Arterial Ischemic Strokes in Infants and Children: An Overview of Current Approaches
Bibliographic record
Abstract
Stroke in children is increasingly recognized. The incidence exceeds 8 per 100,000 per year. Important differences in stroke in newborns and children compared with adults, as well as a paucity of clinical trials, create challenges in the diagnosis and management of pediatric arterial ischemic stroke (AIS). The neurological presentation of AIS can be subtle. Radiographic diagnosis of acute AIS is also challenging because CT scan may be normal early on. Risk factors include vascular, intravascular, and embolic disorders; frequently, there are multiple risk factors in a given child, necessitating thorough investigations. More than 50% have a vasculopathy including postvaricella angiopathy, dissection, moyamoya, or vasculitis. Intravascular mechanisms are frequently present, including dehydration. Hematological or prothrombotic conditions are also associated with AIS in children, and include sickle cell disease and prothrombotic disorders. The latter have been identified in from one third to one half of children with AIS, are usually acquired, and frequently act in concert with other risk factors for stroke. The most common embolic source is congenital heart disease, which is present in 25% of children with AIS. Outcomes include death in 6% and neurological deficits in two thirds of children. Given that no clinical trials have been completed in pediatric stroke to date, treatment is empiric. Initial neuroprotective strategies aim to reduce the size of the infarct. For older children antithrombotic agents (antiplatelet drugs and anticoagulants) are given to reduce the 20 to 30% risk of recurrence. There are coordinated research efforts currently being initiated, which over the next decade will result in clinical trials in this understudied condition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".