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Comparative efficacy and safety of traditional Chinese patent medicine for cognitive dysfunction in diabetic cognitive dysfunction: A protocol for systematic review and Bayesian network meta-analysis
BACKGROUND: More and more studies have shown that cognitive dysfunction is one of the main complications of diabetes. The disorder of glucose and lipid metabolism seriously damages brain function and accelerates the conversion to dementia. At present, there are no drugs that can directly treat diabe...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8913128/ https://www.ncbi.nlm.nih.gov/pubmed/35451386 http://dx.doi.org/10.1097/MD.0000000000028946 |
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author | Wang, Kai Jiang, Zhenyuan Yu, Xiaowen Shao, Yuze Liu, Hailiang Wu, Susu Kong, Linghui Wang, Zhonglin |
author_facet | Wang, Kai Jiang, Zhenyuan Yu, Xiaowen Shao, Yuze Liu, Hailiang Wu, Susu Kong, Linghui Wang, Zhonglin |
author_sort | Wang, Kai |
collection | PubMed |
description | BACKGROUND: More and more studies have shown that cognitive dysfunction is one of the main complications of diabetes. The disorder of glucose and lipid metabolism seriously damages brain function and accelerates the conversion to dementia. At present, there are no drugs that can directly treat diabetic cognitive dysfunction. All drugs for the treatment of this disease achieve the purpose of treatment through strict control of blood sugar levels. This method has great limitations. Traditional Chinese patent medicines (TCPMs) work through multiple targets and multiple pathways, which can not only effectively correct the state of glucose and lipid metabolism disorders, but also significantly improve cognitive ability, but there is a lack of systematic evaluation of their effectiveness and safety. We use the method of network meta-analysis to systematically and comprehensively compare the effectiveness and safety of different Chinese patent medicines. METHODS: We will comprehensively search the following databases, including Web of Science, PubMed, The Cochrane Library, EMBASE, China National Knowledge Infrastructure, Chinese Scientific Journals Database, Wanfang database and China BioMedical Literature. We will include all randomized controlled trials that meet the inclusion criteria, starting from the establishment of the database until September 2021. Two researchers will independently screen the literature based on inclusion criteria. While extracting data, we also assess the risk of bias in the included studies. All the data and evidence obtained will be evaluated by the method of Bayesian network meta-analysis. RESULTS: This study will evaluate the effectiveness and safety of various TCPMs for diabetic cognitive dysfunction. CONCLUSION: The results of this study will provide valuable references for the clinical application of TCPMs, and assist clinicians in formulating more reasonable diagnosis and treatment strategies. ETHICS AND DISSEMINATION: This study does not require ethical approval. INTERNATIONAL PLATFORM OF REGISTERED SYSTEMATIC REVIEW AND META-ANALYSIS PROTOCOLS REGISTRATION NUMBER: INPLASY202190008. |
format | Online Article Text |
id | pubmed-8913128 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-89131282022-03-15 Comparative efficacy and safety of traditional Chinese patent medicine for cognitive dysfunction in diabetic cognitive dysfunction: A protocol for systematic review and Bayesian network meta-analysis Wang, Kai Jiang, Zhenyuan Yu, Xiaowen Shao, Yuze Liu, Hailiang Wu, Susu Kong, Linghui Wang, Zhonglin Medicine (Baltimore) 5300 BACKGROUND: More and more studies have shown that cognitive dysfunction is one of the main complications of diabetes. The disorder of glucose and lipid metabolism seriously damages brain function and accelerates the conversion to dementia. At present, there are no drugs that can directly treat diabetic cognitive dysfunction. All drugs for the treatment of this disease achieve the purpose of treatment through strict control of blood sugar levels. This method has great limitations. Traditional Chinese patent medicines (TCPMs) work through multiple targets and multiple pathways, which can not only effectively correct the state of glucose and lipid metabolism disorders, but also significantly improve cognitive ability, but there is a lack of systematic evaluation of their effectiveness and safety. We use the method of network meta-analysis to systematically and comprehensively compare the effectiveness and safety of different Chinese patent medicines. METHODS: We will comprehensively search the following databases, including Web of Science, PubMed, The Cochrane Library, EMBASE, China National Knowledge Infrastructure, Chinese Scientific Journals Database, Wanfang database and China BioMedical Literature. We will include all randomized controlled trials that meet the inclusion criteria, starting from the establishment of the database until September 2021. Two researchers will independently screen the literature based on inclusion criteria. While extracting data, we also assess the risk of bias in the included studies. All the data and evidence obtained will be evaluated by the method of Bayesian network meta-analysis. RESULTS: This study will evaluate the effectiveness and safety of various TCPMs for diabetic cognitive dysfunction. CONCLUSION: The results of this study will provide valuable references for the clinical application of TCPMs, and assist clinicians in formulating more reasonable diagnosis and treatment strategies. ETHICS AND DISSEMINATION: This study does not require ethical approval. INTERNATIONAL PLATFORM OF REGISTERED SYSTEMATIC REVIEW AND META-ANALYSIS PROTOCOLS REGISTRATION NUMBER: INPLASY202190008. Lippincott Williams & Wilkins 2022-03-11 /pmc/articles/PMC8913128/ /pubmed/35451386 http://dx.doi.org/10.1097/MD.0000000000028946 Text en Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc. https://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 (https://creativecommons.org/licenses/by/4.0/) |
spellingShingle | 5300 Wang, Kai Jiang, Zhenyuan Yu, Xiaowen Shao, Yuze Liu, Hailiang Wu, Susu Kong, Linghui Wang, Zhonglin Comparative efficacy and safety of traditional Chinese patent medicine for cognitive dysfunction in diabetic cognitive dysfunction: A protocol for systematic review and Bayesian network meta-analysis |
title | Comparative efficacy and safety of traditional Chinese patent medicine for cognitive dysfunction in diabetic cognitive dysfunction: A protocol for systematic review and Bayesian network meta-analysis |
title_full | Comparative efficacy and safety of traditional Chinese patent medicine for cognitive dysfunction in diabetic cognitive dysfunction: A protocol for systematic review and Bayesian network meta-analysis |
title_fullStr | Comparative efficacy and safety of traditional Chinese patent medicine for cognitive dysfunction in diabetic cognitive dysfunction: A protocol for systematic review and Bayesian network meta-analysis |
title_full_unstemmed | Comparative efficacy and safety of traditional Chinese patent medicine for cognitive dysfunction in diabetic cognitive dysfunction: A protocol for systematic review and Bayesian network meta-analysis |
title_short | Comparative efficacy and safety of traditional Chinese patent medicine for cognitive dysfunction in diabetic cognitive dysfunction: A protocol for systematic review and Bayesian network meta-analysis |
title_sort | comparative efficacy and safety of traditional chinese patent medicine for cognitive dysfunction in diabetic cognitive dysfunction: a protocol for systematic review and bayesian network meta-analysis |
topic | 5300 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8913128/ https://www.ncbi.nlm.nih.gov/pubmed/35451386 http://dx.doi.org/10.1097/MD.0000000000028946 |
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