Universal versus Selective Iron Supplementation for Infants and the Risk of Unintentional Poisoning in Young Children: A Comparative Study of Two Populations
Bibliographic record
Abstract
BACKGROUND: Iron continues to be a common cause of poisoning in young children, in part due to its widespread use and easy accessibility. OBJECTIVE: To determine differences in the epidemiology and outcome of unintentional iron ingestion by young children in populations practicing selective (eg, US) versus universal (eg, Israel) iron supplementation to infants. METHODS: All cases of unintentional iron ingestion in children younger than 7 years in a one year period were identified through the poison control center databases of 2 sites (Illinois and Israel). Parameters compared include patient sex and age; type, form, and dose of iron preparation; circumstances and clinical manifestations; management; and outcome. RESULTS: A total of 602 children were identified: 459 in Illinois and 143 in Israel. The majority of Illinois children ingested multivitamin preparations (94%), whereas Israeli children ingested single-ingredient iron preparations (78%) (p < 0.001). Iron doses ingested were higher in Israel (median 14.5 vs 6.6 mg/kg; p < 0.001) but remained within the nontoxic range for most children. No deaths or severe poisonings were reported, and 93% of children in both groups were asymptomatic. The majority of ingestions in both locations were due to unintentional self-ingestion. However, parental miscalculation occurred more frequently in Israel (16%) than in Illinois (1%). CONCLUSIONS: Universal iron supplementation to infants was not associated with a negative impact on the outcome of pediatric unintentional ingestions. Low-dose exposures were safely managed by on-site observation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".