Early Benefits of Empagliflozin in Patients with or Without Heart Failure: Findings from EMPA-REG OUTCOME
Bibliographic record
Abstract
AIMS: The EMPA-REG OUTCOME trial demonstrated reductions in cardiovascular (CV) death and heart failure (HF) outcomes with empagliflozin, a sodium-glucose co-transporter 2 inhibitor, in patients with type 2 diabetes and established CV disease over a study period of 3 years. We aimed to investigate the early benefit-risk profile of empagliflozin in patients enrolled in the EMPA-REG OUTCOME trial according to HF status at baseline. METHODS AND RESULTS: The effects of treatments on glycated haemoglobin, systolic blood pressure and body weight, and on the HF endpoints of hospitalization for HF (HHF), HHF or CV death, and HHF or all-cause mortality were evaluated at 12 weeks, 6 months, and 1 year after randomization. Occurrence of adverse events (AEs) during these time points was also evaluated. Compared with placebo, empagliflozin lowered glycated haemoglobin, systolic blood pressure, and body weight and rates of all the HF endpoints, as early as at 12 weeks, regardless of HF status at baseline. Favourable clinical and metabolic effects were maintained over time. AEs were generally higher in those with HF than without HF; however, compared with placebo, empagliflozin did not increase risk of developing AEs over the first year of treatment. CONCLUSIONS: In the EMPA-REG OUTCOME trial, the use of empagliflozin led to early and beneficial effects on clinical, metabolic, and HF outcomes in patients with type 2 diabetes with or without HF at baseline, which were already apparent within 12 weeks from initiation of treatment. Over the first year of treatment, no safety concern was detected with the use of empagliflozin.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".