Resilience and Vulnerability: Neurodevelopment of Very Preterm Children at Four Years of Age
Bibliographic record
Abstract
Children born very preterm (VPT) are at high-risk for altered brain development and impaired neurodevelopmental outcomes but are not well-studied before school-age. We investigated 64 four-year-olds: 37 VPT children [<32 weeks gestational age [GA]; 22 males; mean GA: 28.8 weeks ± 1.6], 25 full-term (FT) children (12 males), plus two VPT cases with ventriculomegaly and exceptionally resilient outcomes. All children underwent high-resolution structural magnetic resonance imaging and developmental assessments. Measures of brain volume, cortical thickness, and surface area were obtained. Children born VPT demonstrated reduced cerebral and cerebellar white matter volumes yet increased cerebral gray matter, temporal lobe, occipital lobe and ventricle volumes after adjusting for total brain volume. Cortical thickness was greater in the VPT children compared to FT children across all lobes. On developmental assessments, the VPT children scored lower on average than FT children while the two cases had intact cognitive abilities. In addition to larger ventricle volumes, the two cases had white matter and gray matter volumes within the ranges of the FT children. The VPT children displayed distinct differences in structural brain volumes at 4 years of age, consistent with delayed maturation. The cases with persistent ventriculomegaly and good cognitive outcomes displayed typical gray matter and increased white matter volumes, indicating a potential protective developmental phenomenon contributing to their intact cognitive abilities.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".