Neonatal Critical Illness, 8-Year White Matter Microstructure, and Motor Function in Children Born Very Preterm
Bibliographic record
Abstract
OBJECTIVE: To assess relationships between neonatal critical illness in children born preterm with white matter maturation and clinical motor and visual-motor integration (VMI) performance at 8 years. STUDY DESIGN: Prospective longitudinal study of 234 neonates (24-32 weeks gestational age [GA]) recruited from 2006 to 2013 at a tertiary neonatal intensive care unit. Neonatal critical illness included infection, bronchopulmonary dysplasia, retinopathy of prematurity, severe intraventricular hemorrhage, and significant white matter injury. At age 8 years, children completed visual-motor (Beery-Buktenica Developmental Test of Visual-Motor Integration, sixth edition) and motor (Movement Assessment Battery for Children, second edition) assessments. Tract-based spatial statistics were used to analyze fractional anisotropy from diffusion tensor imaging acquired at 8 years to measure white matter maturation. RESULTS: Of 226 survivors, 129 children (69 males [53%]) were assessed at 8 years and had high-quality diffusion tensor imaging. Neonatal critical illness counts ≥ 3 were associated with 11.8-point decrease in motor (CI -23-(-.55), P = .04) and 11.3-point decrease in VMI scores (CI -18.2-(-4.5), P = .001), accounting for GA and maternal education. Higher neonatal critical illness counts (P = .04) and lower motor (P < .001) and VMI (P = .04) scores were related to bilateral reductions in white matter fractional anisotropy in the corpus callosum and motor association pathways, accounting for GA, neonatal brain injury, maternal education, and age at scan. CONCLUSIONS: Cumulative critical illness in neonates born preterm is associated with long-term changes in white matter microstructure and maturation, which are related to motor and visual motor performance at school-age. These findings highlight the long-term importance of neonatal intensive care exposures and need for school-age follow-up of children born preterm.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".