Nutrient Intake in the First Two Weeks of Life and Brain Growth in Preterm Neonates
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Optimizing early nutritional intake in preterm neonates may promote brain health and neurodevelopment through enhanced brain maturation. Our objectives were (1) to determine the association of energy and macronutrient intake in the first 2 weeks of life with regional and total brain growth and white matter (WM) maturation, assessed by 3 serial MRI scans in preterm neonates; (2) to examine how critical illness modifies this association; and (3) to investigate the relationship with neurodevelopmental outcomes. METHODS: Forty-nine preterm neonates (21 boys, median [interquartile range] gestational age: 27.6 [2.3] weeks) were scanned serially at the following median postmenstrual weeks: 29.4, 31.7, and 41. The total brain, basal nuclei, and cerebellum were semiautomatically segmented. Fractional anisotropy was extracted from diffusion tensor imaging data. Nutritional intake from day of life 1 to 14 was monitored and clinical factors were collected. RESULTS: Greater energy and lipid intake predicted increased total brain and basal nuclei volumes over the course of neonatal care to term-equivalent age. Similarly, energy and lipid intake were significantly associated with fractional anisotropy values in selected WM tracts. The association of ventilation duration with smaller brain volumes was attenuated by higher energy intake. Brain growth predicted psychomotor outcome at 18 months' corrected age. CONCLUSIONS: In preterm neonates, greater energy and enteral feeding during the first 2 weeks of life predicted more robust brain growth and accelerated WM maturation. The long-lasting effect of early nutrition on neurodevelopment may be mediated by enhanced brain growth. Optimizing nutrition in preterm neonates may represent a potential avenue to mitigate the adverse brain health consequences of critical illness.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it