Brain natriuretic peptide reflects individual variation in hydration status in hemodialysis patients
Bibliographic record
Abstract
INTRODUCTION: Fluid management in hemodialysis patients is a controversial topic. Brain natriuretic peptide (BNP) is secreted from the heart in response to volume overload, and may be a marker of overhydration in hemodialysis patients. Our aim was to investigate the correlation between BNP and overhydration in a cohort of hemodialysis patients, and to find out whether BNP and overhydration correlate in repeated measurements within individuals with elevated BNP. METHODS: The study was prospective, observational, and had a cross-sectional part and a longitudinal follow-up. The distribution of BNP was investigated in a cohort of 64 hemodialysis patients. Blood samples and bioimpedance spectroscopy measurements were performed before midweek dialysis. Subsequently, 11 study participants with elevated BNP concentrations (>500 pg/mL) were assessed in another nine dialysis sessions each. These individuals also had their cardiac function and heart rate variability (HRV) examined. FINDINGS: = 0.381), inflammation and malnutrition, but not with systolic blood pressure. In comparison to participants with BNP below 500 pg/mL, participants with elevated BNP were older, had lower muscle strength, lower bodyweight and lower levels of hemoglobin and albumin. Echocardiography revealed cardiac anomalies in all 11 participants in the longitudinal follow-up, and HRV, as measured by SDNN, was pathologically low. In repeated measurements, the between-individuals variation of BNP in relation to overhydration was greater (SD = 0.581) than the within-person variation (SD = 0.285). DISCUSSION: BNP correlates positively to overhydration, malnutrition, and inflammation. In a subgroup of patients with elevated BNP, who are mainly elderly and frail, BNP reflects individual variation in hydration status, and hence seems to be a modifiable marker of overhydration. These data suggest that BNP is best applied for measuring changes in hydration status within an individual over time.
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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 | 0.002 |
| 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) | 0.001 | 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".