Effect of Sacubitril/Valsartan in Heart Failure with Preserved Ejection Fraction Across the Age Spectrum in PARAGON-HF
Bibliographic record
Abstract
Abstract Aims To evaluate clinical outcomes, echocardiographic features, and the efficacy and safety of sacubitril/valsartan compared to valsartan across age groups in the PARAGON-HF trial. Methods and results A total of 4796 participants ≥50 years of age with chronic heart failure (HF) and left ventricular ejection fraction (LVEF) ≥45% were divided into three age groups: <65 years (n = 825), 65–74 years (n = 1772), and ≥75 years (n = 2199). Echocardiograms of 1097 patients were analysed in a standardized fashion at a core imaging laboratory. The primary composite outcome was total HF hospitalizations and cardiovascular (CV) death. Older patients were more likely to experience primary composite outcomes (compared to patients <65 years, adjusted rate ratio [aRR] for ≥75 years: 1.39, 95% confidence interval [CI] 1.21–1.61), total HF hospitalization (aRR 1.27, 95% CI 1.09–1.49), and CV death (adjusted hazard ratio [aHR] 2.04, 95% CI 1.44–2.87). Age did not modify the effect of sacubitril/valsartan compared to valsartan on primary composite endpoint (pinteraction = 0.79) in the overall population or in those with LVEF ≤57%. Older adults randomized to sacubitril/valsartan were more likely to develop hypotension compared to those receiving valsartan (pinteraction = 0.026). Older patients had smaller left ventricular chamber sizes, higher LVEF, and were more likely to have abnormal measures of diastolic function. Conclusion Older patients with HF with preserved ejection fraction had higher event rates than younger patients, more adverse events overall, and more hypotension when treated with sacubitril/valsartan; however, the treatment benefits of sacubitril/valsartan were retained in older patients.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".