Effects of dapagliflozin in heart failure with reduced ejection fraction and chronic obstructive pulmonary disease: an analysis of <scp>DAPA‐HF</scp>
Bibliographic record
Abstract
AIMS: Chronic obstructive pulmonary disease (COPD) is an important comorbidity in heart failure (HF) with reduced ejection fraction (HFrEF), associated with worse outcomes and often suboptimal treatment because of under-prescription of beta-blockers. Consequently, additional effective therapies are especially relevant in patients with COPD. The aim of this study was to examine outcomes related to COPD in a post hoc analysis of the Dapagliflozin And Prevention of Adverse-outcomes in Heart Failure (DAPA-HF) trial. METHODS AND RESULTS: We examined whether the effects of dapagliflozin in DAPA-HF were modified by COPD status. The primary outcome was the composite of an episode of worsening HF or cardiovascular death. Overall, 585 (12.3%) of the 4744 patients randomized had a history of COPD. Patients with COPD were more likely to be older men with a history of smoking, worse renal function, and higher baseline N-terminal pro B-type natriuretic peptide, and less likely to be treated with a beta-blocker or mineralocorticoid receptor antagonist. The incidence of the primary outcome was higher in patients with COPD than in those without [18.9 (95% confidence interval 16.0-22.2) vs. 13.0 (12.1-14.0) per 100 person-years; hazard ratio (HR) for COPD vs. no COPD 1.44 (1.21-1.72); P < 0.001]. The effect of dapagliflozin, compared with placebo, on the primary outcome, was consistent in patients with [HR 0.67 (95% confidence interval 0.48-0.93)] and without COPD [0.76 (0.65-0.87); interaction P-value 0.47]. CONCLUSIONS: In DAPA-HF, one in eight patients with HFrEF had concomitant COPD. Participants with COPD had a higher risk of the primary outcome. The benefit of dapagliflozin on all pre-specified outcomes was consistent in patients with and without COPD. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov ID NCT03036124.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.010 |
| 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 | 0.002 |
| 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".