Vascular Disease Burden, Outcomes and Benefits with Empagliflozin in Heart Failure: Insights From the EMPEROR-Reduced Trial
Bibliographic record
Abstract
BACKGROUND: The presence of ischemic heart disease impacts prognosis in patients affected by heart failure and reduced ejection fraction (HFrEF). It is not well known how the extent of vascular disease impacts prognoses and responses to therapy in this setting. METHODS: vs poly [≥ 2] vascular bed) of vascular disease. Vascular disease was defined as investigator-reported coronary artery disease (CAD), peripheral artery disease (PAD) and cerebrovascular disease at baseline. Cox proportional-hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). Incidence rates are presented per 100 person-years (py) of follow-up. RESULTS: Of the 3730 study participants enrolled, 1324 (35.5%) had no vascular disease, 1879 (50.4%) had monovascular disease, and 527 (14.1%) had polyvascular disease. Participants with polyvascular disease tended to be older and male and to have had histories of hypertension, diabetes and smoking. In the placebo arm, a significantly higher risk for cardiovascular death existed in those with polyvascular disease (HR 1.57, 95% CI1.02, 2.44, compared to those with no vascular disease). In adjusted analysis, the benefit of empagliflozin in cardiovascular death or hospitalization due to HF, HF hospitalization, cardiovascular death, renal composite endpoint, estimated glomerular filtration slope changes, and health status scores were seen across the 3 groups (interaction P > 0.05 for all) but were attenuated in those with polyvascular disease. Adverse events were higher in those with polyvascular disease, but no major differences were noted between empagliflozin or placebo assignment in the 3 groups. CONCLUSION: In patients with HFrEF, the extent of vascular disease is associated with the risk for adverse cardiovascular outcomes. Empagliflozin offers cardiovascular and renal benefits in HFrEF across the extent of vascular disease, but this benefit is attenuated in those with polyvascular disease.
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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) | 0.000 | 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".