Does Amount of Protein in Formula Matter for Low‐Birthweight Infants? A Cochrane Systematic Review
Bibliographic record
Abstract
BACKGROUND: High protein intake may be associated with negative consequences such as acidosis, uremia, and elevated levels of circulating amino acids (eg, phenylalanine levels). We performed a systematic review of randomized controlled trials to determine whether formula-fed low-birthweight infants could tolerate protein intakes>or=3.0 g/kg/d in their initial hospital stay, without adverse consequences. METHODS: Randomized controlled trials contrasting levels of protein intakes as low (<3.0 g/kg/d), high (>or=3.0 g/kg/d but <4.0 g/kg/d), or very high protein intake (>or=4.0 g/kg/d) while other nutrients were held constant, were identified through a systematic search of the literature. Standard methods of the Cochrane Collaboration were used by 2 independent reviewers, with the third reviewer facilitating consensus decision making. RESULTS: A meta-analysis of 5 randomized trials indicated improved weight gain (weighted mean difference [WMD] 2.36 g/kg/d; 95% confidence interval [CI] 1.31-3.40) and higher nitrogen accretion (WMD 143.7 mg/kg/d; 95% CI 128.7-158.8) with high (>or=3.0 g/kg/d but <4.0 g/kg/d) compared with low (<3.0 g/kg/d) protein intakes while other nutrients were kept constant. No data were available for IQ or Bayley scores at 18 months or later or for very high protein intakes (>or=4.0 g/kg/d). No significant differences were seen in rates of necrotizing enterocolitis, sepsis, or diarrhea. CONCLUSIONS: Accelerated weight and nitrogen accretion were noted with higher protein intakes in "healthy" formula-fed low-birthweight infants. This benefit could not be weighed against the adverse consequences of elevated blood urea nitrogen levels and increased metabolic acidosis and neurodevelopmental abnormalities.
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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 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.014 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".