The relationship between quantitative epicardial adipose tissue based on CT and coronary artery disease

医学 冠状动脉疾病 科克伦图书馆 内科学 脂肪组织 动脉 心脏病学 梅德林 临床意义 荟萃分析 放射科 政治学 法学
作者
Baohua Wu,Zhuanqin Ren,Zhengang Du,Lei Zhang,Bin Hou
出处
期刊:Medicine [Wolters Kluwer]
卷期号:99 (51): e23729-e23729 被引量:2
标识
DOI:10.1097/md.0000000000023729
摘要

Abstract Background: Epicardial adipose tissue (EAT) is a kind of visceral adipose tissue with close proximity to coronary artery and myocardium, which can secrete cell factor, and influence the physiological function and pathophysiological process of myocardium and coronary artery. Clinical imaging diagnosis showed that the volume and thickness of EAT exists a certain relevance with coronary artery disease, but it lacked evidence of evidence-based medicine. The research on the implementation of this program will systematically evaluate the relationship of computed tomography (CT) quantitative EAT and coronary artery disease. Method: The English databases (Embase, PubMed, the Cochrane Library, Web of Science) and Chinese database (CNKI, Wanfang, China biomedical database, VIP) of computer retrieval has collected the case control clinical study of relationship between EAT and coronary artery disease from the establishment of the database to October 2020, which was conducted extraction and quality evaluation by 2 researchers independently for data included in the study, and was conducted Meta-analysis for the included literature by adopting RevMan5.3 software. Result: The research evaluated the correlation between EAT and coronary artery disease through the EAT thickness, EAT volume, and other indexes. Conclusion: The research has provided reliable evidence-based evidence for the correlation between CT EAT quantification and coronary artery disease. Ethics and dissemination: We will not publish private information from individuals. This kind of systematic review does not involve harming the rights of participants. No ethical approval was required. The results can be published in peer-reviewed journals or at relevant conferences. OSF Registration number: DOI 10.17605/OSF.IO/DVQNE
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