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An Apriori Algorithm-Based Association Analysis of Analgesic Drugs in Chinese Medicine Prescriptions Recorded From Patients With Rheumatoid Arthritis Pain

Chronic pain, a common symptom of people with rheumatoid arthritis, usually behaves as persistent polyarthralgia pain and causes serious damage to patients' physical and mental health. Opioid analgesics can lead to a series of side effects like drug tolerance and addiction. Thus, seeking an alt...

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Autores principales: Lai, Wei-dong, Li, Dian-ming, Yu, Jie, Huang, Lin, Zheng, Ming-zhi, Jiang, Yue-peng, Wang, Song, Wen, Jun-jun, Chen, Si-jia, Wen, Cheng-ping, Jin, Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9358686/
https://www.ncbi.nlm.nih.gov/pubmed/35959238
http://dx.doi.org/10.3389/fpain.2022.937259
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author Lai, Wei-dong
Li, Dian-ming
Yu, Jie
Huang, Lin
Zheng, Ming-zhi
Jiang, Yue-peng
Wang, Song
Wen, Jun-jun
Chen, Si-jia
Wen, Cheng-ping
Jin, Yan
author_facet Lai, Wei-dong
Li, Dian-ming
Yu, Jie
Huang, Lin
Zheng, Ming-zhi
Jiang, Yue-peng
Wang, Song
Wen, Jun-jun
Chen, Si-jia
Wen, Cheng-ping
Jin, Yan
author_sort Lai, Wei-dong
collection PubMed
description Chronic pain, a common symptom of people with rheumatoid arthritis, usually behaves as persistent polyarthralgia pain and causes serious damage to patients' physical and mental health. Opioid analgesics can lead to a series of side effects like drug tolerance and addiction. Thus, seeking an alternative therapy and screening out the corresponding analgesic drugs is the key to solving the current dilemma. Traditional Chinese Medicine (TCM) therapy has been recognized internationally for its unique guiding theory and definite curative effect. In this study, we used the Apriori Algorithm to screen out potential analgesics from 311 cases that were treated with compounded medication prescription and collected from “Second Affiliated Hospital of Zhejiang Chinese Medical University” in Hangzhou, China. Data on 18 kinds of clinical symptoms and 16 kinds of Chinese herbs were extracted based on this data mining. We also found 17 association rules and screened out four potential analgesic drugs—“Jinyinhua,” “Wugong,” “Yiyiren,” and “Qingfengteng,” which were promised to help in the clinical treatment. Besides, combined with System Cluster Analysis, we provided several different herbal combinations for clinical references.
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spelling pubmed-93586862022-08-10 An Apriori Algorithm-Based Association Analysis of Analgesic Drugs in Chinese Medicine Prescriptions Recorded From Patients With Rheumatoid Arthritis Pain Lai, Wei-dong Li, Dian-ming Yu, Jie Huang, Lin Zheng, Ming-zhi Jiang, Yue-peng Wang, Song Wen, Jun-jun Chen, Si-jia Wen, Cheng-ping Jin, Yan Front Pain Res (Lausanne) Pain Research Chronic pain, a common symptom of people with rheumatoid arthritis, usually behaves as persistent polyarthralgia pain and causes serious damage to patients' physical and mental health. Opioid analgesics can lead to a series of side effects like drug tolerance and addiction. Thus, seeking an alternative therapy and screening out the corresponding analgesic drugs is the key to solving the current dilemma. Traditional Chinese Medicine (TCM) therapy has been recognized internationally for its unique guiding theory and definite curative effect. In this study, we used the Apriori Algorithm to screen out potential analgesics from 311 cases that were treated with compounded medication prescription and collected from “Second Affiliated Hospital of Zhejiang Chinese Medical University” in Hangzhou, China. Data on 18 kinds of clinical symptoms and 16 kinds of Chinese herbs were extracted based on this data mining. We also found 17 association rules and screened out four potential analgesic drugs—“Jinyinhua,” “Wugong,” “Yiyiren,” and “Qingfengteng,” which were promised to help in the clinical treatment. Besides, combined with System Cluster Analysis, we provided several different herbal combinations for clinical references. Frontiers Media S.A. 2022-07-25 /pmc/articles/PMC9358686/ /pubmed/35959238 http://dx.doi.org/10.3389/fpain.2022.937259 Text en Copyright © 2022 Lai, Li, Yu, Huang, Zheng, Jiang, Wang, Wen, Chen, Wen and Jin. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Pain Research
Lai, Wei-dong
Li, Dian-ming
Yu, Jie
Huang, Lin
Zheng, Ming-zhi
Jiang, Yue-peng
Wang, Song
Wen, Jun-jun
Chen, Si-jia
Wen, Cheng-ping
Jin, Yan
An Apriori Algorithm-Based Association Analysis of Analgesic Drugs in Chinese Medicine Prescriptions Recorded From Patients With Rheumatoid Arthritis Pain
title An Apriori Algorithm-Based Association Analysis of Analgesic Drugs in Chinese Medicine Prescriptions Recorded From Patients With Rheumatoid Arthritis Pain
title_full An Apriori Algorithm-Based Association Analysis of Analgesic Drugs in Chinese Medicine Prescriptions Recorded From Patients With Rheumatoid Arthritis Pain
title_fullStr An Apriori Algorithm-Based Association Analysis of Analgesic Drugs in Chinese Medicine Prescriptions Recorded From Patients With Rheumatoid Arthritis Pain
title_full_unstemmed An Apriori Algorithm-Based Association Analysis of Analgesic Drugs in Chinese Medicine Prescriptions Recorded From Patients With Rheumatoid Arthritis Pain
title_short An Apriori Algorithm-Based Association Analysis of Analgesic Drugs in Chinese Medicine Prescriptions Recorded From Patients With Rheumatoid Arthritis Pain
title_sort apriori algorithm-based association analysis of analgesic drugs in chinese medicine prescriptions recorded from patients with rheumatoid arthritis pain
topic Pain Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9358686/
https://www.ncbi.nlm.nih.gov/pubmed/35959238
http://dx.doi.org/10.3389/fpain.2022.937259
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