Comparison of Omapatrilat and Enalapril in Patients With Chronic Heart Failure
Bibliographic record
Abstract
BACKGROUND: Combined inhibition of the angiotensin-converting enzyme (ACE) and neutral endopeptidase (NEP) may produce greater benefits in heart failure than ACE inhibition alone. METHODS AND RESULTS: We randomly assigned 5770 patients with New York Heart Association class II to IV heart failure to double-blind treatment with either the ACE inhibitor enalapril (10 mg BID, n=2884) or to the ACE-NEP inhibitor omapatrilat (40 mg once daily, n=2886) for a mean of 14.5 months. The primary end point-the combined risk of death or hospitalization for heart failure requiring intravenous treatment--was used prospectively to test both a superiority and noninferiority hypothesis (based on the effect of enalapril in the Studies of Left Ventricular Dysfunction [SOLVD] Treatment Trial). A primary end point was achieved in 973 patients in the enalapril group and in 914 patients in the omapatrilat group (hazard ratio 0.94; 95% CI: 0.86 to 1.03, P=0.187)--a result that fulfilled prespecified criteria for noninferiority but not for superiority. The omapatrilat group also had a 9% lower risk of cardiovascular death or hospitalization (P=0.024) and a 6% lower risk of death (P=0.339). Post hoc analysis of the primary end point with the definition used in the SOLVD Treatment Trial (which included all hospitalizations for heart failure) showed an 11% lower risk in patients treated with omapatrilat (nominal P=0.012). CONCLUSION: Omapatrilat reduces the risk of death and hospitalization in chronic heart failure but was not more effective than ACE inhibition alone in reducing the risk of a primary clinical event. Between-group differences in favor of omapatrilat observed in secondary and post hoc analyses warrant further study.
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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 | 0.003 | 0.004 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".