Non Breast-Milk-Fed Very Preterm Infants Are at Increased Risk of Iron Deficiency at 4–6-Months Corrected Age: A Retrospective Population-Based Cohort Study
Bibliographic record
Abstract
Iron supplementation is routinely recommended for breast-milk-fed preterm infants. However, the Canadian Pediatric Society recommends no additional iron supplementation for preterm infants fed primarily with iron-rich formula. Other pediatric societies don't provide specific guidance on supplemental iron for formula-fed preterm infants. This study investigated how feeding type influences iron status of very preterm infants at 4-6-months corrected age (CA). A retrospective cohort study was conducted using a population-based database on all very preterm infants (<31 weeks gestational age) born in Nova Scotia, Canada from 2005-2018. Information about feeding type, iron intake from formula, supplemental iron therapy and iron status at 4-6-months CA was extracted. Iron deficiency (ID) was defined as serum ferritin <20 and <12 µg/L at 4-and 6-months CA, respectively. Of 392 infants, 107 were "breast-milk-fed" (exclusively or partially) and 285 were "not breast-milk-fed" (exclusively fed with iron-rich formula) at 4-6-months CA. Total daily iron intake was higher in the non-breast-milk-fed group (2.6 mg/kg/day versus 2.0 mg/kg/day). Despite this, 36.8% of non-breast-milk-fed infants developed ID versus 20.6% of breast-milk-fed infants. ID is significantly more prevalent in non-breast-milk-fed infants than breast-milk-fed infants despite higher iron intake. This suggests the need to revisit recommendations for iron supplementation in non-breast-milk-fed preterm infants.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".