Evidence map›Paper›PMID 41853838›Full record

ArticleHypertension (Dallas, Tex. : 1979)2026

Development and Validation of the AI-HeartAge Model in Framingham and UK Biobank.

Timothy J Korzinski, Brenton R Prescott, David J Hamel-Sellman, Vanessa Xanthakis, Leroy L Cooper, Naomi M Hamburg, Connie W Tsao, Emelia J Benjamin, Ramachandran S Vasan, Gary F Mitchell

Abstract readValidation Study
In one paragraph

Article in Hypertension (Dallas, Tex. : 1979), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Timothy J KorzinskiCardiovascular Engineering, Inc, MA (T.J.K., D.J.H.-S., G.F.M.).ORCID 0009-0001-1298-3943
Brenton R PrescottSection of Preventive Medicine and Epidemiology, Department of Medicine (B.R.P., V.X.), Boston University Chobanian & Avedisian School of Medicine, Boston, MA.ORCID 0000-0002-3805-9070
David J Hamel-SellmanCardiovascular Engineering, Inc, MA (T.J.K., D.J.H.-S., G.F.M.).ORCID 0009-0000-1086-1048
Vanessa XanthakisSection of Preventive Medicine and Epidemiology, Department of Medicine (B.R.P., V.X.), Boston University Chobanian & Avedisian School of Medicine, Boston, MA.ORCID 0000-0002-7352-621X
Leroy L CooperBiology Department, Vassar College, Poughkeepsie, NY (L.L.C.).ORCID 0000-0001-9764-0837
Naomi M HamburgWhitaker Cardiovascular Institute (N.M.H., E.J.B.), Boston University Chobanian & Avedisian School of Medicine, Boston, MA.ORCID 0000-0001-5504-5589
Connie W TsaoDepartment of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA (C.W.T.).ORCID 0000-0003-3104-0681
Emelia J BenjaminWhitaker Cardiovascular Institute (N.M.H., E.J.B.), Boston University Chobanian & Avedisian School of Medicine, Boston, MA.ORCID 0000-0003-4076-2336
Ramachandran S VasanBoston University and NHLBI's Framingham Study, Framingham, MA (V.X., E.J.B., R.S.V.).ORCID 0000-0001-7357-5970
Gary F MitchellCardiovascular Engineering, Inc, MA (T.J.K., D.J.H.-S., G.F.M.).ORCID 0000-0001-5643-3145

