Evidence map›Paper›PMID 40468351›Full record

ArticleCardiovascular diabetology2025

Sex-specific cardiometabolic multimorbidity, metabolic syndrome and left ventricular function in heart failure with preserved ejection fraction in the UK Biobank.

Ambre Bertrand, Xin Zhou, Andrew Lewis, Thomas Monfeuga, Ramneek Gupta, Vicente Grau, Blanca Rodriguez

Abstract readMulticenter StudyComparative Study
In one paragraph

Article in Cardiovascular diabetology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
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

7 authors.

Ambre BertrandComputational Cardiovascular Science Group, Department of Computer Science, University of Oxford, Oxford, OX1 3QD, UK. ambre.bertrand@cs.ox.ac.uk.
Xin ZhouComputational Cardiovascular Science Group, Department of Computer Science, University of Oxford, Oxford, OX1 3QD, UK.
Andrew LewisDivision of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, OX3 9DU, UK.
Thomas MonfeugaNovo Nordisk Research Centre Oxford Ltd, Roosevelt Drive, Headington, Oxford, OX3 7FZ, UK.
Ramneek GuptaNovo Nordisk Research Centre Oxford Ltd, Roosevelt Drive, Headington, Oxford, OX3 7FZ, UK.
Vicente GrauDepartment of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, OX3 7DQ, UK.
Blanca RodriguezComputational Cardiovascular Science Group, Department of Computer Science, University of Oxford, Oxford, OX1 3QD, UK. blanca.rodriguez@cs.ox.ac.uk.

Funding

British Heart Foundation FS/ICRF/24/26111British Heart Foundation Oxford Centre for Research Excellence RE/18/3/34214EPSRC Centre for Doctoral Training in Health Data Science EP/S02428X/1EPSRC project CompBioMed X EP/X019446/1Oxford-Bristol Myers Squibb Fellowship R39207/CN063Wellcome TrustWellcome Trust 214290/Z/18/Z
6 · The paper itself

Abstract

backgroundCardiometabolic disturbances play a central role in the pathogenesis of heart failure with preserved ejection fraction (HFpEF). Due to its complexity, HFpEF is a challenging condition to treat, making phenotype-specific disease management a promising approach. However, HFpEF phenotypes are heterogenous and there is a lack of detailed evidence on the different, sex-specific profiles of cardiometabolic multimorbidity and metabolic syndrome present in HFpEF.

methodsWe performed a retrospective, modified cross-sectional study examining a subset of participants in the UK Biobank, an ongoing multi-centre prospective cohort study in the United Kingdom. We defined HFpEF as a record of a heart failure diagnosis using ICD-10 code I50, coupled with a left ventricular ejection fraction (LVEF) ≥ 50% derived from cardiac magnetic resonance (CMR) imaging. We examined sex-specific differences in cardiometabolic comorbidity burden and metabolic syndrome, performed latent class analysis (LCA) to identify distinct clusters of patients based on their cardiometabolic profile, and compared CMR imaging-derived parameters of left ventricular function at rest in the different clusters identified to reflect possible differences in adverse cardiac remodelling.

resultsWe ascertained HFpEF in 445 participants, of which 299 (67%) were men and 146 (33%) women. The median age was 70 years old (interquartile range: [66.0-74.0]). A combination of hypertension and obesity was the most prevalent cardiometabolic pattern both in men and women with HFpEF. Most men had 2-3 clinical cardiometabolic comorbidities while most women had 1-2, despite a similar metabolic syndrome profile (p = 0.05). LCA revealed three distinct, clinically relevant phenogroups, namely (1) a most male and multimorbid group (n = 117); (2) a group with a high prevalence of severe obesity, abnormal waist circumference and with the highest relative proportion of females (n = 116); and finally (3) a group with an apparently lower comorbidity burden aside from hypertension (n = 212). There were significant differences in clinical measurements and medication across the three phenogroups identified. Cardiac output at rest was significantly higher in group 2 vs. group 3 (males: median 5.6 L/min vs. 5.2 L/min, p < 0.05; females: 5.1 L/min vs. 4.4 L/min, p < 0.01). Absolute global longitudinal strain was significantly lower in women in group 1 vs. group 2 (-17.6% vs. -18.5%, p < 0.05).

conclusionWomen with cardiometabolic HFpEF had a lower comorbidity burden compared to men despite a similar metabolic syndrome profile. Based on patients' cardiometabolic profile, we identified three distinct subgroups which differed in body shape and mass, lipid biomarker and medication profile, as well as in cardiac output at rest both in men and women. These factors may affect disease trajectory, treatment options and outcomes in those subgroups. Subject to further validation, our findings provide a refined characterisation of the cardiometabolic HFpEF phenotype, contributing towards a better understanding of the condition to enable phenotype-specific disease management.

Indexed as

Health Status DisparitiesHeart FailureMetabolic SyndromeStroke VolumeVentricular Function, LeftAgedAged, 80 and overBiological Specimen BanksCardiometabolic Risk FactorsCross-Sectional StudiesFemaleHumansMaleMiddle AgedMultimorbidityPhenotypecardiac magnetic resonance imagingcardiometabolic diseasesHFpEFmachine learning, phenomappingmetabolic syndromeUK Biobank

Identifiers

PMID40468351
PMCPMC12139127

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.