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Combination of Acupoints in Treating Patients with Chronic Obstructive Pulmonary Disease: An Apriori Algorithm-Based Association Rule Analysis

机译:穴位与治疗慢性阻塞性肺病患者的组合:基于APRiori算法的关联规则分析

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Chronic obstructive pulmonary disease (COPD) is highly prevalent and a major burden on the healthcare system worldwide. It has a severe impact on patients due to poor health-related quality of life (HRQL), dyspnea, and exertional intolerance. Our previous meta-analysis revealed that body acupuncture therapy had adjuvant benefits of improving HRQL in COPD patients undergoing optimal medical treatment. Previous studies indicated that treatment with combinations of acupoints was more effective than single acupoint treatment. The association rule analysis has been widely used to explore relationships in acupoint combination. Therefore, we aimed to investigate the potential core acupoint combination in COPD treatment by mining the association rules from the retrieved randomized control trials (RCTs) of the previous meta-analyses. This study was conducted based on Apriori algorithm-based association rule analysis, which is a popular data mining method available in software R. We extracted acupoints as binary data from the 12 included RCTs for analysis. There were 27 acupoints extracted from 12 RCTs. The top 10 frequently selected acupoints were BL12, BL13, BL20, BL23, BL43, CV17, EXB1, LU5, LU7, and ST36. We investigated 2444 association rules, and the results showed that {ST36, BL12}?≥?{CV17}, {ST36, BL12}?≥?{EXB1}, {CV17, BL12}?≥?{ST36}, and {EXB1, BL12}?≥?{ST36} were the most associated rules in the retrieved RCTs. The acupoint combinations of ST36, BL12, and CV17 and ST36, BL12, and EXB1 could be considered as the core of acupoint combination for further acupuncture treatment of COPD.
机译:慢性阻塞性肺病(COPD)在全球医疗保健系统方面具有普遍性,主要负担。由于健康相关的生活质量差(HRQL),呼吸困难和担保不耐受,它对患者产生严重影响。我们以前的荟萃分析表明,身体针灸治疗对接受最佳治疗的COPD患者的HRQL具有辅助益处。以前的研究表明,穴位组合的治疗比单一穴位治疗更有效。关联规则分析已被广泛用于探索穴位组合中的关系。因此,我们旨在通过从先前的荟萃分析的检索的随机对照试验(RCT)中挖掘关联规则来研究COPD治疗中的潜在核心穴位组合。本研究是基于基于APRIORI算法的关联规则分析进行的,这是一种流行的数据挖掘方法,它在软件R中提供。我们将acupoint提取为来自12的二进制数据包括RCT用于分析。从12个RCT中提取了27个穴位。前10个经常选择的穴位是BL12,BL13,BL20,BL23,BL43,CV17,EXB1,LU5,LU7和ST36。我们调查了2444个关联规则,结果表明:{ST36,BL12}?≥?{CV17},{ST36,BL12}?≥?{exB1},{CV17,BL12}?≥?{ST36},和{EXB1 ,BL12}?≥?{ST36}是检索到的RCT中最相关的规则。 ST36,BL12和CV17和ST36,BL12和EXB1的穴位组合可以被认为是穴位组合的核心,用于进一步针灸治疗COPD。

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