Abstract 14120: Characteristics, Outcomes and Treatment Response With Dapagliflozin Across the Range of Ejection Fraction in People With HF and a History of CABG Surgery: A Pooled Analysis From DAPA-HF and DELIVER
Bibliographic record
Abstract
Introduction: There is a paucity of data on contemporary outcomes of patients with a history of CABG who have heart failure (HF) with either reduced or preserved left ventricular ejection fraction (LVEF). We aimed to compare the baseline characteristics and outcomes by history of CABG, as well the efficacy and safety of the SGLT2 inhibitor, dapagliflozin, across the full range of LVEF in patients with heart failure. Methods: We conducted a patient-level pooled analysis of two trials testing dapagliflozin in 11,007 participants with HF and LVEF ≤40% (DAPA-HF trial) and >40% (DELIVER trial). The primary outcome was the composite of a worsening HF event or death from CV causes; other outcomes examined included total hospital admissions for HF, MACE, all-cause mortality and Kansas City Cardiomyopathy Questionnaire (KCCQ) scores. Outcomes were compared by history of CABG. Results: Among 11,007 patients, 1576 had a prior history of CABG (~14%). Patients with CABG were characterised by a higher proportion of men, lower eGFR and LVEF, and higher rates of prior MI, PCTA, type 2 diabetes, antiplatelet and statin therapy. CABG patients were more likely to experience primary outcome (adjusted hazard ratio [aHR] 1.21, 95% CI 1.08-1.36), CV death (aHR 1.22, 95% CI 1.04-1.42), all-cause death (aHR 1.22, 95% CI 1.07-1.38), HF hospitalization (aHR 1.31, 95% CI 1.14-1.51), total HF events (adjusted rate ratio 1.38, 95% CI 1.20-1.59), and MACE (aHR 1.34 (1.17-1.52). Dapagliflozin consistently reduced the primary and key secondary endpoints in both people with and without a history of CABG across the entire spectrum of LVEF (P-interaction for all > 0.48) (Table). Adverse events and tolerability were similar between groups. Conclusions: In patients with HF, a prior history of CABG is associated with higher rates of CV outcomes and mortality compared to those without a history of CABG. The efficacy and safety of dapagliflozin was similar in patients with and without a history of CABG.
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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 | 0.011 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.018 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 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".