Empagliflozin and health-related quality of life outcomes in patients with heart failure with reduced ejection fraction: the EMPEROR-Reduced trial
Bibliographic record
Abstract
AIMS: In this secondary analysis of the EMPEROR-Reduced trial, we sought to evaluate whether the benefits of empagliflozin varied by baseline health status and how empagliflozin impacted patient-reported outcomes in patients with heart failure with reduced ejection fraction. METHODS AND RESULTS: Health status was assessed by the Kansas City Cardiomyopathy Questionnaires-clinical summary score (KCCQ-CSS). The influence of baseline KCCQ-CSS (analyzed by tertiles) on the effect of empagliflozin on major outcomes was examined using Cox proportional hazards models. Responder analyses were performed to assess the odds of improvement and deterioration in KCCQ scores related to treatment with empagliflozin. Empagliflozin reduced the primary outcome of cardiovascular death or heart failure hospitalization regardless of baseline KCCQ-CSS tertiles [hazard ratio (HR) 0.83 (0.68-1.02), HR 0.74 (0.58-0.94), and HR 0.61 (0.46-0.82) for <62.5, 62.6-85.4, and ≥85.4 score tertiles, respectively; P-trend = 0.10]. Empagliflozin improved KCCQ-CSS, total symptom score, and overall summary score at 3, 8, and 12 months. More patients on empagliflozin had ≥5-point [odds ratio (OR) 1.20 (1.05-1.37)], 10-point [OR 1.26 (1.10-1.44)], and 15-point [OR 1.29 (1.12-1.48)] improvement and fewer had ≥5-point [OR 0.75 (0.64-0.87)] deterioration in KCCQ-CSS at 3 months. These benefits were sustained at 8 and 12 months and were similar for other KCCQ domains. CONCLUSION: Empagliflozin improved cardiovascular death or heart failure hospitalization risk across the range of baseline health status. Empagliflozin improved health status across various domains, and this benefit was sustained during long-term follow-up. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov. Unique identifier: NCT03057977.
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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) | 0.001 | 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".