Dapagliflozin and New York Heart Association functional class in heart failure with mildly reduced or preserved ejection fraction: the DELIVER trial
Bibliographic record
Abstract
Aims This pre‐specified analysis of the DELIVER trial examined whether clinical benefits of dapagliflozin in heart failure (HF) with left ventricular ejection fraction (LVEF) >40% varied by baseline New York Heart Association (NYHA) class and examined the treatment effects on NYHA class over time. Methods and results Treatment effects of dapagliflozin by baseline NYHA class II ( n = 4713) versus III/IV ( n = 1549) were examined on the primary endpoint (cardiovascular death or worsening HF event) and key secondary endpoints. Effects of dapagliflozin on change in NYHA class at 4, 16, and 32 weeks were also evaluated. Higher baseline NYHA class was associated with older age, female sex, greater comorbidity burden, lower LVEF, and higher natriuretic peptide levels. Participants with baseline NYHA class III/IV, as compared with II, were independently more likely to experience the primary endpoint (adjusted hazard ratio [HR] 1.16 [95% confidence interval, 1.02–1.33]) and all‐cause death (adjusted HR 1.22 [1.06–1.40]). Dapagliflozin consistently reduced the risk of the primary endpoint compared with placebo, irrespective of baseline NYHA class (HR 0.81 [0.70–0.94] for NYHA class II vs. HR 0.80 [0.65–0.98] for NYHA class III/IV; p interaction = 0.921). Participants with NYHA class III/IV had greater improvement in Kansas City Cardiomyopathy Questionnaire total symptom scores between baseline and 32 weeks (+4.8 [2.5–7.1]) versus NYHA class II (+1.8 [0.7–2.9]; p interaction = 0.011). Dapagliflozin was associated with higher odds of any improvement in NYHA class (odds ratio [OR] 1.32 [1.16–1.51]), as well as improvement to NYHA class I (OR 1.43 [1.17–1.75]), versus placebo at 32 weeks, with benefits seen as early as 4 weeks. Conclusions Among symptomatic patients with HF and LVEF >40%, treatment with dapagliflozin provided clinical benefit irrespective of baseline NYHA class and was associated with early and sustained improvements in NYHA class over time.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".