Bibliographic record
Abstract
There are almost 30,000 patients maintained on peritoneal dialysis (PD) in Asia, representing about 8% of all Asian dialysis patients. The largest numbers of PD patients are in Japan and China, but the highest PD penetration is in Hong Kong, Korea, and Singapore. Notable features of PD in Asia include the varying rates of use across the different countries. The reasons for this are reviewed here, with particular emphasis on the significance of whether dialysis providers are predominantly private or public. The excellent rates of both patient and technique survival in the richer Asian countries are also examined and interpreted in the context of recent data showing that Asian patients living in North America have generally superior survival on dialysis and better compliance with PD than their Caucasian counterparts. It is concluded that the healthier baseline health status in South East Asian patients, in particular, contributes to their impressive outcomes. The approach to both clearance and ultrafiltration is less aggressive in Asian countries than in the West. Studies looking at the relationship between clearance and clinical outcome in Asia are reviewed and it is concluded that the benefits of higher clearances have been harder to show than in North America because of the relatively better outcomes of the patients. The concern about sclerosing encapsulating peritonitis in Japan particularly is emphasized. The Hong Kong model of dialysis delivery with its high use of PD and the arguments for and against it are also reviewed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".