Developments in Exercise Capacity Assessment in Heart Failure Clinical Trials and the Rationale for the Design of METEORIC-HF
Bibliographic record
Abstract
Heart failure with reduced ejection fraction (HFrEF) is a highly morbid condition for which exercise intolerance is a major manifestation. However, methods to assess exercise capacity in HFrEF vary widely in clinical practice and in trials. We describe advances in exercise capacity assessment in HFrEF and a comparative analysis of how various therapies available for HFrEF impact exercise capacity. Current guideline-directed medical therapy has indirect effects on cardiac performance with minimal impact on measured functional capacity. Omecamtiv mecarbil is a novel selective cardiac myosin activator that directly increases cardiac contractility and in a phase 3 cardiovascular outcomes study significantly reduced the primary composite end point of time to first heart failure event or cardiovascular death in patients with HFrEF. The objective of the METEORIC-HF trial (Multicenter Exercise Tolerance Evaluation of Omecamtiv Mecarbil Related to Increased Contractility in Heart Failure) is to assess the effect of omecamtiv mecarbil versus placebo on multiple components of functional capacity in HFrEF. The primary end point is to test the effect of omecamtiv mecarbil compared with placebo on peak oxygen uptake as measured by cardiopulmonary exercise testing after 20 weeks of treatment. METEORIC-HF will provide state-of-the-art assessment of functional capacity by measuring ventilatory efficiency, circulatory power, ventilatory anaerobic threshold, oxygen uptake recovery kinetics, daily activity, and quality-of-life assessment. Thus, the METEORIC-HF trial will evaluate the potential impact of increased myocardial contractility with omecamtiv mecarbil on multiple important measures of functional capacity in ambulatory patients with symptomatic HFrEF. Registration: URL: https://clinicaltrials.gov; Unique identifier: NCT03759392.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.439 | 0.395 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".