MaxiMoM InForM: individualised fortification of human milk for very low birthweight infants— protocol of a three-arm randomised clinical trial
Bibliographic record
Abstract
INTRODUCTION: To meet the elevated nutritional requirements of very low birthweight (<1500 g, VLBW) infants during hospitalisation, many neonatal units routinely add a fixed dose of multinutrient fortifier to human milk. Individualised approaches that either tailor macronutrient additions to routine analysis of milk composition (target fortification) or an infant's metabolic response to nutrition (blood urea nitrogen (BUN) adjustable fortification) show short-term improvement in growth, but important outcomes such as longer-term neurodevelopment and major in-hospital morbidity have not been systematically assessed. The aim of our study is to determine whether target or BUN adjustable fortification of human milk, compared with standard fortification, during hospitalisation improves cognitive (primary), language and motor development of VLBW infants at 18-24 months corrected age (CA). Secondary outcomes include growth, body composition, mortality and serious morbidity. METHODS AND ANALYSIS: This is a three-arm, pragmatic, multicentre, double-blind, randomised clinical trial of 615 human milk-fed infants born either (1) ≤1250 g or (2) <30 weeks and <1500 g. Once enteral feeds reach 100 mL/kg/day, and until 36 weeks corrected gestational age (CGA), infants are fed according to one of three fortification protocols: (1) standard fortification, in which a fixed dose of nutrients is added to human milk; (2) target fortification, in which values from twice weekly direct analysis of mother's milk and each batch of donor milk are used to provide 4 and 4.8 g/kg/day true protein and fat, respectively; and (3) BUN adjustable fortification, in which weekly BUN values are used to adjust protein fortification of milk. Neurodevelopment is assessed using the Bayley-IV scale at 18-24 months CA. Growth, morbidities and nutrient intakes are recorded daily during hospitalisation, and skinfolds are measured at 36 weeks CGA and at 4 months CA. At 4 months CA, body composition is determined by air displacement plethysmography on a subset of infants. ETHICS AND DISSEMINATION: Ethical approval was obtained from Clinical Trials Ontario (CTO) and local research ethics boards that are not CTO members. Study findings will be disseminated to clinicians at seminars and conferences and in peer-reviewed publications. TRIAL REGISTRATION NUMBER: NCT05308134.
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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 | 0.024 | 0.025 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.042 | 0.008 |
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".