<scp>Health‐related</scp> quality of life outcomes in <scp>PARAGON‐HF</scp>
Bibliographic record
Abstract
AIMS: Heart failure (HF) is associated with poor health-related quality of life (HRQL). Patients with HF with preserved ejection fraction (HFpEF) have similar HRQL impairment as those with reduced ejection fraction. This study describes the impact of sacubitril/valsartan on HRQL in patients with HFpEF enrolled in the PARAGON-HF trial. METHODS AND RESULTS: Patients completed the Kansas City Cardiomyopathy Questionnaire (KCCQ) and EuroQol (EQ-5D) at randomization, 4, 8 months, and annually thereafter. Changes in HRQL scores were evaluated using repeated measures models adjusted for treatment, baseline values and region. The pre-specified principal efficacy assessment was at 8 months at which time patients randomized to sacubitril/valsartan had borderline higher KCCQ clinical summary score (CSS) with least squares mean (LSM) adjusted difference of 1.0 (95% confidence interval [CI] 0.0, 2.1; p = 0.051). Including all visits up to 36 months, the LSM difference in KCCQ-CSS favoured sacubitril/valsartan with average adjusted difference of 1.1 (95% CI 0.1, 2.0; p = 0.034). Patients treated with sacubitril/valsartan had greater odds of clinically meaningful improvement (≥5-point increase) in KCCQ-CSS (odds ratio 1.31; 95% CI 1.06, 1.61) at 8 months. At 8 months, there was no significant difference in the EQ visual analogue scale between the treatment arms, but sacubitril/valsartan was associated with higher EQ-5D utility score (US-based) with LSM adjusted difference of 0.01 (95% CI 0.00, 0.02; p = 0.019). CONCLUSION: Compared with valsartan, sacubitril/valsartan had a borderline benefit on KCCQ-CSS at 8 months in patients with HFpEF. This benefit became more significant when data from all visits up to 36 months were included. This modest overall benefit was also supported by greater odds of patients reporting a clinically meaningful improvement in HRQL with sacubitril/valsartan.
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".