Changes in N-Terminal Pro-B-Type Natriuretic Peptide Levels and Outcomes in Heart Failure with Preserved Ejection Fraction: An Analysis of the I-Preserve Study
Bibliographic record
Abstract
AIMS: In patients with heart failure (HF) and reduced ejection fraction, decreases or increases in NT-proBNP levels are associated with better and worse outcomes, respectively. The association in HF and preserved ejection fraction (HF-PEF) is unknown. We examined the association between change in level of NT-proBNP and prognosis in patients with HF-PEF. METHODS AND RESULTS: We examined the association between change in NT-proBNP from baseline to 6 months and cardiovascular (CV) death or HF hospitalization in 2612 participants in the Irbesartan in Patients with Heart Failure and Preserved Systolic Function Study (I-Preserve). Change in NT-proBNP was modelled as a restricted cubic spline in a Cox model after adjusting for baseline NT-proBNP and known prognostic variables. Median change in NT-proBNP from baseline was -7 pg/mL (interquartile range -143 to +108). After adjustment, a 1000 pg/mL decrease in NT-proBNP from baseline was associated with a reduction in the risk of CV death or HF hospitalization [hazard ratio (HR) 0.73, 95% confidence interval (CI) 0.53-1.02]; a 1000 pg/mL increase was associated with an increase in risk (HR 2.01, 95% CI 1.50-2.69). Beyond a 1000 pg/mL rise or fall, there was little additional change in risk. Addition of change in NT-proBNP at 6 months to a model with only baseline NT-proBNP improved the C-statistic from 0.752 to 0.769 (P = 0.013). CONCLUSION: In HF-PEF, a rise in NT-proBNP was associated with an increase in risk of CV death or HF hospitalization and a fall was associated with a trend towards a decrease in risk. NT-proBNP may be a useful marker to monitor prognosis in this condition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".