Targeted proteomics improves cardiovascular risk prediction in secondary prevention

Targeted proteomics improves cardiovascular risk prediction in secondary prevention

AIMS: Current risk scores do not accurately identify patients at highest risk of recurrent atherosclerotic cardiovascular disease (ASCVD) in need of more intensive therapeutic interventions. Advances in high-throughput plasma proteomics, analysed with machine learning techniques, may offer new oppor...

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Bibliographic Details
Main Authors:	Belo Pereira, J.P (Author), Bom, M.J (Author), Catapano, A.L (Author), de Kleijn, D. (Author), Hoefer, I.E (Author), Hoogeveen, R.M (Author), Knaapen, P. (Author), Koenig, W. (Author), Kraaijenhof, J.M (Author), Kroon, J. (Author), Levin, E. (Author), Nurmohamed, N.S (Author), Stroes, E.S.G (Author), Timmerman, N. (Author), Visseren, F.L.J (Author), Waissi, F. (Author)
Format:	Article
Language:	English
Published:	NLM (Medline) 2022
Subjects:	ASCVD atherosclerosis Atherosclerosis brain ischemia Brain Ischemia C reactive protein cardiovascular disease Cardiovascular Diseases cerebrovascular accident C-reactive protein C-Reactive Protein Heart Disease Risk Factors human Humans Machine learning NLRP3 procedures proteomics Proteomics risk assessment Risk Assessment risk factor Risk Factors Risk score secondary prevention Secondary Prevention Stroke
Online Access:	View Fulltext in Publisher

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