Role of Oral Iron in the Management of Long-Term Hemodialysis Patients
Bibliographic record
Abstract
BACKGROUND: The literature contends that oral iron supplementation is relatively ineffective in patients who are on long-term hemodialysis (HD), and intravenous iron is the superior form of supplementation. DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS: Data were prospectively abstracted from a cross-sectional cohort of all patients in the long-term in-center HD program at St. Michael's Hospital (SMH) from April 1, 2003, to April 1, 2004. Laboratory data were measured monthly. SMH data were compared with those in eight other centers in the Toronto Region Dialysis Registry. RESULTS: A total of 93% of the 151 patients tolerated oral iron. Eighty-eight (58%) patients received oral iron exclusively, and 60 (40%) patients received intravenous iron with or without oral iron. Of the patients who received oral iron exclusively, 73% maintained a hemoglobin of > or =110 g/L and 93% maintained a hemoglobin of > or =100 g/L. A total of 74% had an iron saturation > or =20%, and 36% had a ferritin level >100 g/L. Among the patients who were on oral iron alone and had hemoglobin of > or =110 g/L, the same amount of erythropoietin was used regardless of ferritin levels (P = 0.17), but less erythropoietin was used when they reached the target for either iron saturation or both iron indices (P = 0.02 and 0.03, respectively). Among the centers in the Toronto Region Dialysis Registry, hemoglobin levels and erythropoietin dosages did not differ among the three centers that predominantly used oral iron versus the six centers that predominantly use intravenous iron (P = 0.46 and 0.95, respectively). CONCLUSIONS: Oral iron is a well-tolerated and effective form of iron supplementation in long-term HD patients.
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 | 0.005 |
| 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 | 0.001 | 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 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".