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Machine Learning-De...
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Kobayashi, MasatakeUniversity Hospital of Nancy
(author)
Machine Learning-Derived Echocardiographic Phenotypes Predict Heart Failure Incidence in Asymptomatic Individuals
- Article/chapterEnglish2022
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LIBRIS-ID:oai:lup.lub.lu.se:b3894f90-0c70-470d-a1eb-53e8cd1e5049
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https://lup.lub.lu.se/record/b3894f90-0c70-470d-a1eb-53e8cd1e5049URI
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https://doi.org/10.1016/j.jcmg.2021.07.004DOI
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Language:English
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Summary in:English
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Subject category:art swepub-publicationtype
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Subject category:ref swepub-contenttype
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OBJECTIVES: This study sought to identify homogenous echocardiographic phenotypes in community-based cohorts and assess their association with outcomes.BACKGROUND: Asymptomatic cardiac dysfunction leads to a high risk of long-term cardiovascular morbidity and mortality; however, better echocardiographic classification of asymptomatic individuals remains a challenge.METHODS: Echocardiographic phenotypes were identified using K-means clustering in the first generation of the STANISLAS (Yearly non-invasive follow-up of Health status of Lorraine insured inhabitants) cohort (N = 827; mean age: 60 ± 5 years; men: 48%), and their associations with vascular function and circulating biomarkers were also assessed. These phenotypes were externally validated in the Malmö Preventive Project cohort (N = 1,394; mean age: 67 ± 6 years; men: 70%), and their associations with the composite of cardiovascular mortality (CVM) or heart failure hospitalization (HFH) were assessed as well.RESULTS: Three echocardiographic phenotypes were identified as "mostly normal (MN)" (n = 334), "diastolic changes (D)" (n = 323), and "diastolic changes with structural remodeling (D/S)" (n = 170). The D and D/S phenotypes had similar ages, body mass indices, cardiovascular risk factors, vascular impairments, and diastolic function changes. The D phenotype consisted mainly of women and featured increased levels of inflammatory biomarkers, whereas the D/S phenotype, consisted predominantly of men, displayed the highest values of left ventricular mass, volume, and remodeling biomarkers. The phenotypes were predicted based on a simple algorithm including e', left ventricular mass and volume (e'VM algorithm). In the Malmö cohort, subgroups derived from e'VM algorithm were significantly associated with a higher risk of CVM and HFH (adjusted HR in the D phenotype = 1.87; 95% CI: 1.04 to 3.37; adjusted HR in the D/S phenotype = 3.02; 95% CI: 1.71 to 5.34).CONCLUSIONS: Among asymptomatic, middle-aged individuals, echocardiographic data-driven classification based on the simple e'VM algorithm identified profiles with different long-term HF risk. (4th Visit at 17 Years of Cohort STANISLAS-Stanislas Ancillary Study ESCIF [STANISLASV4]; NCT01391442).
Subject headings and genre
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Huttin, OlivierUniversity Hospital of Nancy
(author)
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Magnusson, MartinLund University,Lunds universitet,Kardiovaskulär forskning - hypertoni,Forskargrupper vid Lunds universitet,WCMM- Wallenberg center för molekylär medicinsk forskning,Medicinska fakulteten,Cardiovascular Research - Hypertension,Lund University Research Groups,WCMM-Wallenberg Centre for Molecular Medicine,Faculty of Medicine(Swepub:lu)medf-mma
(author)
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Ferreira, João PedroUniversity Hospital of Nancy
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Bozec, ErwanUniversity Hospital of Nancy
(author)
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Huby, Anne-CecileUniversity Hospital of Nancy
(author)
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Preud'homme, GregoireUniversity Hospital of Nancy
(author)
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Duarte, KevinUniversity Hospital of Nancy
(author)
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Lamiral, ZohraUniversity Hospital of Nancy
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Dalleau, KevinUniversity of Lorraine
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Bresso, EmmanuelUniversity of Lorraine
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Smaïl-Tabbone, MalikaUniversity of Lorraine
(author)
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Devignes, Marie-DominiqueUniversity of Lorraine
(author)
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Nilsson, Peter MLund University,Lunds universitet,Enheten för medicinens historia,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Internmedicin - epidemiologi,Forskargrupper vid Lunds universitet,History of Medicine,Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Internal Medicine - Epidemiology,Lund University Research Groups,Skåne University Hospital(Swepub:lu)medf-pni
(author)
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Leosdottir, MargretLund University,Lunds universitet,Internmedicin - epidemiologi,Forskargrupper vid Lunds universitet,Internal Medicine - Epidemiology,Lund University Research Groups,Skåne University Hospital(Swepub:lu)medf-mle
(author)
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Boivin, Jean-MarcUniversity Hospital of Nancy
(author)
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Zannad, FaiezUniversity Hospital of Nancy
(author)
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Rossignol, PatrickUniversity Hospital of Nancy
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Girerd, NicolasUniversity Hospital of Nancy
(author)
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University Hospital of NancyKardiovaskulär forskning - hypertoni
(creator_code:org_t)
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STANISLAS study
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In:JACC: Cardiovascular Imaging: Elsevier BV15:2, s. 193-2081876-75911936-878X
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