Role of Residual Renal Function in Phosphate Control and Anemia Management in Chronic Hemodialysis Patients
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: There is increasing awareness that residual renal function (RRF) has beneficial effects in hemodialysis (HD) patients. The aim of this study was to investigate the role of RRF, expressed as GFR, in phosphate and anemia management in chronic HD patients. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Baseline data of 552 consecutive patients from the Convective Transport Study (CONTRAST) were analyzed. Patients with a urinary output≥100 ml/24 h (n=295) were categorized in tertiles on the basis of degree of GFR and compared with anuric patients (i.e., urinary output<100 ml/24 h, n=274). Relations between GFR and serum phosphate and erythropoiesis-stimulating agent (ESA) index (weekly ESA dose per kg body weight divided by hematocrit) were analyzed with multivariable regression models. RESULTS: Phosphate levels were between 3.5 and 5.5 mg/dl in 68% of patients in the upper tertile (GFR>4.13 ml/min per 1.73 m2), as compared with 46% in anuric patients despite lower prescription of phosphate-binding agents. Mean hemoglobin levels were 11.9±1.2 g/dl with no differences between the GFR categories. The ESA index was 31% lower in patients in the upper tertile as compared with anuric patients. After adjustments for patient characteristics, patients in the upper tertile had significantly lower serum phosphate levels and ESA index as compared with anuric patients. CONCLUSIONS: This study suggests a strong relation between RRF and improved phosphate and anemia control in HD patients. Efforts to preserve RRF in HD patients could improve outcomes and should be encouraged.
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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 | 0.004 |
| 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 | 0.000 | 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".