Swallowing, Oral Motor, Motor Speech, and Language Impairments Following Acute Pediatric Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Following adult stroke, dysphagia, dysarthria, and aphasia are common sequelae. Little is known about these impairments in pediatric stroke. We assessed frequencies, co-occurrence and associations of dysphagia, oral motor, motor speech, language impairment, and caregiver burden in pediatric stroke. METHODS: Consecutive acute patients from term birth-18 years, hospitalized for arterial ischemic stroke (AIS), and cerebral sinovenous thrombosis, from January 2013 to November 2018 were included. Two raters reviewed patient charts to detect documentation of in-hospital dysphagia, oral motor dysfunction, motor speech and language impairment, and caregiver burden, using a priori operational definitions for notation and assessment findings. Other variables abstracted included demographics, preexisting conditions, stroke characteristics, and discharge disposition. Impairment frequencies were obtained by univariate and bivariate analysis and associations by simple logistic regression. RESULTS: A total of 173 patients were stratified into neonates (N=67, mean age 2.9 days, 54 AIS, 15 cerebral sinovenous thrombosis) and children (N=106, mean age 6.5 years, 73 AIS, 35 cerebral sinovenous thrombosis). Derived frequencies of impairments included dysphagia (39% neonates, 41% children); oral motor (6% neonates, 41% children); motor speech (37% children); and language (31% children). Common overlapping impairments included oral motor and motor speech (24%) and dysphagia and motor speech (23%) in children. Associations were found only in children between stroke type (AIS over cerebral sinovenous thrombosis) and AIS severity (more severe deficit at presentation) for all impairments except feeding impairment alone. Caregiver burden was present in 58% patients. CONCLUSIONS: For the first time, we systematically report the frequencies and associations of dysphagia, oral motor, motor speech, and language impairment during acute presentation of pediatric stroke, ranging from 30% to 40% for each impairment. Further research is needed to determine long-term effects of these impairments and to design standardized age-specific assessment protocols for early recognition following stroke.
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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 | 0.005 |
| 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 | 0.001 |
| 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".