Intravenous iron administration strategies and anemia management in hemodialysis patients
Bibliographic record
Abstract
Background: The effect of maintenance intravenous (IV) iron administration on subsequent achievement of anemia management goals and mortality among patients recently initiating hemodialysis is unclear. Methods: We performed an observational cohort study, in adult incident dialysis patients starting on hemodialysis. We defined IV administration strategies over a 12-week period following a patient's initiation of hemodialysis; all those receiving IV iron at regular intervals were considered maintenance, and all others were considered non-maintenance. We used multivariable models adjusting for demographics, clinical and treatment parameters, iron dose, measures of iron stores and pro-infectious and pro-inflammatory parameters to compare these strategies. The outcomes under study were patients' (i) achievement of hemoglobin (Hb) of 10-12 g/dL, (ii) more than 25% reduction in mean weekly erythropoietin stimulating agent (ESA) dose and (iii) mortality, ascertained over a period of 4 weeks following the iron administration period. Results: Maintenance IV iron was administered to 4511 patients and non-maintenance iron to 8458 patients. Maintenance IV iron administration was not associated with a higher likelihood of achieving an Hb between 10 and 12 g/dL {adjusted odds ratio (OR) 1.01 [95% confidence interval (CI) 0.93-1.09]} compared with non-maintenance, but was associated with a higher odds of achieving a reduced ESA dose of 25% or more [OR 1.33 (95% CI 1.18-1.49)] and lower mortality [hazard ratio (HR) 0.73 (95% CI 0.62-0.86)]. Conclusions: Maintenance IV iron strategies were associated with reduced ESA utilization and improved early survival but not with the achievement of Hb targets.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".