Revolutionizing cardiovascular risk prediction in patients with chronic kidney disease: machine learning and large-scale proteomic risk prediction model lead the way
Author:
Affiliation:
1. Division of Cardiology, Department of Medicine, Montreal Heart Institute, University of Montreal , 5000 Belanger Street, Montréal, QC H1T 1C8 , Canada
Funder
‘Fonds de la recherche en santé du Québec»
Publisher
Oxford University Press (OUP)
Subject
Cardiology and Cardiovascular Medicine
Link
https://academic.oup.com/eurheartj/article-pdf/44/23/2111/50660276/ehad127.pdf
Reference9 articles.
1. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization;Go;N Engl J Med,2004
2. Dapagliflozin in patients with chronic kidney disease;Heerspink;N Engl J Med,2020
3. Cardiovascular disease in chronic kidney disease;Jankowski;Circulation,2021
4. 2013 ACC/AHA guideline on the assessment of cardiovascular risk;Goff;Circulation,2014
5. Framingham and American College of Cardiology/American Heart Association pooled cohort equations, high-sensitivity troponin T, and N-terminal pro-brain-type natriuretic peptide for predicting atherosclerotic cardiovascular events across the spectrum of kidney dysfunction;Lidgard;J Am Heart Assoc,2022
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