Dapagliflozin and the Incidence of Type 2 Diabetes in Patients With Heart Failure and Reduced Ejection Fraction: An Exploratory Analysis From DAPA-HF
Bibliographic record
Abstract
OBJECTIVE The sodium–glucose cotransporter 2 inhibitor dapagliflozin reduced the risk of cardiovascular mortality and worsening heart failure in the Dapagliflozin and Prevention of Adverse Outcomes in Heart Failure (DAPA-HF) trial. This report explores the effect of dapagliflozin on incident type 2 diabetes (T2D) in the cohort without diabetes enrolled in the trial. RESEARCH DESIGN AND METHODS The subgroup of 2,605 patients with heart failure and reduced ejection fraction (HFrEF), no prior history of diabetes, and an HbA1c of <6.5% at baseline was randomized to dapagliflozin 10 mg daily or placebo. In this exploratory analysis, surveillance for new-onset diabetes was accomplished through periodic HbA1c testing as part of the study protocol and comparison between the treatment groups assessed through a Cox proportional hazards model. RESULTS At baseline, the mean HbA1c was 5.8%. At 8 months, there were minimal changes, with a placebo-adjusted change in the dapagliflozin group of −0.04%. Over a median follow-up of 18 months, diabetes developed in 93 of 1,307 patients (7.1%) in the placebo group and 64 of 1,298 (4.9%) in the dapagliflozin group. Dapagliflozin led to a 32% reduction in diabetes incidence (hazard ratio 0.68, 95% CI 0.50–0.94; P = 0.019). More than 95% of the participants who developed T2D had prediabetes at baseline (HbA1c 5.7–6.4%). Participants who developed diabetes in DAPA-HF had a higher subsequent mortality than those who did not. CONCLUSIONS In this exploratory analysis among patients with HFrEF, treatment with dapagliflozin reduced the incidence of new diabetes. This potential benefit needs confirmation in trials of longer duration and in people without heart failure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".