Efficacy and Safety of Sodium–Glucose Co-Transporter 2 Inhibition According to Left Ventricular Ejection Fraction in DAPA-HF
Bibliographic record
Abstract
AIMS: The aim of this study was to examine whether left ventricular ejection fraction (LVEF) modified efficacy and safety of dapagliflozin 10 mg compared with placebo in the 4744 patients with LVEF ≤40% randomized in the Dapagliflozin And Prevention of Adverse-outcomes in Heart Failure trial (DAPA-HF). METHODS AND RESULTS: We examined whether LVEF, analysed categorically or continuously, modified the effect of dapagliflozin. The primary efficacy outcome was the composite of a worsening heart failure (HF) event (unplanned HF hospitalization/an urgent HF visit requiring intravenous therapy) or cardiovascular death. Mean LVEF was 31.1% and LVEF categories analysed were: <26% (n = 1143), 26-30% (n = 1018), 31-35% (n = 1187), and >35% (n = 1396). Each 5% decrease in LVEF was associated with a higher risk of the primary outcome [hazard ratio (HR) 1.18; 95% confidence interval (CI) 1.13-1.24]. The benefit of dapagliflozin was consistent across the spectrum of LVEF: the dapagliflozin vs. placebo HR was 0.75 (95% CI 0.59-0.95) for LVEF <26%, 0.75 (0.57-0.98) for LVEF 26-30%, 0.67 (0.51-0.89) for LVEF 31-35%, and 0.83 (0.63-1.09) for LVEF >35% (P for interaction = 0.762). Similarly, the effect of dapagliflozin on the components of the primary endpoint was not modified by baseline LVEF (P for interaction for cardiovascular death = 0.974, and for worsening HF = 0.161). Safety of dapagliflozin was also consistent across the range of LVEF and neither efficacy nor safety were modified by diabetes status. CONCLUSION: Left ventricular ejection fraction was a significant predictor of hospitalization and mortality in patients with HF with reduced ejection fraction but did not modify the beneficial effect of dapagliflozin, overall or separately, in patients with and without diabetes. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifier 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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".