Vericiguat and mortality in heart failure and reduced ejection fraction: the VICTOR trial
Bibliographic record
Abstract
BACKGROUND AND AIMS: In the VICTOR trial (NCT05093933), vericiguat was neutral for the primary composite endpoint of cardiovascular death or hospitalization for heart failure (HF). VICTOR was powered to independently assess cardiovascular death. This study reports detailed analysis on the effects of vericiguat on mortality. METHODS: VICTOR, a double-blind, placebo-controlled, randomized trial, enrolled 6105 ambulatory patients with HF and reduced ejection fraction (HFrEF) without recent worsening and randomized them to vericiguat or placebo. The main outcome for this analysis was the pre-specified secondary endpoint of cardiovascular death. All-cause death, sudden cardiac death, and death related to HF were also assessed. RESULTS: Over a median of 19.7 months (inter-quartile range 14.6-25.4), cardiovascular deaths occurred in 292 patients (5.7 deaths per 100 patient-years) and 346 patients (6.8 deaths per 100 patient-years) in the vericiguat and placebo groups, respectively (hazard ratio [HR] 0.83, 95% confidence interval [CI] 0.71-0.97; P = .020). Risk of death from any cause was lower with vericiguat vs placebo (377 [7.3 deaths per 100 patient-years] vs 440 [8.6 deaths per 100 patient-years]; HR 0.84, 95% CI 0.74-0.97; P = .015). Sudden cardiac death and HF-related deaths were lower with vericiguat vs placebo (1.6 vs 2.2 events per 100 patient-years; HR 0.75, 95% CI 0.56-0.99; P = .042 and 1.7 vs 2.4 events per 100 patient-years; HR 0.71, 95% CI 0.54-0.94; P = .016, respectively). Lower mortality rates were consistent across subgroups including baseline therapy. Consistent cardiovascular and all-cause mortality benefit was seen across baseline N-terminal pro-B-type natriuretic peptide levels. CONCLUSIONS: In ambulatory well-treated participants with HFrEF, vericiguat was associated with clinically meaningful reductions in the key secondary outcome of cardiovascular death, as well as all-cause mortality.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".