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Record W4410482540 · doi:10.1093/eurjpc/zwaf236.057

Exercise limitations in heart failure with preserved ejection fraction and obesity: is the issue the engine or chassis?

2025· article· en· W4410482540 on OpenAlexaff
Stephen Foulkes, Sara Ferreira, Maurício Milani, Youri Bekhuis, Maarten Falter, Sarah Stroobants, S Joghani, Sevilay Altıntaş, Rūta Jasaitytė, Jan Stassen, Lieven Herbots, Guido Claessen, Mark J. Haykowsky, Jan Verwerft

Bibliographic record

VenueEuropean Journal of Preventive Cardiology · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineChassisEjection fractionHeart failureHeart failure with preserved ejection fractionCardiologyObesityInternal medicineMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Background Heart failure with preserved ejection fraction (HFpEF) is a complex clinical syndrome characterized by reduced peak oxygen uptake (VO2peak) secondary to central and peripheral limitations. Obesity is a well-established risk factor for HFpEF and has garnered considerable interest as a therapeutic target, particularly in the context of the obese-HFpEF phenotype. However, the impact of obesity on VO2peak and its Fick determinants in HFpEF remains unclear. Purpose To understand the impact of obesity on VO2peak and it’s central and peripheral determinants in individuals with HFpEF. Methods Patients referred to a multi-disciplinary unexplained dyspnea clinic with an established HFpEF diagnosis were included (n=448), and sub-grouped based on body mass index (BMI, ≥30 kg/m2 or <30) into HFpEF with- (HFpEFObese, n=138; BMI=34.3±3.7 kg/m2; 68% female; 71±9 yrs) or without obesity (HFpEFNon-Obese, n=310; BMI=24.9±3.0 kg/m2; 60% female; 74±9 yrs.). Patients underwent maximal cardiopulmonary exercise testing with simultaneous echocardiography (CPETecho) to assess VO2peak, exercise hemodynamics (cardiac output, CO; stroke volume, SV; heart rate, HR, mean pulmonary artery pressure, mPAP) and the arterio-venous oxygen difference (a-vO2diff). HFpEF sub-groups were compared using ANCOVA with adjustment for age and sex. Comparison was made using absolute values and values adjusted for bodyweight (peak VO2) or body surface area (BSA; CO, SV) . Pooled HFpEF sub-groups were also compared using ANCOVA (adjusted for age and sex) to controls (CON, n=153; BMI: 23.1±2.7 kg/m2, 41% female; 62±5 yrs) without HFpEF to elucidate the impact of HFpEF, versus HFpEF plus obesity on VO2peak and its determinants. Results HFpEFObese and HFpEFNon-Obese had comparable absolute VO2peak, peak exercise HR and a-vO2diff, while HFpEFObese had higher CO at peak exercise secondary to a larger SV. Resting and exercise mPAP and mPAP-CO slopes were higher in HFpEF vs CON (P<0.001 for all; Fig. 2), with no differences seen between HFpEF obesity phenotypes (P>0.50 for all). In contrast, bodyweight-adjusted peak VO2 was markedly lower in HFpEFObese (Fig. 1B), despite comparable peak exercise cardiac index and stroke volume index. Regardless of HFpEF sub-group, peak VO2, central (CO, HR, mPAP) and peripheral factors (a-vO2diff) were markedly impaired in HFpEF versus CON (Fig. 1). Conclusions Obese HFpEF patients demonstrate a higher stroke volume reserve while maintaining oxygen extraction. However, these adaptations are insufficient to sustain weight-adjusted peak VO2 at the levels of their non-obese counterparts. This suggests that obesity induces adaptive cardiac and peripheral muscle remodeling. Accordingly, HFpEF patients achieving weight reduction should be supported with adjuvant exercise training programs to preserve cardiac and peripheral muscle performance as the load of excess body mass is alleviated, thereby enhancing exercise tolerance.Fig 1.Differences in VO2 determinantsFig 2.Differences in mPAP and CO

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.193

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.256
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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