Effects of sacubitril/valsartan on glycemia in patients with diabetes and heart failure: the PARAGON-HF and PARADIGM-HF trials
Bibliographic record
Abstract
Abstract Background Compared with enalapril, sacubitril/valsartan lowered HbA1c and reduced new insulin therapy in patients with heart failure with reduced ejection fraction (HFrEF) and diabetes in the PARADIGM-HF trial. We sought to assess the glycemic effects of sacubitril/valsartan in heart failure with preserved ejection fraction (HFpEF) and diabetes, and across the spectrum of left ventricular ejection fraction (LVEF) in heart failure and diabetes. Methods We compared the effect of sacubitril/valsartan, relative to valsartan, on HbA1c, new insulin therapy and hypoglycemia in the randomized controlled trial PARAGON-HF, and performed pooled analyses of PARAGON-HF and PARADIGM-HF. Results Among 2395 patients with HFpEF and diabetes in PARAGON-HF, sacubitril/valsartan compared with valsartan reduced HbA1c (baseline-adjusted between-group difference in HbA1c change at 48 weeks: − 0.24%, 95% CI − 0.33 to − 0.16%, P < 0.001). Numerically, new insulin treatment was initiated less often in the sacubitril/valsartan group than in the valsartan group, but the difference was not statistically significant (12.8% vs. 16.1%; HR: 0.80, 95% CI 0.62–1.02, P = 0.07). Hypoglycemia adverse event reports were low, but more frequent in those receiving sacubitril/valsartan than in the valsartan group (4.2% vs. 2.6%; HR: 1.64, 95% CI 1.05–2.56, P = 0.030). In a pooled analysis of PARAGON-HF and PARADIGM-HF, the effect of sacubitril/valsartan on change in HbA1c was not significantly modified by LVEF (Pinteraction = 0.56). Across the spectrum of LVEF, sacubitril/valsartan reduced new insulin therapy (HR: 0.75, 95% CI 0.63–0.89, P = 0.001), compared with enalapril or valsartan. Conclusions Sacubitril/valsartan reduced HbA1c and new insulin therapy in patients with heart failure and diabetes across the spectrum of LVEF but may be associated with a slightly higher risk for hypoglycemia. Trial registration ClinicalTrials.gov NCT01920711
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.019 | 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".