Craniocervical Arterial Dissection in Children: Clinical and Radiographic Presentation and Outcome
Bibliographic record
Abstract
Craniocervical arterial dissection is a recognized cause of arterial ischemic stroke in children. Whether children with craniocervical arterial dissection have dissection characteristics different from those of adults is unclear. A retrospective review of children, 1 month to 18 years of age, with dissection from two Canadian pediatric ischemic stroke registry centers was conducted. From 213 patients with arterial ischemic stroke, 16 (7.5%) were identified with dissection, 37.5% had warning symptoms, and 50% had a history of head or neck trauma. The clinical presentation included headache (44%), altered consciousness (25%), seizures (12.5%), and focal deficits (87.5%). Dissection involved extracranial vessels in 75% and anterior circulation in 56%. Follow-up included complete recovery in 43%, mild to moderate deficits in 44%, and severe deficits in 13%. Fourteen (87.5%) children received antithrombotic treatment. Follow-up angiography showed resolution of abnormalities in 60% of vessels. Total occlusion had the worst outcome for recanalization. In conclusion, the etiology of arterial dissection in the majority of children appears to be either trauma or idiopathic. Long-term angiography shows variable outcomes, depending on the initial findings. The relationship of angiographic outcomes with recurrent strokes requires further study in pediatric dissection. (J Child Neurol 2006;21:8-16).
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".