Language and cognitive outcomes after pediatric ischemic stroke: The role of linguistic diversity and age at stroke onset
Bibliographic record
Abstract
Abstract Pediatric stroke disrupts ongoing neurodevelopment and often results in long-term cognitive challenges. For bilingual children navigating healthcare systems that underserve linguistically diverse families, these impacts raise critical health equity considerations. While bilingualism has historically been framed as a burden, research suggests it may support development in clinical populations. This cross-sectional study investigated how linguistic diversity relates to language and cognitive outcomes following arterial ischemic stroke, examining moderation by age at stroke onset. Twenty-nine children completed language and executive function assessments; caregivers reported language exposure and socioeconomic information. Analyses showed no main effect of linguistic diversity, but significant interactions with age at stroke. In the neonatal group, greater linguistic diversity was associated with better expressive language, whereas the presumed perinatal group showed the inverse pattern; childhood-onset stroke showed minimal associations. Findings suggest that bilingual environments do not impede, and may support, language following stroke, underscoring the importance of culturally/linguistically responsive care.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".