Anemia and iron deficiency among chronic kidney disease Stages 3–5ND patients in the Chronic Kidney Disease Outcomes and Practice Patterns Study: often unmeasured, variably treated
Bibliographic record
Abstract
BACKGROUND: International variation in anemia assessment and management practices in chronic kidney disease (CKD) is poorly understood. METHODS: We performed a cross-sectional analysis of anemia laboratory monitoring, prevalence and management in the prospective Chronic Kidney Disease Outcomes and Practice Patterns Study (CKDopps). A total of 6766 participants with CKD Stages 3a-5ND from nephrology clinics in Brazil, France, Germany and the USA were included. RESULTS: Among patients with anemia (hemoglobin <12 g/dL), 36-58% in Brazil, the USA and Germany had repeat hemoglobin measured and 40-61% had iron indices measured within 3 months of the index hemoglobin measurement. Anemia was more common in the USA and Brazil than in France and Germany across CKD stages. Higher ferritin and lower iron saturation (TSAT) levels were observed with lower hemoglobin levels, and higher ferritin with more advanced CKD. The proportion of anemic patients with ferritin <100 ng/mL or TSAT <20% ranged from 42% in Brazil to 53% in France and Germany, and of these patients, over 40% in Brazil, Germany and the USA, compared with 27% in France, were treated with oral or intravenous iron within 3 months after hemoglobin measurement. The proportion of patients with hemoglobin <10 g/dL treated with erythropoiesis-stimulating agents ranged from 28% in the USA to 57% in Germany. CONCLUSIONS: Hemoglobin and iron stores are measured less frequently than per guidelines. Among all regions, there was a substantial proportion of anemic patients with iron deficiency who were not treated with iron, highlighting an area for practice improvement in CKD care.
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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 | 0.002 | 0.004 |
| 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 | 0.000 | 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".