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Abstract 16798: The Influence of Heart Failure With Preserved or Reduced Ejection Fraction on Relationships Between Cardiac Power and Stroke Work With VO2

2015· article· en· W2910618304 on OpenAlexaff
Erik H. Van Iterson, Eric M. Snyder, Barry A. Borlaug, Thomas P. Olson

Bibliographic record

VenueCirculation · 2015
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and exercise physiology
Canadian institutionsStuart Olson (Canada)
Fundersnot available
KeywordsMedicineCardiologyInternal medicineHeart failureEjection fractionPulmonary wedge pressureStroke volumeStroke (engine)Blood pressureHeart failure with preserved ejection fractionCardiac outputCardiac function curveCardiac catheterization

Abstract

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Introduction: Invasive measurement of cardiac power (CP) and stroke work (SW) during exercise are robust indices of cardiac function and relate to syndrome severity and prognosis in heart failure patients with preserved (HFpEF) or reduced (HFrEF) ejection fraction. Because invasive measurement via catheterization laboratories are not always readily available, non-invasive cardiopulmonary exercise testing to estimate cardiac function is routinely performed in the clinical evaluation of HFpEF and HFrEF. However, it is unknown how VO 2 relates with CP and SW in HFpEF vs HFrEF. We compared relationships between CP and SW with VO 2 at rest and peak exercise in HFpEF vs HFrEF. Methods: 30 HFpEF and 32 HFrEF (EF: 62±2 vs 22±1%; males: 17 vs 30; age: 70±2 vs 55±2 yrs; BMI: 34±1 vs 28±1 kg/m 2 ; wt: 98±4 vs 86±3 kg (all p<0.05)) participated in exercise testing during right heart catheterization. Oxygen consumption (VO 2 ) was measured continuously from rest to peak work. Invasive measures at rest and peak work included mean radial arterial pressure (MAP), right atrial pressure (RAP), and pulmonary capillary wedge pressure (PCWP). We calculated CP=(MAP–RAP) x Q I x 2.22х10 -3 and SW=(MAP–PCWP) x SV I x 0.133. Results: At rest, R 2 between VO 2 and CP or SW were not different between HFpEF (CP=0.41, SW=0.30) and HFrEF (CP=0.39, SW=0.15). Slopes did not differ significantly between HFpEF (CP=0.13, SW=0.01) and HFrEF (CP=0.16, SW=0.01) for regressions between VO 2 and CP or SW; but, fitted intercepts of the regression showed significantly higher intercepts in HFrEF (CP=0.89, SW=1.16) vs HFpEF (CP=0.05, SW=0.27) for VO 2 vs CP and SW, respectively. At peak exercise, R 2 between VO 2 and CP or SW were not different between HFpEF (CP=0.48, SW=0.64) and HFrEF (CP=0.70, SW=0.67). Slopes did not differ between HFpEF (CP=0.18, SW=0.02) and HFrEF (CP=0.15, SW=0.02) for regressions between VO 2 and CP or SW, whereas the fitted intercepts the slope of the regression were significantly higher in HFrEF (CP=5.1, SW=4.4) vs HFpEF (CP=3.2, SW=2.0) for VO 2 vs CP and SW, respectively. Conclusion: Our data suggest that despite lower VO 2 relative to CP and SW in HFpEF, both the strength of relationship and rate of increase in VO 2 relative to CP and SW are similar between HFpEF and HFrEF at rest and peak exercise.

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)0.002
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 score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0070.001

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 head0.035
GPT teacher head0.263
Teacher spread0.228 · 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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Citations0
Published2015
Admission routes1
Has abstractyes

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