A Direct Comparison of the Natriuretic Peptides and Their Relationship to Survival in Chronic Heart Failure of a Presumed Non-Ischaemic Origin
Bibliographic record
Abstract
The natriuretic peptides have been validated as sensitive and specific markers of left ventricular dysfunction; brain natriuretic peptide (BNP), N-terminal atrial natriuretic peptide (NT-proANP) and N-terminal brain natriuretic peptide (NT-proBNP) elevations have been associated with New York Heart Association (NYHA) Class I-IV heart failure. We directly compared the association of each of these markers with 1-year survival in 173 patients with chronic heart failure of a presumed nonischaemic origin entering the PRAISE-2 Trial, a clinical study which assessed the therapeutic effect of Amlodipine in patients with NYHA Class III and IV heart failure and a left ventricular ejection fraction (LVEF) <30%. BNP, NT-proBNP, and NT-proANP levels were all correlated with 1-year mortality by univariate Cox proportional hazards analyses. With respect to multivariate Cox proportional hazards regression models containing variables deemed significant in univariate analyses, NT-proANP alone was identified as an independent predictor of 1-year mortality when log-transformed continuous covariates were utilized in the analysis. When the analysis was repeated using dichotomous covariates, NT-proANP remained the most significant predictor of 1-year mortality, followed by NT-proBNP, NYHA classification and BNP. We conclude that all three natriuretic peptides are significant predictors of short-term mortality in subjects with chronic congestive heart failure (CHF) of a presumed nonischaemic origin. Larger prospective studies are required to validate the clinical utility of NT-proANP as a discriminating marker of short-term survival, and to validate proposed cutoffs of approximately 2300 pmol/l for NT-proANP, 1500 pg/ml for NT-proBNP, and 50 pmol/l for BNP as prognostic indicators of adverse short-term outcome.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".