Prevalence and Implications of Low Reticulocyte–Hemoglobin Levels among Extreme Preterm Neonates: A Single-Center Retrospective Study
Bibliographic record
Abstract
This retrospective cohort study aims to determine the epidemiology of iron deficiency among extreme preterm neonates and the association of iron-deficient status during the NICU stay with neurodevelopmental outcomes at 18−24 months. Neonates ≤29 weeks gestational age (GA) born between June 2016 and December 2019, who received routine iron supplementation were enrolled. Iron deficiency was defined as reticulocyte−hemoglobin (Ret-Hb) levels ≤ 29 pg at 36 weeks corrected age. A subcohort of neonates completed standardized developmental assessment at 18−24 months corrected age. Significant neurodevelopmental impairment (sNDI) was defined as either Bayley Scales of Infant Development score < 70 or cerebral palsy or blindness or hearing aided. Among a cohort of 215 neonates [GA 25.8 (1.7) weeks, birthweight 885 (232) g], prevalence of iron deficiency was 55%, 21%, 26%, and 13%, in neonates <24 weeks, 24−25 + 6 weeks, 26−27 + 6 weeks, and ≥ 28 weeks GA, respectively. Male sex and receipt of corticosteroid therapy were associated with iron-deficiency. In the subcohort analysis (n = 69), there was no statistically significant association between Ret-Hb levels at 36 weeks corrected age and the risk of sNDI [OR 0.99 (95% CI 0.85−1.2)]. Male infants and those who received postnatal corticosteroids are likely to have iron-limited erythropoiesis at corrected term despite routine iron-supplementation; however, low Ret-Hb levels during the neonatal period were not associated with significant neurological disability in early childhood.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".