Effects of Dapagliflozin on Symptoms, Function, and Quality of Life in Patients With Heart Failure and Reduced Ejection Fraction
Bibliographic record
Abstract
Background: Goals of management in patients with heart failure and reduced ejection fraction include reducing death and hospitalizations, and improving health status (symptoms, physical function, and quality of life). In the DAPA-HF trial (Dapagliflozin and Prevention of Adverse-Outcomes in Heart Failure), sodium–glucose cotransporter-2 inhibitor, dapagliflozin, reduced death and hospitalizations, and improved symptoms in patients with heart failure and reduced ejection fraction. In this analysis, we examine the effects of dapagliflozin on a broad range of health status outcomes, using the Kansas City Cardiomyopathy Questionnaire (KCCQ). Methods: KCCQ was evaluated at randomization, 4 and 8 months. Patients were divided by baseline KCCQ total symptom score (TSS); Cox proportional hazards models examined the effects of dapagliflozin on clinical events across these subgroups. We also evaluated the effects of dapagliflozin on KCCQ-TSS, clinical summary score, and overall summary score. Responder analyses were performed to compare proportions of dapagliflozin versus placebo-treated patients with clinically meaningful changes in KCCQ at 8 months. Results: A total of 4443 patients had available KCCQ at baseline (median KCCQ-TSS, 77.1 [interquartile range, 58.3–91.7]). The effects of dapagliflozin vs placebo on reducing cardiovascular death or worsening heart failure were consistent across the range of KCCQ-TSS (lowest to highest tertile: hazard ratio, 0.70 [95% CI, 0.57–0.86]; hazard ratio, 0.77 [95% CI, 0.61–0.98]; hazard ratio, 0.62 [95% CI, 0.46–0.83]; P for heterogeneity=0.52). Patients treated with dapagliflozin had greater improvement in mean KCCQ-TSS, clinical summary score, and overall summary score at 8 months (2.8, 2.5 and 2.3 points higher versus placebo; P <0.0001 for all). Fewer patients treated with dapagliflozin had a deterioration in KCCQ-TSS (odds ratio, 0.84 [95% CI, 0.78–0.90]; P <0.0001); and more patients had at least small, moderate, and large improvements (odds ratio, 1.15 [95% CI, 1.08–1.23]; odds ratio, 1.15 [95% CI, 1.08–1.22]; odds ratio, 1.14 [95% CI, 1.07–1.22]; number needed to treat=14, 15, and 18, respectively; P <0.0001 for all; results consistent for KCCQ clinical summary score and overall summary score). Conclusions: Dapagliflozin reduced cardiovascular death and worsening heart failure across the range of baseline KCCQ, and improved symptoms, physical function, and quality of life in patients with heart failure and reduced ejection fraction. Furthermore, dapagliflozin increased the proportion of patients experiencing at least small, moderate, and large improvements in health status; these effects were clinically important. Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT03036124.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".