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Integrative medicine using East Asian herbal medicine for inflammatory pain in patients with rheumatoid arthritis: A protocol for systematic review and meta-analysis integrated with multiple data mining for core candidate discoveryopen access

Authors
Jo, Hee-GeunSeo, JihyeBaek, EunhyeHwang, Ji-HyeLee, Donghun
Issue Date
Jun-2023
Publisher
LIPPINCOTT WILLIAMS & WILKINS
Keywords
bioinformatics; herbal medicine; integrative medicine; meta-analysis; rheumatoid arthritis; systematic review
Citation
MEDICINE, v.102, no.23
Journal Title
MEDICINE
Volume
102
Number
23
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/88485
DOI
10.1097/MD.0000000000033903
ISSN
0025-7974
1536-5964
Abstract
Background:Rheumatoid arthritis is a chronic inflammatory autoimmune disease characterized by a wide range of clinical symptoms affecting various bodily functions, including skeletal, vascular, metabolic, and cognitive functions. This review aimed to evaluate the efficacy and safety of integrative medicine (East Asian herbal medicine combined with conventional medicine) used for the treatment of inflammatory pain in rheumatoid arthritis and to identify key candidate drugs based on the data. Methods:A comprehensive literature search will be conducted in 4 core databases (PubMed, Excerpta Medica database, Cochrane Library, and Cumulative Index to Nursing & Allied Health Literature) 4 Korean databases (Oriental Medicine Advanced Searching Integrated System, Korean Studies Information Service System, Research Information Service System, and Korea Citation Index), 2 Chinese databases (Chinese National Knowledge Infrastructure Database and Wanfang data), and 1 Japanese database (Citation Information by National Institute of Informatics) for randomized controlled trials from December 13, 2022. Statistical analysis will be performed using R version 4.1.2 and R Studio program. The American College of Rheumatology 20/50/70 score and rate of adverse events will be the primary outcomes. All outcomes will be analyzed using a random-effects model to produce more statistically conservative results. Sensitivity, meta-regression, and subgroup analyses will be used to identify the sources of any heterogeneity in the study. The revised tool for assessing the risk of bias in randomized trials, version 2.0, will be used to evaluate methodological quality. The overall quality of evidence will be assessed according to the Grading of Recommendations Assessment, Development, and Evaluation Pro Framework. Ethics and dissemination:There are no ethical issues, as no primary data will be collected directly from the participants. The results of this review will be reported in a peer-reviewed scientific journal.
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