Diuretic use and outcomes in patients with HFrEF: Insights from the VICTORIA trial
Bibliographic record
Abstract
Abstract Background In the Vericiguat Global Study in Subjects with Heart Failure with Reduced Ejection Fraction (VICTORIA) trial, vericiguat, compared with placebo, reduced the risk of cardiovascular death (CVD) and heart failure hospitalization (HFH) in patients enrolled shortly after a worsening heart failure (WHF) event. We examined the clinical outcomes and efficacy of vericiguat as it relates to the background use of loop diuretics in this population of patients with WHF. Methods We calculated the total daily loop diuretic dose equivalent to furosemide dosing at randomization and categorized these as <40, 40, and >40 mg total daily dose (TDD). The primary composite outcome of CVD or HFH and its components were evaluated as clinical outcomes and expressed as adjusted hazard ratios (adjHR) and 95% confidence intervals (95% CI). Post-randomization rates of change in TDD and safety were also examined. Results Of 4434 patients with diuretic dose information available at randomization, 647 (14.6%) were on <40 mg, 1633 (36.8%) were on 40 mg, and 2154 (48.6%) were on >40 mg TDD. Patient characteristics revealed those patients taking >40 mg TDD were more often in NYHA Class III/IV, diabetic, and had higher NT-proBNP, lower eGFR, less triple guideline-based HF therapy, and a higher MAGGIC risk score. The composite event rate of CVD or HFH per 100 patient years (pt-yrs) progressively increased with higher doses of diuretics: 29.8 per 100 pt-yrs for 40 mg TDD: adjHR 1.23 (95%CI 1.02-1.49); 48.1 per 100 pt-yrs for >40 mg TDD adjHR 1.50 (95%CI 1.25-1.81), relative to <40 mg TDD (22.5 per 100 pt-yrs). Results were similarly observed for the components of the composite endpoint (Figure). There was no significant interaction for the efficacy of vericiguat vs placebo for any outcome examined according to TDD at randomization (p-interaction >0.72, 0.57 and 0.64 for the primary endpoint, CVD and HFH). Diuretic dose changes post-randomization were assessed in 3684 eligible patients (followed for a median duration of 14.2 months). By treatment group, there were similar rates of up-titration (26.7 and 29.4 per 100 pt-yrs), down-titration (13.8 and 15.4 per 100 pt-yrs), and stopping of diuretic use (23.4 and 24.2 per 100 pt-yrs) observed for vericiguat and placebo groups, respectively. Conclusions The amount of loop diuretic TDD at randomization was associated with a higher risk phenotype commensurate with worse outcomes. However, the efficacy of vericiguat was preserved across this range of different loop diuretic doses used by patients with recent WHF in VICTORIA.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".