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Chinese herbal medicine injections (CHMIs) for chronic pulmonary heart disease: A protocol for a Bayesian network meta-analysis

BACKGROUND: Chinese herbal medicine injections (CHMIs) are frequently used for various refractory diseases including chronic pulmonary heart disease (CPHD). However, due to the diversity of CHMIs treatments, its relative effectiveness and safety remain unclear. In our study, Bayesian network meta-an...

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Autores principales: Lei, Yuping, Wang, Meili, Sun, Guiqiang, Liu, Yong, Yang, Yapei, Hao, Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7837975/
https://www.ncbi.nlm.nih.gov/pubmed/33546022
http://dx.doi.org/10.1097/MD.0000000000024128
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author Lei, Yuping
Wang, Meili
Sun, Guiqiang
Liu, Yong
Yang, Yapei
Hao, Dong
author_facet Lei, Yuping
Wang, Meili
Sun, Guiqiang
Liu, Yong
Yang, Yapei
Hao, Dong
author_sort Lei, Yuping
collection PubMed
description BACKGROUND: Chinese herbal medicine injections (CHMIs) are frequently used for various refractory diseases including chronic pulmonary heart disease (CPHD). However, due to the diversity of CHMIs treatments, its relative effectiveness and safety remain unclear. In our study, Bayesian network meta-analysis will be used to identify differences in efficacy and safety between diverse CHMI for CPHD. METHODS: Relevant randomized controlled trials (RCTs) and prospective controlled clinical trials published in PubMed, Google Scholar, Excerpt Medica Database, Medline, Cochrane Library, Web of Science, China Scientific Journal Database, China National Knowledge Infrastructure, Chinese Biomedical Literature Database and Wanfang Database will be systematic searched to identify eligible studies from their establishment to December 2020. The methodological qualities, including the risk of bias, will be evaluated using the Cochrane risk of bias assessment tool. Stata14.2 and WinBUGS 1.4.3 software were used for data synthesis. The evidentiary grade of the results will be also evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. RESULTS: The results of this study will be published in a peer-reviewed journal, and provide reliable evidence for different CHMIs on CPHD. CONCLUSIONS: The findings will provide reference for evaluating the efficacy and safety of different CHMIs for CPHD, and provide a helpful evidence for clinicians to formulate the best adjuvant treatment strategy for CPHD patients. TRIAL REGISTRATION NUMBER: INPLASY2020120004.
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spelling pubmed-78379752021-01-27 Chinese herbal medicine injections (CHMIs) for chronic pulmonary heart disease: A protocol for a Bayesian network meta-analysis Lei, Yuping Wang, Meili Sun, Guiqiang Liu, Yong Yang, Yapei Hao, Dong Medicine (Baltimore) 3800 BACKGROUND: Chinese herbal medicine injections (CHMIs) are frequently used for various refractory diseases including chronic pulmonary heart disease (CPHD). However, due to the diversity of CHMIs treatments, its relative effectiveness and safety remain unclear. In our study, Bayesian network meta-analysis will be used to identify differences in efficacy and safety between diverse CHMI for CPHD. METHODS: Relevant randomized controlled trials (RCTs) and prospective controlled clinical trials published in PubMed, Google Scholar, Excerpt Medica Database, Medline, Cochrane Library, Web of Science, China Scientific Journal Database, China National Knowledge Infrastructure, Chinese Biomedical Literature Database and Wanfang Database will be systematic searched to identify eligible studies from their establishment to December 2020. The methodological qualities, including the risk of bias, will be evaluated using the Cochrane risk of bias assessment tool. Stata14.2 and WinBUGS 1.4.3 software were used for data synthesis. The evidentiary grade of the results will be also evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. RESULTS: The results of this study will be published in a peer-reviewed journal, and provide reliable evidence for different CHMIs on CPHD. CONCLUSIONS: The findings will provide reference for evaluating the efficacy and safety of different CHMIs for CPHD, and provide a helpful evidence for clinicians to formulate the best adjuvant treatment strategy for CPHD patients. TRIAL REGISTRATION NUMBER: INPLASY2020120004. Lippincott Williams & Wilkins 2021-01-22 /pmc/articles/PMC7837975/ /pubmed/33546022 http://dx.doi.org/10.1097/MD.0000000000024128 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0
spellingShingle 3800
Lei, Yuping
Wang, Meili
Sun, Guiqiang
Liu, Yong
Yang, Yapei
Hao, Dong
Chinese herbal medicine injections (CHMIs) for chronic pulmonary heart disease: A protocol for a Bayesian network meta-analysis
title Chinese herbal medicine injections (CHMIs) for chronic pulmonary heart disease: A protocol for a Bayesian network meta-analysis
title_full Chinese herbal medicine injections (CHMIs) for chronic pulmonary heart disease: A protocol for a Bayesian network meta-analysis
title_fullStr Chinese herbal medicine injections (CHMIs) for chronic pulmonary heart disease: A protocol for a Bayesian network meta-analysis
title_full_unstemmed Chinese herbal medicine injections (CHMIs) for chronic pulmonary heart disease: A protocol for a Bayesian network meta-analysis
title_short Chinese herbal medicine injections (CHMIs) for chronic pulmonary heart disease: A protocol for a Bayesian network meta-analysis
title_sort chinese herbal medicine injections (chmis) for chronic pulmonary heart disease: a protocol for a bayesian network meta-analysis
topic 3800
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7837975/
https://www.ncbi.nlm.nih.gov/pubmed/33546022
http://dx.doi.org/10.1097/MD.0000000000024128
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