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Some but not all breast‐fed infants benefit from iron supplementation

2010· article· en· W124953930 on OpenAlexafffundabout
James K. Friel

Bibliographic record

VenueThe FASEB Journal · 2010
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsUniversity of Manitoba
FundersCanadian Institutes of Health Research
KeywordsMedicineBayley Scales of Infant DevelopmentPediatricsIron supplementationPopulationAnthropometryBreast feedingPlaceboVenipunctureBreast milkPhysiologyInternal medicineIron deficiencyAnemiaSurgeryPsychomotor learningBiology

Abstract

fetched live from OpenAlex

Full‐term healthy breast‐fed infants in Newfoundland Canada have previously been shown to benefit from iron supplements early in infancy by increasing developmental motor scores (Friel et al., J. Pediatrics, 2003). To test this hypothesis in another Canadian province, 82 infants in Manitoba were randomized to receive 7.5 mg of supplemental iron as ferrous sulphate (I) or placebo (P) once a day from 1 to 6 months of age. All infants were breast‐fed at one month of age and were encouraged to continue exclusive breast‐feeding to 6 months before introducing solid foods. Blood samples were collected by venipuncture at 4 and 12 months of age. Anthropometric and demographic data was collected at 1, 4, 6 and 12 months of age when a Bayley Developmental assessment was conducted. Although P infants weighed more at birth (P: 3.63 ± 0.4 vs. I: 3.42 ± 0.5 kg P<0.05) this difference did not persist after one month of age. At 4 months ferritin (I: 110 ± 91 vs. P: 75 ± 48) was higher and transferrin receptors (I: 20 ± 4.4 vs. P: 22 ± 6) were lower in the iron‐supplemented group. At 4 months GPx was higher (I: 10.7 ± 3 vs. P: 9.3 ± 2) which did not persist to 12 months. Bayley MDI (P: 99 ± 9 vs. I: 97 ± 10) and PDI (P: 91 ± 14 vs. I: 92 ± 14) did not differ. These results suggest that full‐term healthy breast fed infants from an advantaged population will increase iron stores when given iron supplements with no adverse effects on growth but gain no advantage for developmental outcome at one year. Supported by CIHR and MICH.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.013
GPT teacher head0.269
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2010
Admission routes3
Has abstractyes

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