Similarities and differences in cerebellar alterations between youth born preterm and youth born with congenital heart disease
Bibliographic record
Abstract
Individuals born preterm (PT) or with complex congenital heart disease (CHD) present with comparable prevalence of developmental challenges and patterns of neonatal brain injury. Converging evidence also supports that cerebellar development is altered in PT and in CHD survivors. However, no study compared cerebellar integrity between these two groups. This study aims to assess total and regional cerebellar development between youth born PT or with CHD as compared to controls. Participants aged 16-27 years born before 33 weeks of gestational age or who underwent open-heart surgery for CHD during infancy and a group of healthy term-born controls, underwent a brain MRI. Cerebellums were segmented at the lobular level. Youth born PT or with CHD exhibited a comparable pattern of volume reduction affecting total, regional and lobular cerebellar volumes. After adjusting for total brain volume, no significant differences remained between CHD and controls. Only regions and lobules in the anterior cerebellum remained significantly smaller than controls in the youth born PT. Atypical cerebellar development is present in youth born PT and in youth with CHD. However, our results suggested that premature exposure to the extra-uterine environment alters cerebellar development selectively while the cumulative effect of CHD globally hinders brain development.
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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 | 0.002 |
| 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 | 0.000 |
| 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".