SGLT2 Inhibitors for the Prevention and Treatment of Heart Failure: A Scientific Statement of the HFA and the HFAI
Bibliographic record
Abstract
In the 2021 European Society of Cardiology (ESC) heart failure (HF) guidelines, sodium-glucose cotransporter 2 (SGLT2) inhibitors were recommended for the prevention of HF in patients with type 2 diabetes mellitus (T2DM) and for the treatment of HF with reduced ejection fraction (HFrEF). Further trials showed efficacy of empagliflozin and dapagliflozin in patients with HF with preserved ejection fraction (HFpEF). These results prompted a broadened recommendation for the SGLT2 inhibitors dapagliflozin or empagliflozin across the whole left ventricular ejection fraction (LVEF) spectrum in the 2023 Focused Update of the ESC HF guidelines and in other international guidelines. In SOLOIST-WHF and EMPULSE, sotagliflozin (enrolling only patients with T2DM) and empagliflozin, respectively, were beneficial when initiated at the end or soon after an episode of decompensated HF. Based on these results and on the early appearance of their beneficial effects, the administration of SGLT2 inhibitors should start early in patients hospitalized for acute HF. Analyses after study drug withdrawal in randomized clinical trials have shown that their benefits may decline rapidly after discontinuation, and thus, persistence of treatment is advised. In EMPACT-MI, empagliflozin did not reduce the primary outcome of cardiovascular (CV) death/HF hospitalization but reduced first/recurrent HF hospitalizations. Potential benefits of SGLT2 inhibitors in further specific conditions (i.e., cardiac amyloidosis, grown-up congenital heart disease and paediatric patients with HF) have been reported in observational studies but need confirmation from prospective trials. This scientific statement summarizes current evidence regarding the effects of SGLT2 inhibitors for the prevention and treatment of HF.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".