frequency and total effective rate of high-frequency acupoints, meridians and acupoint combinations were analyzed, and the association rules of acupoints and meridians were analyzed by Apriori algorithm.

Results: A total of 87 RCTs were included, involving 104 acupoints with a total frequency of 921. Among them, the high-frequency acupoints were cervical Jiaji (EX-B 2, 87 times), Fengchi (GB 20, 70 times), Houxi (SI 3, 54 times), etc. The frequently-used acupoints were mainly distributed in the hand large intestine meridian, the foot gallbladder meridian and hand small intestine meridian. The frequently-used acupoint combination was Fengchi (GB 20)-cervical Jiaji (EX-B 2), and most of the combinations were acupoints at the proximal end and acupoints at the far and near end. With the analysis of association rules, 15 groups of acupoint association rules and meridian association rules were obtained.

Conclusion: It is feasible to explore the acupoint selection and compatibility rules of acupuncture for cervical spondylotic radiculopathy by data mining. This study could provide corresponding reference for clinical treatment.