Testing the feasibility and safety of feeding preterm infants fresh mother’s own milk in the NICU: A pilot study
Bibliographic record
Abstract
Necrotizing enterocolitis (NEC) is the leading cause of death among infants born at <30 weeks' gestation, but donor human milk can reduce the incidence of NEC. Unfortunately, freezing or pasteurizing human milk deactivates beneficial bioactive components. We evaluated the feasibility, safety, and impact of feeding very preterm infants fresh (unprocessed) mother's own milk within 4 hours of expression. In our multicentre prospective cohort analytic study, we fed 109 control and 98 intervention infants previously frozen donor or mother's own milk; only the intervention group was fed fresh mother's own milk once daily from enrollment until 32 weeks' corrected age. Control group mothers could not commit to provide fresh milk daily and were less likely receive antenatal corticosteroids than mothers in the intervention group. In the intervention group, 87.5% (98/112) of mothers were able to provide at least one feed of fresh milk a day. No critical incidents or non-compliance with the protocol were reported. The duration of mechanical ventilation and total parenteral nutrition use were shorter in the intervention group than controls (P < 0.01) but the length of hospital stay was similar (P = 0.57). Although the study might be underpowered, the intervention group had lower unadjusted rates of the composite outcome NEC ≥ stage 2 or mortality (8% vs 20%, P = 0.04), sepsis (22% vs 38%, P = 0.02), retinopathy of prematurity (17% vs 39%, P < 0.01) and bronchopulmonary dysplasia (32% vs 47%, P < 0.01) than the control. These results indicated that feeding fresh mother's own milk once daily was safe, feasible, and may reduce morbidity.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".