Changes in urine volume and serum albumin in incident hemodialysis patients
Bibliographic record
Abstract
Abstract Introduction: Hypoalbuminemia is a predictor of poor outcomes in dialysis patients. Among hemodialysis patients, there has not been prior study of whether residual kidney function or decline over time impacts serum albumin levels. We hypothesized that a decline in residual kidney function is associated with an increase in serum albumin levels among incident hemodialysis patients. Methods: In a large national cohort of 38,504 patients who initiated hemodialysis during 1/2007‐12/2011, we examined the association of residual kidney function, ascertained by urine volume and renal urea clearance, with changes in serum albumin over five years across strata of baseline residual kidney function, race, and diabetes using case‐mix adjusted linear mixed effects models. Findings: Serum albumin levels increased over time. At baseline, patients with greater urine volume had higher serum albumin levels: 3.44 ± 0.48, 3.50 ± 0.46, 3.57 ± 0.44, 3.59 ± 0.45, and 3.65 ± 0.46 g/dL for urine volume groups of <300, 300–<600, 600–<900, 900–<1,200, and ≥1,200 mL/day, respectively (Ptrend < 0.001). Over time, urine volume and renal urea clearance declined and serum albumin levels rose, while the baseline differences in serum albumin persisted across groups of urinary volume. In addition, the rate of decline in residual kidney function was not associated with the rate of change in albumin. Discussion: Hypoalbuminemia in hemodialysis patients is associated with lower residual kidney function. Among incident hemodialysis patients, there is a gradual rise in serum albumin that is independent of the rate of decline in residual kidney function, suggesting that preservation of residual kidney function does not have a deleterious impact on serum albumin levels.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".