Evidence map›Paper›PMID 41862470›Full record

Articlenpj aging2026

Electrocardiogram derived heart age models agreement, accuracy and predictive ability in the Tromsø study.

Arya Panthalanickal Vijayakumar, Tom Wilsgaard, Henrik Schirmer, Ernest Diez Benavente, René van Es, Rutger R van de Leur, Haakon Lindekleiv, Zachi I Attia, Francisco Lopez-Jimenez, David A Leon and 1 more

Abstract read
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In one paragraph

Article in npj aging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Arya Panthalanickal VijayakumarDepartment of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway. arya.p.vijayakumar@uit.no.
Tom WilsgaardDepartment of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway.
Henrik SchirmerAkershus University Hospital, Lørenskog, Norway.
Ernest Diez BenaventeDepartment of Experimental Cardiology University Medical Center Utrecht, Utrecht, The Netherlands.
René van EsDepartment of Cardiology University Medical Center Utrecht, Utrecht, The Netherlands.
Rutger R van de LeurDepartment of Cardiology University Medical Center Utrecht, Utrecht, The Netherlands.
Haakon LindekleivDepartment of Radiology, University Hospital of North, Oslo, Norway.
Zachi I AttiaMayo Clinic College of Medicine, Rochester, MN, USA.
Francisco Lopez-JimenezMayo Clinic College of Medicine, Rochester, MN, USA.
David A LeonDepartment of Noncommunicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Olena IakunchykovaDepartment of Psychology, University of Oslo, Oslo, Norway.

Funding

Helse Nord RHF HNF1636-22
6 · The paper itself

Abstract

Convolutional neural networks (CNNs) can estimate electrocardiogram (ECG)-based heart age. We compared three published CNNs in the Tromsø Study cohort (7,108 participants) for accuracy, agreement, and prognostic value. Mean absolute error versus chronological age was 6.8, 7.8, and 6.4 years. Correlations with age were ~0.71-0.73 and agreement across CNNs was high (overall ICC 0.86). Using Cox models, we estimated hazard ratios per SD of δ-age (ECG age minus chronological age) for myocardial infarction, stroke, cardiovascular mortality, and all-cause mortality; discrimination was quantified by cross-validated C-index. δ-age predicted higher risk across outcomes; associations were strongest for δ-age

Identifiers

PMID41862470
PMCPMC13223277

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.