An Apriori Algorithm-Based Association Rule Analysis to Identify Herb Combinations for Treating Uremic Pruritus Using Chinese Herbal Bath Therapy.
Journal
Evidence-based complementary and alternative medicine : eCAM
ISSN: 1741-427X
Titre abrégé: Evid Based Complement Alternat Med
Pays: United States
ID NLM: 101215021
Informations de publication
Date de publication:
2020
2020
Historique:
received:
29
09
2020
revised:
23
10
2020
accepted:
24
10
2020
entrez:
10
12
2020
pubmed:
11
12
2020
medline:
11
12
2020
Statut:
epublish
Résumé
Uremic pruritus (UP) is prevalent among patients with end-stage renal disease (ESRD), which causes severe itching and affects their quality of life. Additionally, patients experience fatigue and depression, and an increased risk of mortality has also been reported. A meta-analysis of 17 randomized controlled trials (RCTs) has indicated that Chinese herbal bath therapy (CHBT) had adjuvant benefits in improving UP in ESRD patients, and previous studies have reported that herb combinations were more useful than treatment with a single herb. Association rule analysis has been used to evaluate potential correlations between herb combinations, and Apriori algorithms are one of the most powerful machine-learning algorithms available for identifying associations within databases. Therefore, we used the Apriori algorithm to analyze association rules of potential core herb combinations for use in CHBT for UP treatment using data from a meta-analysis of 17 RCTs that used CHBT for UP treatment. Data on 43 CHBT herbs were extracted from 17 RCTs included for analysis and we found 19 association rules. The results indicated that the following herb combinations {Chuanxiong, Baijili} ≥ {Dahuang} and {Dahuang, Baijili} ≥ {Chuanxiong} were most strongly associated, implying that these herb combinations represent potential CHBT treatments for UP.
Identifiants
pubmed: 33299462
doi: 10.1155/2020/8854772
pmc: PMC7704140
doi:
Types de publication
Journal Article
Langues
eng
Pagination
8854772Informations de copyright
Copyright © 2020 Ping-Hsun Lu et al.
Déclaration de conflit d'intérêts
The authors declare that there are no conflicts of interest regarding the publication of this article.
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