Anemia Management in the China Dialysis Outcomes and Practice Patterns Study
Bibliographic record
Abstract
BACKGROUND: As the utilization of hemodialysis increases in China, it is critical to examine anemia management. METHODS: Using data from the China Dialysis Outcomes and Practice Patterns Study (DOPPS), we describe hemoglobin (Hgb) distribution and anemia-related therapies. RESULTS: Twenty one percent of China's DOPPS patients had Hgb <9 g/dl, compared with ≤10% in Japan and North America. A majority of medical directors targeted Hgb ≥11. Patients who were female, younger, or recently hospitalized had higher odds of Hgb <9; those with insurance coverage or on twice weekly dialysis had lower odds of Hgb <9. Iron use and erythropoietin-stimulating agents (ESAs) dose were modestly higher for patients with Hgb <9 compared with Hgb in the range 10-12. CONCLUSION: A large proportion of hemodialysis patients in China's DOPPS do not meet the expressed Hgb targets. Less frequent hemodialysis, patient financial contribution, and lack of a substantial increase in ESA dose at lower Hgb concentrations may partially explain this gap. Video Journal Club 'Cappuccino with Claudio Ronco' at http://www.karger.com/?doi=442741.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".