Vericiguat Global Study in Participants with Chronic Heart Failure: Design of the VICTOR Trial
Bibliographic record
Abstract
AIMS: In the VICTORIA (Vericiguat Global Study in Subjects with Heart Failure with Reduced Ejection Fraction) trial, the soluble guanylate cyclase stimulator vericiguat reduced the risk of hospitalization for heart failure (HHF) or cardiovascular death in patients with heart failure (HF) and reduced ejection fraction (HFrEF) with recent worsening HF. The effect of vericiguat in patients with HFrEF without recent worsening HF remains unknown. The VICTOR (Vericiguat Global Study in Participants with Chronic Heart Failure) trial was designed to assess the efficacy and safety of vericiguat in patients with ejection fraction ≤40% without recent worsening HF on a background of current foundational HFrEF therapy. METHODS: The primary endpoint for VICTOR is time to first event for the composite of HHF or cardiovascular death. The trial will also assess the effect of vericiguat on time to cardiovascular death, time to HHF, total HHF, and all-cause death. As an event-driven trial, at least 1080 primary events are expected, but follow-up will continue until the targeted number of at least 590 cardiovascular deaths has been reached. Approximately 6000 participants will be randomized to vericiguat or placebo. CONCLUSION: VICTOR is the first large event-driven HFrEF trial performed in the contemporary era of quadruple foundational guideline-directed medical therapy, in a compensated ambulatory HF population. VICTOR will add important information to the evidence of the effects of vericiguat across the spectrum of patients with HFrEF.
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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 | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.003 |
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".