Vericiguat in patients with atrial fibrillation and heart failure with reduced ejection fraction: insights from the <scp>VICTORIA</scp> trial
Bibliographic record
Abstract
AIMS: We evaluated the relation between baseline and new-onset atrial fibrillation (AF) and outcomes, and assessed whether vericiguat modified the likelihood of new-onset AF in patients with worsening heart failure (HF) with reduced ejection fraction in VICTORIA. METHODS AND RESULTS: Of 5050 patients randomized, 5010 with recorded AF status at baseline were analysed. Patients were classified into three groups: no known AF (n = 2661, 53%), history of AF alone (n = 992, 20%), and AF on randomization electrocardiogram (n = 1357, 27%). Compared with those with no AF, those with history of AF alone had a higher risk of cardiovascular death [adjusted hazard ratio (HR) 1.21, 95% confidence interval (CI) 1.01-1.47] without excess myocardial infarction or stroke; neither type of AF was associated with a higher risk of the primary composite outcome (time to cardiovascular death or first HF hospitalization), HF hospitalizations, or all cause-death. The beneficial effect of vericiguat on the primary composite outcome and its components was evident irrespective of AF status at baseline. Over a median follow-up of 10.8 months, new-onset AF occurred in 6.1% of those with no AF and 18.3% with history of AF alone (P < 0.0001). These events were not influenced by vericiguat treatment (adjusted HR 0.93, 95% CI 0.75-1.16; P = 0.51), but were associated with an increase in the hazard of both primary and secondary outcomes. CONCLUSIONS: Atrial fibrillation was present in nearly half of this high-risk population with worsening HF. A history of AF alone at baseline portends an increased risk of cardiovascular death. Neither type of AF affected the beneficial effect of vericiguat. Development of AF post-randomization was associated with an increase in both cardiovascular death and HF hospitalization which was not influenced by vericiguat.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".