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在心血管疾病的一级预防中,心脏代谢风险预测应该优于心血管风险评估。

Cardio-metabolic risk prediction should be superior to cardiovascular risk assessment in primary prevention of cardiovascular diseases.

机构信息

Centre of Preventive Cardiology of the 2nd Medical Department University Hospital, E. Benese 13, 305 99 Pilsen, Czech Republic.

出版信息

EPMA J. 2011 Mar;2(1):15-26. doi: 10.1007/s13167-011-0066-1. Epub 2011 Mar 5.

DOI:10.1007/s13167-011-0066-1
PMID:23199124
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3405365/
Abstract

Cardiovascular atherosclerotic diseases represent the main cause of death in the developed and developing populations. Although major progress has been made in the management of the classical modifiable cardiovascular risk factors, unhealthy lifestyle conduces to an increasing prevalence of overweight, obesity, metabolic disorders, type 2 diabetes mellitus, premature atherosclerosis and cardiovascular diseases. That is why cardio-metabolic risk prediction should be superior in the primary prevention of atherosclerosis and cardiovascular diseases. Up-to-date primary preventive strategies according to the European Guidelines, especially the high risk strategy approach, are being implemented. Individual cardiovascular and better cardio-metabolic risk assessment represents the basic approach in the individualized primary prevention of cardiovascular diseases and type 2 diabetes mellitus. Cardio-metabolic biomarkers, especially high sensitivity C-reactive protein, albuminuria, N-terminal pro-brain natriuretic peptide, and imaging procedures (carotid intima-media thickness measured by ultrasound) could improve the prediction of cardiovascular diseases and type 2 diabetes beyond that using traditional risk factors.

摘要

心血管动脉粥样硬化疾病是发达和发展中人群的主要死亡原因。尽管在管理经典可改变心血管危险因素方面取得了重大进展,但不良的生活方式导致超重、肥胖、代谢紊乱、2 型糖尿病、早发动脉粥样硬化和心血管疾病的患病率不断上升。这就是为什么心血管代谢风险预测应该在动脉粥样硬化和心血管疾病的一级预防中占主导地位。根据欧洲指南,最新的一级预防策略,特别是高危策略方法,正在实施。个体心血管和更好的心血管代谢风险评估是心血管疾病和 2 型糖尿病个体化一级预防的基本方法。心血管代谢生物标志物,特别是高敏 C 反应蛋白、白蛋白尿、氨基末端脑钠肽前体和影像学检查(超声测量颈动脉内膜中层厚度)可以提高心血管疾病和 2 型糖尿病的预测能力,超过传统风险因素的预测能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/181d/3405365/d00def43534c/13167_2011_66_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/181d/3405365/894d8c4c1072/13167_2011_66_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/181d/3405365/266e1cabd5d5/13167_2011_66_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/181d/3405365/d00def43534c/13167_2011_66_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/181d/3405365/894d8c4c1072/13167_2011_66_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/181d/3405365/266e1cabd5d5/13167_2011_66_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/181d/3405365/d00def43534c/13167_2011_66_Fig3_HTML.jpg

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