Neurodevelopmental outcomes at 18 months of children diagnosed with CHD compared to children born very preterm
Bibliographic record
Abstract
OBJECTIVE: To compare neurodevelopmental outcomes and parent behaviour ratings of children born term with CHD to children born very preterm. METHODS: A clinical research sample of 181 children (CHD [n = 81]; very preterm [≤32 weeks; n = 100]) was assessed at 18 months. RESULTS: Children with CHD and born very preterm did not differ on Bayley-III cognitive, language, or motor composite scores, or on expressive or receptive language, or on fine motor scaled scores. Children with CHD had lower ross motor scaled scores compared to children born very preterm (p = 0.047). More children with CHD had impaired scores (<70 SS) on language composite (17%), expressive language (16%), and gross motor (14%) indices compared to children born very preterm (6%; 7%; 3%; ps < 0.05). No group differences were found on behaviours rated by parents on the Child Behaviour Checklist (1.5-5 years) or the proportion of children with scores above the clinical cutoff. English as a first language was associated with higher cognitive (p = 0.004) and language composite scores (p < 0.001). Lower median household income and English as a second language were associated with higher total behaviour problems (ps < 0.05). CONCLUSIONS: Children with CHD were more likely to display language and motor impairment compared to children born very preterm at 18 months. Outcomes were associated with language spoken in the home and household income.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".