Prognostic value of serial measurements of blood urea nitrogen in ambulatory patients with chronic heart failure.
Bibliographic record
Abstract
BACKGROUND: Elevated blood urea nitrogen (BUN) in chronic heart failure (CHF) patients may represent increased neurohormonal activation. The purpose of this work was to evaluate the prognostic value of BUN and its variation in ambulatory patients with stable CHF. METHODS: In a retrospective analysis we included 241 outpatients with stable CHF (NYHA class I-III). We evaluated patients at baseline and at 6 months, then they have been followed for one year. The population was divided in four groups according to the median value of BUN at baseline and BUN change (percentage) at 6 months (group 1 BUN <25.2 mg/dL and variation <3.4%, group 2 BUN <25.2 mg/dL and ≥3.4 %, group 3 BUN ≥25.2 mg/dL and <3.4%, group 4 BUN ≥25.2 mg/dL and ≥3.4%). During a median follow-up of one year, 3 (1.3%) patients died and 49 (20.3%) were hospitalized due to worsening heart failure HF. RESULTS: The Kaplan-Meier curve showed that group 3 and group 4 had worse prognosis compared with group 1 and 2 and that a greater change in BUN, was associated with a further worsening of the prognosis (group 4). Multivariable models confirmed that cardiovascular mortality and HF hospitalizations were more frequent in patients who had an increase of BUN (HR 1.011 [IC 95% 1.002-1.021]; P=0.015). CONCLUSIONS: In ambulatory patients with stable chronic heart failure the increment of BUN is associated with increased cardiovascular mortality and heart failure hospitalizations at one-year.
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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 | 0.000 | 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".