The Safety of Intravenous Ferric Gluconate Self Administered During Routine Home Hemodialysis
Bibliographic record
Abstract
Home hemodialysis (HHD) patients are often inconvenienced when intravenous iron preparations are administered. Formerly, these patients received their medication in the clinic on an off‐dialysis day or during in‐center hemodialysis (HD). For the last 2 years, 5 patients in our HHD program have been receiving intravenous ferric gluconate during their routine HD session. Procedure: All patients were trained in the proper administration of ferric gluconate in‐center. No test dose was administered. Ferric gluconate was infused via the heparin infusion pump on their HD machine at a rate of 31.25 mg/h. Doses were of either 62.5 mg or 125 mg per session. K/DOQI guidelines for intravenous iron use were adhered to. TSATs greater than 25%, ferritin greater than 100 ng/mL and less than 800 ng/mL, and hemoglobin between 11 and 12 g% were the goals of therapy. Both loading doses (8 doses during sequential HD sessions) and maintenance doses every week or every other week were employed. Results: Over the last 2 years, 223 doses were administered at home. No serious reactions occurred during the course of therapy. One patient experienced minor nausea and vomiting during one dose, which was thought to be possibly related to the iron infusion. This patient subsequently received ferric gluconate again without difficulty. Conclusion: Ferric gluconate can be safely administered at home during HHD.
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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 | 0.007 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".