Do aggressive feeding guidelines eliminate first week nutrition deficits in very low birth weight infants fed exclusively mother’s own milk? (247.2)
Bibliographic record
Abstract
Background: Hospitalized VLBW infants fed human milk are reported to have lower growth rates compared to those fed nutrient‐enriched formulas. Aggressive parenteral nutrition guidelines for VLBW infants have been adopted in many neonatal intensive care units (NICUs) in response to data confirming short‐term safety of this approach and potential long‐term neurocognitive benefits. However, actual intakes during the first week of life have not been extensively evaluated since adoption of these guidelines. Objective: To describe the parenteral and enteral energy and macronutrient intakes in human milk‐fed VLBW infants from NICUs with aggressive nutrition guidelines. Design: Daily parenteral and enteral intakes were prospectively collected for 96 VLBW infants fed only MOM enterally during the first week . Feeding goals included provision of protein ( > 2.0) and lipids (1.0 g/kg/day) on the day of birth, advancing to 3.5 (protein) and 3.0 (lipid) g/kg/day within the first few days. Results: We found that 34% and 70% of infants did not meet protein and energy goals (of 3.5 g/kg/day and 90‐100 kcal/kg/day), respectively, at the end of the first week. Conclusions: Despite the adoption of more aggressive nutrition guidelines, most MOM‐fed VLBW infants remain undernourished at the end of the first week of life. Strategies to address these deficits may significantly impact the health outcomes of this vulnerable population. Grant Funding Source : Supported by CIHR (MOP#210093).
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".