SP575PREVALENCE AND AWARENESS AND TREATMENT OF URAEMIC PRURITUS IN PEOPLE ON AEMODIALYSIS: INTERNATIONAL COMPARISONS FROM THE DOPPS
Bibliographic record
Abstract
Introduction and Aims: Uraemic pruritus (UP) in haemodialysis (HD) patients is common and associated with reduced quality of life and increased mortality. As a benchmark for improvement, we describe the prevalence, awareness and treatment of UP for HD patients in 17 countries in the DOPPS. Methods: Data were taken from DOPPS phase 1-5 (1996-2015). Data in phase 5 (2012-2015) were from 5713 patient questionnaires and 268 medical director surveys from HD facilities in Belgium, Canada, the 6 Gulf Cooperation Council countries, Germany, Italy, Japan, Russia, Spain, Sweden, Turkey, UK and USA. Results: Overall, HD patients moderately to extremely bothered by itchy skin declined from 44% in 1996-2001 to 37% in 2012-15. 9 countries with continuous data from 2002 showed the same trend. In 2012-15 this varied from 25% in Germany to 52% in the UK (figure). Nephrologists appear to significantly underestimate the prevalence of UP. On average, 20.5% of patients in each country who were at least moderately bothered by itchy skin did not report their symptoms to a healthcare professional. Severe UP was undertreated; 20.3% of patients who were very much or extremely bothered by itchy skin used no treatment for it. For patients with severe UP, phosphorus control in patients with high serum phosphorus was ranked as the most important therapeutic option by nephrologists. The most commonly used medications were oral and topical antihistamines. UVB phototherapy was rarely used. Overall, a majority of nephrologists never used gabapentin or pregabalin. However, in Germany, which has the lowest prevalence of severe UP, all dialysis facility medical directors reported using gabapentin as chronic therapy.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".