Growth and Body Composition of Human Milk–fed Premature Infants Provided With Extra Energy and Nutrients Early After Hospital Discharge: 1‐year Follow‐up
Bibliographic record
Abstract
OBJECTIVES: Human milk (HM) is the optimal source of nutrition for premature infants; however, it is unclear whether HM alone is sufficient to meet their elevated nutritional requirements early after hospital discharge. We previously reported that premature infants (750-1800 g birth weight) fed HM containing extra nutrients for 12 weeks after discharge had dietary intakes closer to recommended levels and grew more rapidly than those fed HM alone. The objectives of the present article are to examine the impact of this intervention on bone mineralization, body composition, and HM use up to 1 year. Data are also presented on general developmental level at 18-month corrected age (CA). PATIENTS AND METHODS: At discharge, predominantly HM-fed infants were randomized to receive for 12 weeks either approximately half of their feedings containing a multinutrient fortifier (intervention, n=19) or all of their feedings as HM alone (control, n=20). RESULTS: Intervention infants remained longer (P<0.001) and had greater whole-body bone mineral content (P=0.02) until 12-month CA compared with controls. Intervention infants born less than or equal to 1250 g continued to have a larger mean head circumference throughout the first year of life (P<0.0001). Human milk feeding (mL.kg(-1).day(-1)) differed between groups at 6- (P=0.035), but not 12-month CA. No statistically significant differences were found between groups in the mental, motor, or behavior rating scale scores of the Bayley II at 18-month CA. CONCLUSIONS: Adding a multinutrient fortifier to HM provided to predominantly HM-fed premature infants early after discharge results in sustained differences in weight, length, and whole-body bone mineral content, and in smaller babies, head circumference for the first year of life.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".