271-OR: ADA Presidents’ Select Abstract: Effect of Dapagliflozin on the Incidence of Diabetes: A Prespecified Exploratory Analysis from DAPA-HF
Bibliographic record
Abstract
In DAPA-HF, the SGLT2 inhibitor (i) dapagliflozin (dapa) reduced worsening heart failure (HF) and cardiovascular death in 4744 patients (pts) with HF and reduced ejection fraction (HFrEF.) Only 45% had type 2 diabetes (T2D) at baseline. We evaluated whether dapa reduced the incidence of diabetes in the 55% of pts without T2D. Pts were randomized to dapa 10 mg or placebo and followed for a median of 18.2 months. New-onset T2D was defined as A1c ≥6.5% measured at 2 consecutive study visits post-randomization or investigator-reported new T2D (with the initiation of a glucose-lowering agent.) The effect of dapa on incident T2D was assessed using a Cox proportional hazards model and confirmed with a Fine and Gray competing risk model to account for mortality. Of the 2605 non-T2D pts at baseline, 157 developed T2D on trial, 150 (95.5%) of whom had prediabetes (A1c 5.7-6.4%) (136 [86.6%] using the more restrictive 6.0-6.4% criterion.) Those with incident T2D had a higher mean baseline A1c (6.2 ±0.3 vs. 5.7 ±0.4%; p<0.001), greater BMI (28.5 ±5.9 vs. 27.1 ±5.7 kg/m2; p=0.003), and lower eGFR (61.5 ±17.4 vs. 68.2 ±19.3 ml/min/1.73 m2; p<0.001) than those who remained nondiabetic. Dapa reduced new-onset diabetes by 32%: placebo 93/1307 (7.1%) vs. dapa 64/1298 (4.9%); HR 0.68 (95% CI, 0.50-0.94; p=0.019) (Cox.) Results were virtually identical using the Fine and Gray model. Diabetes prevention may be another benefit of dapagliflozin. Disclosure S.E. Inzucchi: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Lexicon Pharmaceuticals, Inc., Novo Nordisk A/S, Sanofi. Consultant; Self; Abbott, Merck & Co., Inc., vTv Therapeutics. K. Docherty: Speaker’s Bureau; Self; Eli Lilly and Company. Other Relationship; Self; AstraZeneca. L. Kober: Speaker’s Bureau; Self; AstraZeneca, Novartis AG. Other Relationship; Self; AstraZeneca. M.N. Kosiborod: Consultant; Self; Amarin Corporation, Amgen, Applied Therapeutics, AstraZeneca, Bayer AG, Boehringer Ingelheim Pharmaceuticals, Inc., Eisai Inc., Eli Lilly and Company, GlaxoSmithKline plc., Glytec, Intarcia Therapeutics, Janssen Scientific Affairs, LLC., Merck & Co., Inc., Novartis Pharmaceuticals Corporation, Novo Nordisk Inc., Sanofi US, Vifor Pharma Group. Research Support; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc. F. Martinez: Board Member; Self; AstraZeneca, Novartis Pharmaceuticals Corporation. P. Ponikowski: None. M.S. Sabatine: Consultant; Self; Amgen, AstraZeneca, Bristol-Myers Squibb, CVS Caremark, DalCor Pharmaceuticals, Dyrnamix Inc., Esperion Therapeutics, Inc., IFM Therapeutics, Intarcia Therapeutics, Ionis Pharmaceuticals, Inc., Medicines Company, MedImmune, Merck & Co., Inc. Research Support; Self; Amgen, AstraZeneca, Bayer U.S., Daiichi Sankyo, Eisai Inc., Intarcia Therapeutics, Janssen Research and Development, Medicines Company, MedImmune, Merck & Co., Inc., Novartis AG, Pfizer Inc., Quark Pharmaceuticals. S. Solomon: Consultant; Self; AstraZeneca, Theracos, Inc. Research Support; Self; AstraZeneca, Theracos, Inc. J. Belohlavek: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH. M. Böhm: Speaker’s Bureau; Self; Abbott, Amgen, AstraZeneca, Bayer AG, Boehringer Ingelheim Pharmaceuticals, Inc., Bristol-Myers Squibb, Medtronic, Novartis Pharmaceuticals Corporation, Servier, Vifor Pharma Group. C. Chiang: Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Daiichi Sankyo, Merck Sharp & Dohme Corp., Novartis AG, Pfizer Inc., Sanofi. R.A. de Boer: Speaker’s Bureau; Self; Abbott, AstraZeneca, Novartis AG, Roche Diagnostics France. M. Diez: Other Relationship; Self; AstraZeneca. A. Dukat: None. C.E.A. Ljungman: Advisory Panel; Self; AstraZeneca, Novartis AG, Pfizer Foundation. Stock/Shareholder; Self; AstraZeneca. Other Relationship; Self; AstraZeneca, Novartis AG. S. Verma: Advisory Panel; Self; Amgen, AstraZeneca, Bayer AG, Boehringer Ingelheim (Canada) Ltd., Boehringer Ingelheim Pharmaceuticals, Inc., Eli Lilly and Company, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novo Nordisk A/S, Sanofi. Research Support; Self; Amgen, AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Bristol-Myers Squibb, Janssen Pharmaceuticals, Inc., Merck & Co., Inc. Other Relationship; Self; AstraZeneca, AstraZeneca, Bayer AG, Boehringer Ingelheim (Canada) Ltd., Boehringer Ingelheim International GmbH, Eli Lilly and Company, Eli Lilly and Company, EOCI Pharmacomm, Janssen Pharmaceuticals, Inc., Merck & Co., Inc., Novartis Pharmaceuticals Canada Inc., Novo Nordisk A/S, Novo Nordisk A/S, Sanofi, Sanofi, Sun Pharmaceuticals, Toronto Knowledge Translation Working Group. D.L. DeMets: Consultant; Self; Actelion Pharmaceuticals US, Inc., AstraZeneca, Boston Scientific, Bristol-Myers Squibb, DalCor Pharmaceuticals, Intercept Pharmaceuticals, Inc., Medtronic. O. Bengtsson: Employee; Self; AstraZeneca. A. Langkilde: Employee; Self; AstraZeneca. Stock/Shareholder; Self; AstraZeneca. M. Sjöstrand: Employee; Self; AstraZeneca. P. Jhund: Advisory Panel; Self; Cytokinetics Inc. Research Support; Self; Boehringer Ingelheim International GmbH. Speaker’s Bureau; Self; Novartis AG. Other Relationship; Self; AstraZeneca. J.J. McMurray: Other Relationship; Self; AbbVie Inc., Alnylam Pharmaceuticals, Amgen, AstraZeneca, Bayer Healthcare Pharmaceuticals Inc., Bristol-Myers Squibb, Cardurion, GlaxoSmithKline plc., Novartis Pharmaceuticals Corporation, Theracos, Inc. Funding AstraZeneca
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".