P3373Better health-related quality of life in patients treated with sacubitril/valsartan compared with enalapril, irrespective of NYHA class: Analysis of EQ-5D in PARADIGM-HF
Bibliographic record
Abstract
Background: The totality of a patient's health-related quality of life (HRQL) experience may be better assessed by a generic rather than a disease-specific instrument. We assessed HRQL with a validated and widely used generic instrument, the EQ-5D-3L, in PARADIGM-HF. PARADIGM-HF was a randomised controlled trial which compared sacubitril/valsartan with enalapril in patients with heart failure and reduced ejection fraction. Methods: The EQ-5D-3L is a patient-completed HRQL instrument evaluating five dimensions (mobility, self-care, usual activities, pain/discomfort, and anxiety/depression), each with 3 levels of response. In PARADIGM-HF, the EQ-5D was administered at baseline, months 4, 8, 12, 24 and 36. The EQ-5D index value sets (based on public preferences) were applied to domain-level EQ-5D responses to generate EQ-5D index scores for each subject at each available observation from PARADIGM-HF, with zero representing death and one perfect health. Changes in EQ-5D from baseline were calculated using a repeated measures mixed-effects model that adjusted for treatment, region, month, New York Heart Association (NYHA) class, treatment-by-month-by-NHYA class interaction and baseline EQ-5D. We dichotomized patients according to baseline NYHA) class i.e. as NYHA class categories I/II and III/IV. EQ-5D scores following death were treated as missing.
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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 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".