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
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