Efficacy of Empagliflozin in Patients With Heart Failure Across Kidney Risk Categories
Bibliographic record
Abstract
BACKGROUND: Empagliflozin reduces the risk of major heart failure outcomes in heart failure with reduced or preserved ejection fraction. OBJECTIVES: The goal of this study was to evaluate the effect of empagliflozin across the spectrum of chronic kidney disease in a pooled analysis of EMPEROR-Reduced and EMPEROR-Preserved (Empagliflozin Outcome Trial in Patients with Chronic Heart Failure with Reduced or Preserved Ejection Fraction, respectively). METHODS: A total of 9,718 patients were grouped into Kidney Disease Improving Global Outcomes (KDIGO) categories based on estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio into low-, moderate-, high-, and very-high-risk categories, comprising 32.0%, 29.1%, 21.9%, and 17.0% of the participants, respectively. RESULTS: In the placebo arm, when compared with lower risk categories, patients at higher risk experienced a slower rate of decline in eGFR, but a higher risk of a composite kidney event. Empagliflozin reduced the risk of cardiovascular death or heart failure hospitalizations similarly in all KDIGO categories (HR: 0.81; 95% CI: 0.66-1.01 for low-; HR: 0.63; 95% CI: 0.52-0.76 for moderate-; HR: 0.82; 95% CI: 0.68-0.98 for high-; and HR: 0.84; 95% CI: 0.71-1.01 for very-high-risk groups; P trend = 0.30). Empagliflozin reduced the rate of decline in eGFR whether it was estimated by chronic slope, total slope, or unconfounded slope. When compared with the unconfounded slope, the magnitude of the effect on chronic slope was larger, and the effect on total slope was smaller. In EMPEROR-Reduced, patients at lowest risk experienced the largest effect of empagliflozin on eGFR slope; this pattern was not observed in EMPEROR-Preserved. CONCLUSIONS: The benefit of empagliflozin on major heart failure events was not influenced by KDIGO categories. The magnitude of the renal effects of the drug depended on the approach used to calculate eGFR slopes.
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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| 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".