Empagliflozin, Health Status, and Quality of Life in Patients With Heart Failure and Preserved Ejection Fraction: The EMPEROR-Preserved Trial
Bibliographic record
Abstract
Background: Patients with heart failure with preserved ejection fraction have significant impairment in health-related quality of life. In the EMPEROR-Preserved trial (Empagliflozin Outcome Trial in Patients With Chronic Heart Failure With Preserved Ejection Fraction), we evaluated the efficacy of empagliflozin on health-related quality of life in patients with heart failure with preserved ejection fraction and whether the clinical benefit observed with empagliflozin varies according to baseline health status. Methods: Health-related quality of life was measured with the Kansas City Cardiomyopathy Questionnaire (KCCQ) at baseline and 12, 32, and 52 weeks. Patients were divided by baseline KCCQ Clinical Summary Score (CSS) tertiles, and the effect of empagliflozin on outcomes was examined. The effect of empagliflozin on KCCQ-CSS, Total Symptom Score, and Overall Summary Score was evaluated. Responder analyses were performed to compare the odds of improvement and deterioration in KCCQ related to treatment with empagliflozin. Results: The effect of empagliflozin on reducing the risk of time to cardiovascular death or heart failure hospitalization was consistent across baseline KCCQ-CSS tertiles (hazard ratio, 0.83 [95% CI, 0.69–1.00], 0.70 [95% CI, 0.55–0.88], and 0.82 [95% CI, 0.62–1.08] for scores <62.5, 62.5–83.3, and ≥83.3, respectively; P trend=0.77). Similar results were seen for total heart failure hospitalizations. Patients treated with empagliflozin had significant improvement in KCCQ-CSS versus placebo (+1.03, +1.24, and +1.50 at 12, 32, and 52 weeks, respectively; P <0.01); similar results were seen for Total Symptom Score and Overall Summary Score. At 12 weeks, patients on empagliflozin had higher odds of improvement ≥5 points (odds ratio, 1.23 [95% CI, 1.10–1.37]), ≥10 points (odds ratio, 1.15 [95% CI, 1.03–1.27]), and ≥15 points (odds ratio, 1.13 [95% CI, 1.02–1.26]) and lower odds of deterioration ≥5 points in KCCQ-CSS (odds ratio, 0.85 [95% CI, 0.75–0.97]). A similar pattern was seen at 32 and 52 weeks, and results were consistent for Total Symptom Score and Overall Summary Score. Conclusions: In patients with heart failure with preserved ejection fraction, empagliflozin reduced the risk for major heart failure outcomes across the range of baseline KCCQ scores. Empagliflozin improved health-related quality of life, an effect that appeared early and was sustained for at least 1 year. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03057951.
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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) | 0.000 | 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".