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Left ventricular volume as a predictor of exercise capacity and functional independence in individuals with preserved ejection fraction

2024· article· en· W4403837919 on OpenAlexaff
Stacey L Rowe, Wouter L’Hoyes, Stephen Foulkes, E. Paratz, Jan Stassen, Boris Delpire, Maurício Milani, Sara Ferreira, Maarten Falter, Youri Bekhuis, Lieven Herbots, Mark J. Haykowsky, Guido Claessen, André La Gerche, Jan Verwerft

Bibliographic record

VenueEuropean Heart Journal · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineEjection fractionCardiologyInternal medicineIndependence (probability theory)Stroke volumeVentricular functionHeart failureStatistics

Abstract

fetched live from OpenAlex

Abstract Background Cardiorespiratory fitness (CRF) is vital for independent living and is a powerful prognostic marker. Increased left ventricular (LV) volume has been linked with high CRF in athletes, but its utility as a diagnostic marker of low CRF across the entire health-disease continuum has yet to be tested. Methods This multi-center international cohort from Australia and Belgium examined the relationship between ventricular size on resting echocardiography and CRF (peakVO2 from cardiopulmonary exercise testing [CPET] or CPET with simultaneous echocardiography) in individuals with preserved LV ejection fraction (≥50%). LV end-diastolic volume (LVEDV) and LVEDV indexed to body surface area (LVEDVi) were tested as predictors of very low CRF (CRF associated with functional disability - peakVO2 < 1100ml or <18 ml/kg/min) and compared against other candidate measures of systolic and diastolic cardiac function that have been associated with heart disease. Thresholds for absolute and indexed LVEDV which best distinguished between lower and higher CRF status were identified. Results 2876 individuals (251 healthy non-athletes, 309 elite endurance athletes, 1969 individuals with unexplained dyspnea, 347 individuals with heart failure with preserved ejection fraction) were included. For the entire cohort, LVEDV had the strongest univariate association with peakVO2 (R2 = 0.45, standardized [std] β 0.67, p< 0.001) and, remained the strongest independent predictor of peakVO2 after adjusting for age, sex and body mass index (std β 0.44, p < 0.001). The relationship between LVEDV and VO2peak differed based on health/disease status (Figure 1). LVEDV demonstrated the greatest diagnostic capability in identifying functional disability (LVEDV AUC 0.72; LVEDVi AUC 0.71, Figure 2), outperforming ejection fraction, diastolic velocities, atrial volumes and pulmonary artery pressure estimates. The probability of achieving a peak VO2 below the threshold required for functional independence was highest for smaller ventricular volumes with LVEDV and LVEDVi of 88ml and 57 ml/m2 proving the optimal cut-points, respectively. Conclusions A small LVEDV is associated with a higher probability of poor exercise capacity, failure to achieve the peak VO2 required for functional independence and is the strongest independent echocardiographic predictor of CRF across the health-disease continuum.Figure 1.Ventricular Size and CRFFigure 2.Predictors of CRF status

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.024
GPT teacher head0.248
Teacher spread0.224 · 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 source (direct Gemma or distilled Codex), 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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Citations1
Published2024
Admission routes1
Has abstractyes

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