Language and Cognitive Outcomes Following Ischemic Stroke in Children With Monolingual and Bilingual Exposure
Bibliographic record
Abstract
Aim: Although many children who experience ischemic stroke come from bilingual backgrounds, it is unclear whether bilingual exposure affects poststroke development. Our research evaluates bilingual and monolingual exposure on linguistic/cognitive development poststroke across 3 stroke-onset groups. Method: An institutional stroke registry and medical charts were used to gather data on 237 children across 3 stroke-onset groups: neonatal, <28 days; first-year, 28 days to 12 months; and childhood, 13 months to 18 years. The Pediatric Stroke Outcome Measure (PSOM), administered several times poststroke, was used to evaluate cognition and linguistic development. Results: Similar cognitive outcomes were observed across language groups. However, an interaction effect with stroke-onset group was observed, with monolinguals in the first-year group having worse productive language outcomes as compared to bilinguals. Interpretation: Overall, no detrimental effects of bilingualism were found on children's poststroke cognition and linguistic development. Our study suggests that a bilingual environment may facilitate language development in children poststroke.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".