Funding

FRAMINGHAM HEART STUDY - YEAR 5 EXAM75N92019D00031 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · 2019 to 2024
$29.8M
IDENTIFICATION OF COMMON GENETIC VARIANTS FOR ATRIAL FIBRILLATION AND PR INTERVALR01HL092577 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI BENJAMIN, EMELIA J., ELLINOR, PATRICK THOMAS · 2009 to 2025
$20.6M
ConProject-006U54HL120163 · NHLBI · AMERICAN HEART ASSOCIATION · PI BHATNAGAR, ARUNI, ROBERTSON, ROSE MARIE · 2018 to 2022
$18.8M
Cardiac microstructure and the immune-inflammatory response to SARS-CoV-2R01HL131532 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI CHENG, SUSAN, LI, DEBIAO · 2016 to 2025
$6.6M
Myocardial Radiomics and Mechanics in the Pathology and Prognosis of Cardiovascular DiseaseR01HL155717 · NHLBI · BETH ISRAEL DEACONESS MEDICAL CENTER · PI TSAO, CONNIE · 2021 to 2025
$4.1M
Mediators of Systemic Inflammation and Heart Failure Risk in the CommunityR01HL143227 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI CHENG, SUSAN · 2019 to 2022
$3.3M
CAPSITE: Community Assessment of Pain and Sensitization in the ElderlyR01AG066010 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BENJAMIN, EMELIA J., EDWARDS, ROBERT R · 2020 to 2025
$3.3M
Ventricular-vascular coupling in the elderly: lifecourse determinants, trajectories, and prognostic significanceR01HL142983 · NHLBI · UNIVERSITY OF TEXAS HLTH SCIENCE CENTER · PI CHENG, SUSAN, MITCHELL, GARY FRANK · 2019 to 2022
$3.2M
Endothelial Cell Health Across the Spectrum of Cardiometabolic DiseaseR01HL168889 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI Naomi Miriam Hamburg, Jennifer E Ho · 2023 to 2026
$3.1M
Mitochondrial Dynamics and UCP2 - Endothelial Dysfunction in Human ObesityR01HL115391 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI HAMBURG, NAOMI MIRIAM · 2013 to 2017
$2.8M
Vascular Stiffness as a Precursor of Hypertension in a Middle-aged CohortR01HL126136 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI MITCHELL, GARY FRANK, RAMACHANDRAN, VASAN S · 2015 to 2018
$2.6M
Aortic Dysfunction, Pulsatile Stress and Target Organ Damage in FraminghamR01HL107385 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI MITCHELL, GARY FRANK, RAMACHANDRAN, VASAN S · 2011 to 2014
$2.6M
NHLBI NIH HHS 75N92019D00031NHLBI NIH HHS HHSN268201500001CNHLBI NIH HHS HHSN268201500001INHLBI NIH HHS K01 HL161494NHLBI NIH HHS N01 HC025195NHLBI NIH HHS R01 HL070100NHLBI NIH HHS R01 HL092577NHLBI NIH HHS R01 HL093328NHLBI NIH HHS R01 HL107385NHLBI NIH HHS R01 HL115391NHLBI NIH HHS R01 HL126136NHLBI NIH HHS R01 HL131532NHLBI NIH HHS R01 HL142983NHLBI NIH HHS R01 HL143227NHLBI NIH HHS R01 HL155717NHLBI NIH HHS R01 HL168889NHLBI NIH HHS U54 HL120163NIA NIH HHS R01 AG066010NIA NIH HHS R01 AG079390NIA NIH HHS RF1 AG079390NIDDK NIH HHS R01 DK080739
6 · The paper itself

Abstract

backgroundArterial pressure waveform shape conveys information regarding interactions between the left ventricle and aorta that could provide an estimate of biological heart age and cardiovascular disease (CVD) risk.

methodsArtificial intelligence heart age (AI-HA) was estimated by averaging results from 2 convolutional neural networks trained to predict mitral annulus tissue Doppler e' and s' peak velocities using an uncalibrated arterial tonometry or photoplethysmography waveform as input. Models were developed using FHS (Framingham Heart Study) participant pressure waveforms and echocardiographic measurements (N=6916 participants, 38 174 waveforms, 56% women, mean age 61±12). We validated AI-HA using Cox modeling in an FHS holdout set of baseline radial waveforms (N=7018, 54% women, age 50±16 years) and in UK Biobank participants (N=67 986, 53% women, age 57±8 years).

resultsIn FHS (up to 10 years of follow-up, 148 heart failure [HF] and 331 CVD events), using models that adjusted for PREVENT (AHA Predicting Risk of CVD Events) risk factors, AI-HA was associated with incident HF (hazard ratio, 2.09 [CI, 1.64-2.68]; continuous net reclassification, 0.22 [CI, 0.13-0.30]) and CVD (hazard ratio, 1.52 [CI, 1.28-1.81]; continuous net reclassification, 0.13 [CI, 0.07-0.20]). In UK Biobank (up to 10 years of follow-up, 1408 HF and 2709 CVD events), AI-HA was associated with incident HF (hazard ratio, 1.23 [CI, 1.13-1.33]; continuous net reclassification, 0.09 [CI, 0.06-0.12]) and CVD (hazard ratio, 1.22 [CI, 1.15-1.30]; continuous net reclassification, 0.08 [CI, 0.06-0.09]).

conclusionsAI-HA is a novel and accessible measure of left ventricle function and HF risk in community-based samples.

Indexed as

Artificial IntelligenceCardiovascular DiseasesHeart FailureAdultAgedArterial PressureBiological Specimen BanksFemaleHumansMaleMiddle AgedRisk AssessmentUK BiobankUnited Kingdomaortaarterial pressurecardiovascular diseaseheart failurerisk factors

Identifiers

PMID41853838
PMCPMC13004166

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