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Cardiac magnetic resonance characteristics and prognostic associations of hypertension-mediated left ventricular hypertrophy

Abstract:
Aims: Hypertension-mediated left ventricular hypertrophy (LVH) phenotypes: normal left ventricle (LV), LV remodelling, eccentric and concentric LVH have been reported using cardiac magnetic resonance (CMR). Although previous smaller studies have explored associations of these phenotypes with select CMR metrics, large population-based longitudinal data comparing their clinical trajectories are lacking. This study aimed to evaluate CMR characteristics across hypertension-mediated LVH phenotypes and their associations with incident cardiovascular outcomes. Methods and results: In the UK Biobank imaging cohort, 24 463 hypertensives were categorized into LVH phenotypes using CMR. Logistic regression models explored the relationship between phenotypes, setting normal LV as the reference, and CMR parameters as exposures. Cox proportional hazard models evaluated associations with incident major adverse cardiovascular events (MACE) and separately heart failure over a median follow-up of 4.9 years. Among the participants, 23 206 had normal LV, 889 LV remodelling, 253 eccentric and 115 concentric LVH. Hypertensives with eccentric LVH had the most impaired LV function using ejection fraction and strain, and those with concentric LVH had the highest T1 values and maximal wall thickness. Hypertensives with eccentric LVH were associated with a 2.5 times higher rate of MACE (HR 2.5, CI: 1.7–3.8) and 9 times higher heart failure event rates (HR 9.0, CI: 5.7–14.2). Hypertensives with concentric LVH had 4.1 times higher heart failure events rates (HR 4.1, CI: 1.8–9.3), and no association with MACE. Conclusion: In this large population study, we found distinct differences in CMR characteristics between hypertension-mediated LVH phenotypes with eccentric and concentric LVH exhibiting the worst prognosis.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/ehjimp/qyaf168

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Author
ORCID:
0000-0002-3217-780X
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Institution:
University of Oxford
Department:
Big Data Institute
Role:
Author
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Role:
Author
ORCID:
0000-0003-4130-5866


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Funder identifier:
https://ror.org/03x94j517
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Funder identifier:
https://ror.org/026zzn846
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Funder identifier:
https://ror.org/02wdwnk04
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Funder identifier:
https://ror.org/00b31g692


Publisher:
Oxford University Press
Journal:
European Heart Journal - Imaging Methods and Practice More from this journal
Volume:
4
Issue:
1
Article number:
qyaf168
Publication date:
2026-01-13
Acceptance date:
2025-12-30
DOI:
EISSN:
2755-9637
ISSN:
2755-9637


Language:
English
Keywords:
Pubs id:
2365686
UUID:
uuid_93366096-fb77-4a59-a7ba-7aa7c391baf8
Local pid:
pubs:2365686
Source identifiers:
3682648
Deposit date:
2026-01-21
ARK identifier:
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