Sacubitril/valsartan and quality of life assessed using the EuroQol Five-dimension Three-level questionnaire level sum score (EQ-5D-3L-LSS) in patients with HFrEF and HFmrEF/HFpEF
Bibliographic record
Abstract
AIMS: To investigate the EQ-5D-3L Level Sum Score (LSS) in patients with heart failure (HF) and reduced (HFrEF) and mildly reduced or preserved ejection fraction (HFmrEF/HFpEF) and the effect of sacubitril/valsartan on this score using patient-level data from the PARADIGM-HF and PARAGON-HF trials. METHODS AND RESULTS: The LSS was calculated by summing the three levels (1-3) for each of the five domains (minimum sum score = 5; maximum sum score = 15). Patient characteristics and outcomes were compared across LSS tertiles (T1-T3) at baseline. Cox models were used to evaluate the primary endpoint [first HF hospitalization or cardiovascular death (CVD)] according to tertiles of LSS. Changes in LSS severity at 8 months were analysed using ordinal logistic regression models to estimate the effect of sacubitril/valsartan vs. enalapril or valsartan. Of 13 195 patients, 12 974 had a baseline LSS. Compared to lower LSS, patients with higher (worse) scores were older, more often women and White, and had more comorbidities and more severe HF. At 8 months, patients assigned to sacubitril/valsartan experienced more improvement and less worsening of LSS vs. the comparator: OR:1.16 (95%CI: 1.08-1.24). Sacubitril/valsartan also reduced the risk of the primary outcome across LSS tertiles: T1: HR: 0.87 (95%CI: 0.75-1.00); T2: 0.80 (95%CI: 0.71-0.90); T3: 0.87 (95%CI: 0.77-0.97); Pinteraction = 0.59. Higher LSS was independently associated with a greater risk of the primary endpoint, and the achieved LSS at 8 months may be more strongly associated with subsequent outcomes. CONCLUSION: Sacubitril/valsartan significantly reduced the risk of HF events and improved health status across the LSS spectrum in HFrEF and HFmrEF/HFpEF. CLINICAL TRIAL REGISTRATION: https://www.clinicaltrials.gov. Unique identifiers: NCT01920711 (PARAGON-HF), NCT01035255 (PARADIGM-HF).
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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 | 0.003 | 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".