N-terminal Pro-B–Type Natriuretic Peptide (NT-proBNP) Concentrations in Hemodialysis Patients: Prognostic Value of Baseline and Follow-up Measurements
Bibliographic record
Abstract
BACKGROUND: Increased N-terminal pro-B-type natriuretic peptide (NT-proBNP) concentrations are associated with increased cardiovascular mortality in chronic hemodialysis patients. Previous studies focused on prevalent dialysis patients and examined single measurements of NT-proBNP in time. METHODS: We measured NT-proBNP concentrations in 2990 incident hemodialysis patients to examine the risk of 90-day and 1-year mortality associated with baseline NT-proBNP concentrations. In addition, we calculated the change in concentrations after 3 months in a subset of 585 patients to examine the association between longitudinal changes in NT-proBNP and subsequent mortality. RESULTS: Increasing quartiles of NT-proBNP were associated with a monotonic increase in 90-day [quartile 1, referent; from quartile 2 to quartile 4, hazard ratio (HR) 1.7-6.3, P < 0.001] and 1-year (quartile 1, referent; from quartile 2 to quartile 4, HR 1.7-4.9, P < 0.001) all-cause mortality. After multivariable adjustment, these associations remained robust. When examined using a multivariable fractional polynomial, increased NT-proBNP concentrations were associated with increased 90-day (HR per unit increase in log NT-proBNP 1.5, 95% CI 1.3-1.7) and 1-year (HR per unit increase in log NT-proBNP 1.4, 95% CI 1.3-1.5) all-cause mortality. In addition, patients with the greatest increase in NT-proBNP after 3 months of dialysis had a 2.4-fold higher risk of mortality than those with the greatest decrease in NT-proBNP. CONCLUSIONS: NT-proBNP concentrations are independently associated with mortality in incident hemodialysis patients. Furthermore, the observation that longitudinal changes in NT-proBNP concentrations were associated with subsequent mortality suggests that monitoring serial NT-proBNP concentrations may represent a novel tool for assessing adequacy and guiding therapy in patients initiating hemodialysis.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".