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 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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".