Comparison of BNP and NT-proBNP in Patients With Heart Failure and Reduced Ejection Fraction
Bibliographic record
Abstract
Background: Both BNP (B-type natriuretic peptide) and NT-proBNP (N-terminal pro B-type natriuretic peptide) are widely used to aid diagnosis, assess the effect of therapy, and predict outcomes in heart failure and reduced ejection fraction. However, little is known about how these 2 peptides compare in heart failure and reduced ejection fraction, especially with contemporary assays. Both peptides were measured at screening in the PARADIGM-HF trial (Prospective Comparison of ARNI With ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure). Methods: Eligibility criteria in PARADIGM-HF included New York Heart Association functional class II to IV, left ventricular ejection fraction ≤40%, and elevated natriuretic peptides: BNP ≥150 pg/mL or NT-proBNP ≥600 pg/mL (for patients with HF hospitalization within 12 months, BNP ≥100 pg/mL or NT-proBNP ≥400 pg/mL). BNP and NT-proBNP were measured simultaneously at screening and only patients who fulfilled entry criteria for both natriuretic peptides were included in the present analysis. The BNP/NT-proBNP criteria were not different for patients in atrial fibrillation. Estimated glomerular filtration rate <30 mL/min per 1.73 m 2 was a key exclusion criterion. Results: The median baseline concentration of NT-proBNP was 2067 (Q1, Q3: 1217–4003) and BNP 318 (Q1, Q3: 207–559), and the ratio, calculated from the raw data, was ≈6.25:1. This ratio varied considerably according to rhythm (atrial fibrillation 8.03:1; no atrial fibrillation 5.75:1) and with age, renal function, and body mass index but not with left ventricular ejection fraction. Each peptide was similarly predictive of death (all-cause, cardiovascular, sudden and pump failure) and heart failure hospitalization, for example, cardiovascular death: BNP hazard ratio, 1.41 (95% CI, 1.33–1.49) per 1 SD increase, P <0.0001; NT-proBNP, 1.45 (1.36–1.54); P <0.0001. Conclusions: The ratio of NT-proBNP to BNP in heart failure and reduced ejection fraction appears to be greater than generally appreciated, differs between patients with and without atrial fibrillation, and increases substantially with increasing age and decreasing renal function. These findings are important for comparison of natriuretic peptide concentrations in heart failure and reduced ejection fraction.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".