Low hemoglobin at hemodialysis initiation: an international study of anemia management and mortality in the early dialysis period
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Anemia at hemodialysis (HD) initiation is common. Correcting low hemoglobin (Hgb) before HD initiation may improve survival by avoiding potential harms of chronic anemia, high doses of erythropoiesis-stimulating agents (ESAs) and intravenous (IV) iron in the early HD period, and/or rapid Hgb rise. METHODS: We included 4604 incident HD patients from 21 countries in the Dialysis Outcomes and Practice Patterns Study Phases 4-5 (2009-15). Because low Hgb at HD start may reflect comorbidity or ESA hyporesponse, we restricted our analysis to the 80% of patients who achieved Hgb ≥10 g/dL 91-120 days after HD start (Month 4). RESULTS: About 53% of these patients had Hgb <10 g/dL in Month 1 (<30 days after HD start); they were younger with a similar comorbidity profile (versus Hgb ≥10 g/dL). Month 1 Hgb was associated with first-year HD mortality (adjusted hazard ratio for 1 g/dL higher Hgb was 0.89; 95% confidence interval: 0.81-0.97), despite minimal differences in Month 4 Hgb. Patients with lower Hgb in Month 1 received higher doses of ESA, but not IV iron, over the first 3 months of HD. Results were consistent when excluding catheter users or adjusting for IV iron and ESA dose over the first 3 months. CONCLUSIONS: Even among patients with Hgb ≥10 g/dL 3 months later, anemia at HD initiation was common and associated with elevated mortality. A more proactive approach to anemia management in advanced chronic kidney disease (CKD) may thus improve survival on HD, though long-term prospective studies of non-dialysis CKD patients are needed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it