Exploring the incremental utility of circulating biomarkers for robust risk prediction of incident atrial fibrillation in European cohorts using regressions and modern machine learning methods.
Betül ToprakStephanie BrandtJan BredereckeFrancesco GianfagnaJulie K K Vishram-NielsenFrancisco M OjedaSimona CostanzoChristin S BörschelStefan SöderbergIoannis KatsoularisStephan CamenErkki VartiainenMaria Benedetta DonatiJukka KonttoMartin BobakEllisiv B MathiesenAllan LinnebergWolfgang KoenigMaja-Lisa LøchenAugusto Di CastelnuovoStefan BlankenbergGiovanni de GaetanoKari KuulasmaaVeikko V SalomaaLicia IacovielloTeemu J NiiranenTanja ZellerRenate B SchnabelPublished in: Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology (2023)
Using different variable selection procedures including ML methods, NT-proBNP consistently remained the strongest blood-based predictor of incident AF and ranked before classical cardiovascular risk factors. The clinical benefit of these findings for identifying at-risk individuals for targeted AF screening needs to be elucidated and tested prospectively.