Abstract 4140480: The Relationship Between Obesity Status and Change in NT-proBNP with Angiotensin-Neprilysin Inhibition in Patients with Mildly Reduced or Preserved Ejection Fraction and Recent Worsening Heart Failure Event: Results from the PARAGLIDE-HF Trial
Bibliographic record
Abstract
Background: In PARAGLIDE-HF, patients with heart failure with mildly reduced or preserved ejection fraction (HFpEF) and a recent worsening HF event randomized to sacubitril/valsartan (sac/val) vs val had a significantly larger reduction in NT-proBNP and were numerically more likely to derive clinical benefit as assessed by a win ratio. Patients with obesity and HFpEF may represent a unique phenotype, characterized by a high risk for recurrent HF hospitalization and lower levels of NT-proBNP. Research Question: Does BMI category modify the relationship between sac/val vs val on NT-proBNP change and/or a win ratio among patients with HFpEF or mildly reduced EF? Methods: To assess the interaction between BMI and sac/val vs val on NT-proBNP, the time-averaged proportional change in NT-proBNP from baseline to Weeks 4 and 8 was assessed with an analysis of covariance model including the interaction of treatment-by-BMI group (obese with BMI ≥30 vs normal/overweight, BMI 18.5 to <30 kg/m 2 ). A win ratio of cardiovascular death, total HF hospitalizations, urgent HF visits, and change in NT-proBNP was calculated for both BMI groups, including an interaction term with significance set at ≤0.1. Results: Overall, 65% (n=298) of patients had obesity and 35% (n=164) of patients had normal/overweight. When the interaction between BMI category and the effect of sac/val vs val on the time-averaged proportional change from baseline NT-proBNP was assessed, patients with obesity had a non-significant but numerically larger decrease in NT-proBNP ( Table ). Patients with obesity were also more likely to derive clinical benefit overall from sac/val vs val as compared to patients with normal/overweight (win ratio 1.38, 95% CI 1.01-1.90 vs 0.90, 95% CI 0.62-1.32, p interaction = 0.09). Conclusion: These preliminary data suggest that patients with HF with mildly reduced or preserved EF and obesity may experience a larger clinical benefit from sac/val than patients with normal/overweight BMI.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".