International comparison of peritoneal dialysis prescriptions from the Peritoneal Dialysis Outcomes and Practice Patterns Study (PDOPPS)
Bibliographic record
Abstract
Background:We describe peritoneal dialysis (PD) prescription variations among Peritoneal Dialysis Outcomes and Practice Patterns Study (PDOPPS) participants on continuous ambulatory PD (CAPD) and automated PD (APD; n = 4657) from Australia/New Zealand (A/NZ), Canada, Japan, Thailand, United Kingdom (UK), and United States (US).Results:CAPD was more commonly used in Thailand and Japan, while APD predominated over CAPD in A/NZ, Canada, the US, and the UK. Total prescribed PD volume normalized to the surface area was the highest in Thailand and the lowest in Japan (for both APD and CAPD) and the UK (for CAPD). PD patients from Thailand had the lowest residual urine volume and residual renal urea clearance, yet achieved the highest dialysis urea clearance. Japanese patients had the lowest dialysis urea clearances for both APD and CAPD. Despite having similar urine volumes to patients in A/NZ, Canada, Japan, and the UK, US CAPD and APD patients used 2.5% and 3.86% glucose PD solutions more frequently, whereas fewer than 25% of these patients used icodextrin. Over half of the patients in A/NZ, Canada, the UK, and Japan used icodextrin, whereas it was hardly used in Thailand. Japan and Thailand were more likely to use 1.5% glucose solutions for their PD prescription.Conclusions:There are considerable international variations in PD modality use and prescription patterns that translate into important differences in achieved dialysis clearances. Ongoing recruitment of additional PDOPPS participants and accrual of follow-up time will allow us to test the associations between specific PD prescription regimens and clinical and patient-reported outcomes.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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".