Pruritus in hemodialysis patients: The problem remains
Bibliographic record
Abstract
Pruritus is still one of the most common and disturbing symptoms of end-stage renal disease. The objective of this study is to analyze the prevalence of pruritus in hemodialysis patients and the possible factors implicated in its genesis. In a cross-sectional study, 101 patients on hemodialysis at our center were screened for pruritus. The relationship of various factors with pruritus was evaluated. Of the 101 patients included, 31(30.7%) had pruritus at the time of examination. Patients with pruritus were significantly older than those without pruritus (P=0.0027). Pruritus tended to be more prevalent in patients undergoing dialysis 3 times a week than in those undergoing daily dialysis, but the difference did not reach statistical significance (P=0.0854). Lower transferrin saturation levels were found in patients with pruritus than in those without pruritus (P=0.0144). C-reactive protein levels were significantly higher in patients with pruritus than in those without pruritus (P=0.0013). There was no significant difference between the groups in the levels of the other inflammatory biomarkers measured. However, there was a tendency toward a correlation between the levels of alpha-1-glycoprotein and the intensity of pruritus (P=0.0834). Our results suggest a possible relationship of the inflammatory response upregulation to pruritus. Additionally, there was a positive relationship between pruritus and iron deficiency, possibly associated with inflammatory elevation of hepcidin. A better understanding of the factors implicated in the genesis of pruritus related to end-stage renal disease is crucial in the development of more effective treatments for this symptom.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".