Rationale, Design and Baseline Characteristics of the PARAGLIDE-HF Trial: Sacubitril/Valsartan vs Valsartan in HFmrEF and HFpEF With a Worsening Heart Failure Event
Bibliographic record
Abstract
BACKGROUND: The PARAGON-HF trial studied the effect of sacubitril/valsartan (Sac/Val) compared with valsartan (Val) on clinical outcomes in patients with chronic heart failure with preserved ejection fraction (HFpEF) or mildly reduced EF (HFmrEF). Further data are needed regarding the use of Sac/Val in these groups with EF and with recent worsening heart failure (WHF) events and in key populations not broadly represented in the PARAGON-HF trial, including those with de novo HF, the severely obese and Black patients. METHODS: The PARAGLIDE-HF trial is a multicenter, double-blind, randomized, controlled trial of Sac/Val vs Val that enrolled patients at 100 sites. Medically stable patients ≥ 18 years old with EF > 40%, amino terminal-pro B-type natriuretic peptide (NT-proBNP) levels ≥ 500 pg/mL and within 30 days of a WHF event were eligible for participation. Patients were randomly assigned 1:1 to Sac/Val vs Val. The primary efficacy endpoint is time-averaged proportional change in NT-proBNP from baseline through Weeks 4 and 8. Secondary endpoints include clinical outcomes during follow-up and additional biomarker assessments. Safety endpoints include symptomatic hypotension, worsening renal function and hyperkalemia. RESULTS: ). The median (IQR) EF was 55% (50%-60%), 23% with HFmrEF (LVEF 41%-49%), 24% with EF > 60% and 33% with de novo HFpEF. Median screening NT-proBNP was 2009 (1291-3813) pg/mL, and 69% were enrolled in the hospital. CONCLUSIONS: The PARAGLIDE-HF trial enrolled a broad and diverse range of patients with heart failure with mildly reduced or preserved ejection fraction and will inform clinical practice by providing evidence about the safety, tolerability and efficacy of Sac/Val vs Val in those with a recent WHF event.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.037 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 0.006 |
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".