Biomarker Profiles Associated with Reverse Ventricular Remodelling in Patients with Heart Failure and a Reduced Ejection Fraction: Insights from the Echocardiographic Substudy of the VICTORIA Trial
Bibliographic record
Abstract
AIMS: Reverse ventricular remodelling, defined as a decrease in left ventricular end-systolic volume indexed to body surface area (LVESVI) or an increase in left ventricular ejection fraction (LVEF), is associated with improved clinical outcomes in patients with heart failure with reduced ejection fraction (HFrEF). However, the underlying pathophysiological mechanisms remain unclear. METHODS AND RESULTS: We evaluated paired core-lab assessed echocardiograms and measurements of 92 biomarkers at baseline and 8 months thereafter in 419 participants with HFrEF. Reverse ventricular remodelling was defined as a >5% LVEF increase or >15% LVESVI relative decrease between baseline and 8 months. We evaluated the association between baseline biomarkers and their changes with reverse ventricular remodelling in the prospectively randomized controlled VICTORIA (Vericiguat Global Study in Subjects With Heart Failure With Reduced Ejection Fraction) trial. Of 419 patients (median age 66 [interquartile range 57-74] years, 27.4% women), 206 (49.2%) had reverse ventricular remodelling (either a 5% LVEF increase or a 15% LVESVI decrease). There were no differences in baseline biomarker concentrations between patients with versus those without reverse ventricular remodelling on follow-up. However, in patients with reverse ventricular remodelling there were significant decreases in biomarkers relating to inflammation and cardiac metabolism; particularly the tumour necrosis factor superfamily member 13B (ratio 0.82, 95% confidence interval [CI] 0.77-0.88), growth differentiation factor-15 (ratio 0.74, 95% CI 0.66-0.84), and insulin-like growth factor binding protein 7 (ratio 0.80, 95% CI 0.73-0.88). CONCLUSIONS: Reverse ventricular remodelling in patients with HFrEF is associated with a decrease of biomarkers related to inflammation and cardiac metabolism.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".