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dc.contributor.authorBenavente, Ernest Diez
dc.contributor.authorJimenez-Lopez, Francisco
dc.contributor.authorAttia, Zachi I.
dc.contributor.authorMalyutina, Sofia
dc.contributor.authorKudryavtsev, Alexander
dc.contributor.authorRyabikov, Andrey
dc.contributor.authorFriedman, Paul A.
dc.contributor.authorKapa, Suraj
dc.contributor.authorVoevoda, Michael
dc.contributor.authorPerel, Pablo
dc.contributor.authorSchirmer, Henrik
dc.contributor.authorHughes, Alun D.
dc.contributor.authorClark, Taane
dc.contributor.authorLeon, David A.
dc.date.accessioned2021-11-19T14:23:58Z
dc.date.available2021-11-19T14:23:58Z
dc.date.issued2021-01-25
dc.description.abstractBackground: A non-invasive, easy-to-access marker of accelerated cardiac ageing would provide novel insights into the mechanisms and aetiology of cardiovascular disease (CVD) as well as contribute to risk stratification of those who have not had a heart or circulatory event. Our hypothesis is that differences between an ECG-predicted and chronologic age of participants (δage) would reflect accelerated or decelerated cardiovascular ageing Methods: A convolutional neural network model trained on over 700,000 ECGs from the Mayo Clinic in the U.S.A was used to predict the age of 4,542 participants in the Know Your Heart study conducted in two cities in Russia (2015-2018). Thereafter, δage was used in linear regression models to assess associations with known CVD risk factors and markers of cardiac abnormalities. Results: The biomarker δage (mean: +5.32 years) was strongly and positively associated with established risk factors for CVD: blood pressure, body mass index (BMI), total cholesterol and smoking. Additionally, δage had strong independent positive associations with markers of structural cardiac abnormalities: N-terminal pro b-type natriuretic peptide (NT-proBNP), high sensitivity cardiac troponin T (hs-cTnT) and pulse wave velocity, a valid marker of vascular ageing. Conclusion: The difference between the ECG-age obtained from a convolutional neural network and chronologic age (δage) contains information about the level of exposure of an individual to established CVD risk factors and to markers of cardiac damage in a way that is consistent with it being a biomarker of accelerated cardiovascular (vascular) ageing. Further research is needed to explore whether these associations are seen in populations with different risks of CVD events, and to better understand the underlying mechanisms involved.en_US
dc.identifier.citationBenavente, Jimenez-Lopez, Attia, Malyutina, Kudryavtsev, Ryabikov, Friedman, Kapa, Voevoda, Perel, Schirmer, Hughes, Clark, Leon. Studying accelerated cardiovascular ageing in Russian adults through a novel deep-learning ECG biomarker. Wellcome Open Research. 2021;6:1-12en_US
dc.identifier.cristinIDFRIDAID 1950798
dc.identifier.doi10.12688/wellcomeopenres.16499.1
dc.identifier.issn2398-502X
dc.identifier.urihttps://hdl.handle.net/10037/23094
dc.language.isoengen_US
dc.publisherF1000Researchen_US
dc.relation.journalWellcome Open Research
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2021 The Author(s)en_US
dc.subjectVDP::Medical disciplines: 700::Basic medical, dental and veterinary science disciplines: 710en_US
dc.subjectVDP::Medisinske Fag: 700::Basale medisinske, odontologiske og veterinærmedisinske fag: 710en_US
dc.titleStudying accelerated cardiovascular ageing in Russian adults through a novel deep-learning ECG biomarkeren_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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