Early childhood language outcomes after arterial switch operation: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Developmental and language outcomes at 2 years of age of children who had arterial switch operation (ASO) for transposition of the great arteries 2004-2010 are described. METHODS: In this prospective cohort study, 91/98 (93 %) children who underwent ASO were assessed at 2 years of age with the Bayley Scales of Infant & Toddler Development-3rd Edition. Outcomes were compared by patient and perioperative variables using bivariate and multivariate regression analyses to identify predictors of language delay. RESULTS: Infants without ventricular septal defect (VSD) (n = 60) were more likely to be outborn (73 vs 58 %, p = 0.038), require septostomy (80 vs 58 %, p = 0.026), have a shorter cross clamp time (min) (62.7 vs 73.0, p = 0.019), and a lower day 1 post-operative plasma lactate (mmol/L) (3.9 vs 4.8, p = 0.010). There were no differences in cognitive, motor and language outcomes based on presence of a VSD. Language delay (<85) of 29 % was 1.8 times higher than the normative sample; risk factors for this in multivariate analyses included <12 years of maternal education (AOR 19.3, 95 % CI 2.5-148.0) and cross-clamp time ≥70 min (AOR 14.5, 95 % CI 3.1-68.5). Maternal education <12 years was associated with lower Language Composite Scores (-20.2, 95 % CI -32.3 to -9.1). CONCLUSIONS: Outcomes at 2 years of age in children who undergo ASO are comparable to the normative sample with the exception of language. There is a risk of language delay for which maternal education and cross-clamp duration are predictors. These findings suggest that focused post-operative early language interventions could be considered.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".