Impact of iron dextran shortage on patients with intestinal failure receiving home parenteral nutrition: Experience from a multidisciplinary rehabilitation program
Bibliographic record
Abstract
Background: Iron deficiency is prevalent in children with intestinal failure (IF), and enteral iron is not effective in this population. Iron deficiency (ID)in growing children is associated with neurocognitive deficits in adulthood despite correction of deficiency at diagnosis. While many intestinal rehabilitation programs (IRP) exclude iron from PN prescriptions, our center historically added iron dextran (iDex) daily until its unavailability in 2023. This study aimed to evaluate the impact of iDex shortage on children with IF on home PN (HPN), followed by the IRP. Material and methods: A retrospective chart review of HPN patients assessed the number of patients requiring intravenous iron post-discontinuation of iDex, biochemical markers of iron status, and responses to enteral iron supplementation. Data were compared pre (baseline) and post iron discontinuation using a related-sample T-test and analysis of variance. Results: Fifty-six HPN patients aged 8 ± 1.4 y (mean ± SD) were reviewed. Before iDex discontinuation, 3 % required IV iron infusions. Since discontinuation, 3 % tolerated enteral supplementation, with no biochemical improvement in iron status, and 27 % required IV iron infusion within 12 months due to development of iron deficiency. Conclusion: The addition of iron to PN seems to be advantageous for iron deficiency prevention in children with IF. Given the association of iron deficiency with neurocognitive deficits, management of iron status should focus on prevention of iron deficiency. Therefore, for patients with IF on long-term PN, iron can be beneficial as part of the PN prescription for adequate provision of a balance nutrient profile.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".