International Anemia Prevalence and Management in Peritoneal Dialysis Patients
Bibliographic record
Abstract
Background The optimal treatment for managing anemia in peritoneal dialysis (PD) patients and best clinical practices are not completely understood. We sought to characterize international variations in anemia measures and management among PD patients. Methods The Peritoneal Dialysis Outcomes and Practice Patterns Study (PDOPPS) enrolled adult PD patients from 6 countries from 2014 to 2017. Hemoglobin (Hb), ferritin levels, and transferrin saturation (TSAT), as well as erythropoiesis stimulating agents (ESAs) and iron use were compared cross-sectionally at study enrollment in Australia and New Zealand (A/NZ), Canada, Japan, the United Kingdom (UK), and the United States (US). Results Among 3,603 PD patients from 193 facilities, mean Hb ranged from 11.0 – 11.3 g/dL across countries. The majority of patients (range 53% – 59%) had Hb 10 – 11.9 g/dL, with 4% – 12% patients ≥ 13 g/dL and 16% – 23% < 10 g/dL. Use of ESAs was higher in Japan (94% of patients) than elsewhere (66% – 79% of patients). In the US, 63% of patients had a ferritin level > 500 ng/mL, compared with 5% – 38% in other countries. In the US and Japan, 87% – 89% of PD patients had TSAT ≥ 20%, compared with 73% – 76% in other countries. Intravenous (IV) iron use within 4 months of enrollment was higher in the US (55% of patients) than elsewhere (6% – 17% patients). Conclusions In this largest international observational study of anemia and anemia management in patients receiving PD, comparable Hb levels across countries were observed but with notable differences in ESA and iron use. Peritoneal dialysis patients in the US have higher ferritin levels and higher IV iron use than other countries.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".