Evidence map›Paper›PMID 40638553›Full record

ArticlePLoS computational biology2025

Anatomical-electrical coupling of cardiac axes: Definitions and population variability for advancing personalised ECG interpretation.

Mohammad Kayyali, Ana Mincholé, Shuang Qian, Alistair Young, Devran Ugurlu, Elliot Fairweather, Steven Niederer, John Whitaker, Martin Bishop, Pablo Lamata

Abstract read
In one paragraph

Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

10 authors.

Mohammad KayyaliSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.ORCID 0009-0004-9830-8050
Ana MincholéBSICoS, I3A, IIS Aragon, University of Zaragoza, Zaragoza, Spain.
Shuang QianSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.ORCID 0000-0002-2313-0268
Alistair YoungSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Devran UgurluSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Elliot FairweatherSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Steven NiedererNational Heart and Lung Institute, Imperial College London, London, United Kingdom.
John WhitakerSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.ORCID 0000-0002-5361-5725
Martin BishopSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Pablo LamataSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.ORCID 0000-0002-3097-4928

Funding

The Cardiac Atlas ProjectR01HL121754 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MCCULLOCH, ANDREW D., OMENS, JEFFREY H. · 2014 to 2023
$5.0M
British Heart Foundation (BHF) PG/18/74/34077British Heart Foundation (BHF) PG/22/10871British Heart Foundation (BHF) PG/22/11159NHLBI NIH HHS R01 HL121754NIH HHS RO1 HL121754Wellcome TrustWellcome Trust WT203148/Z/16/Z
6 · The paper itself

Abstract

Electrocardiogram (ECG) recordings are affected by the heart's three-dimensional orientation within the thorax, i.e., the anatomical axis. Various cardiac conditions can cause the anatomical axis to shift and/or alter the pattern of electrical activation, leading to changes in the electrical axis. Nevertheless, there remains a lack of a formal, population-level study of the interplay between the cardiac anatomical and electrical axes and the factors that affect them. In this context, this study aimed to: (1) propose standardised definitions for the cardiac anatomical and electrical axes, (2) characterise their population-wide interplay in healthy conditions, (3) evaluate the impact of hypertension on their distribution and (4) identify associations with phenotypical and disease characteristics. Using cardiac magnetic resonance images and 12-lead ECGs from ~39,000 UK Biobank participants, patient-specific, paired biventricular geometries and vectorcardiograms were constructed. Five anatomical and four electrical axis definitions were computed, with the optimal pair of definitions selected based on their mutual alignment in 3D space within 28,000 healthy subjects. Accordingly, the anatomical axis was defined as the vector from the apex to the spatial centre of the four valves, and the electrical axis as the direction of the maximum QRS dipole. Mean angular separation in 3D, [Formula: see text], was 145.0° ± 16.8° in the healthy cohort. The electrical axes exhibited a much larger variability, and strong evidence of anatomical-electrical coupling was identified. Increasing BMI notably affected the anatomical axis, rotating the heart more horizontally-a pattern mirrored by the electrical axis. Both axes were also significantly influenced by sex and, to a lesser extent, age. The axes were then studied in the sub-cohort of ~3,500 UK BioBank participants with primary hypertension, where a similar rotational pattern as that with increasing BMI was revealed. Finally, phenome-wide association studies in the 39,000 participants reveal associations between the axes angular metrics and phenotypes signalling an increased afterload, and an association to hypertension among other clinical conditions. These findings underscore the complex anatomical-electrical interplay and highlight the potential of cardiac axes biomarkers for an improved clinical ECG interpretation and disease characterisation.

Indexed as

ElectrocardiographyHeartAdultAgedComputational BiologyFemaleHumansHypertensionMagnetic Resonance ImagingMaleMiddle AgedModels, CardiovascularUnited Kingdom

Identifiers

PMID40638553
PMCPMC12244483

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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.