Abnormal brain maturation in preterm neonates associated with adverse developmental outcomes
Bibliographic record
Abstract
OBJECTIVE: Our objective was to determine the association of early brain maturation with neurodevelopmental outcome in premature neonates. METHODS: Neonates born between 24 and 32 weeks' gestation (April 2006 to August 2010) were prospectively studied with MRI early in life and again at term-equivalent age. Using diffusion tensor imaging and magnetic resonance spectroscopic imaging, fractional anisotropy (FA) (microstructure) and N-acetylaspartate (NAA)/choline (metabolism) were measured from the basal nuclei, white matter tracts, and superior white matter. Brain maturation is characterized by increasing FA and NAA/choline from early in life to term-equivalent age. In premature neonates, systemic illness and critical care therapies have been linked to abnormalities of these measures. Of the 177 neonates in this cohort, 5 died and 157 (91% of survivors) were assessed at 18 months' corrected age (adjusted for prematurity) using the Bayley Scales of Infant and Toddler Development III motor, cognitive, and language composite scores (mean = 100, SD = 15). RESULTS: Among these 157 infants, white matter injury was seen in 48 (30%). Severe white matter injury, in 10 neonates (6%), was associated with a decrease in motor (-18 points; p < 0.001) and cognitive (-8 points; p = 0.085) scores. With greater severity of adverse neurodevelopmental outcomes, slower increases in FA and NAA/choline were observed in the basal nuclei and brain white matter regions as neonates matured to term-equivalent age, independent of the presence of white matter injury. CONCLUSIONS: In the preterm neonate, abnormal brain maturation evolves through the period of neonatal intensive care and is associated with adverse neurodevelopmental outcomes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".