Clinical and Imaging Characteristics of Arteriopathy Subtypes in Children with Arterial Ischemic Stroke: Results of the VIPS Study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Childhood arteriopathies are rare but heterogenous, and difficult to diagnose and classify, especially by nonexperts. We quantified clinical and imaging characteristics associated with childhood arteriopathy subtypes to facilitate their diagnosis and classification in research and clinical settings. MATERIALS AND METHODS: The Vascular Effects of Infection in Pediatric Stroke (VIPS) study prospectively enrolled 355 children with arterial ischemic stroke (2010-2014). A central team of experts reviewed all data to diagnose childhood arteriopathy and classify subtypes, including arterial dissection and focal cerebral arteriopathy-inflammatory type, which includes transient cerebral arteriopathy, Moyamoya disease, and diffuse/multifocal vasculitis. Only children whose stroke etiology could be conclusively diagnosed were included in these analyses. We constructed logistic regression models to identify characteristics associated with each arteriopathy subtype. RESULTS: = 26), at all ages. Vertigo at stroke presentation was common in dissection. Dissection affected the cervical arteries, while Moyamoya disease involved the supraclinoid internal carotid arteries. A banded appearance of the M1 segment of the middle cerebral artery was pathognomonic of focal cerebral arteriopathy-inflammatory type but was present in <25% of patients with focal cerebral arteriopathy-inflammatory type; a small lenticulostriate distribution infarct was a more common predictor of focal cerebral arteriopathy-inflammatory type, present in 76%. It remained difficult to distinguish focal cerebral arteriopathy-inflammatory type from intracranial dissection of the anterior circulation. We observed only secondary forms of diffuse/multifocal vasculitis, mostly due to meningitis. CONCLUSIONS: Childhood arteriopathy subtypes have some typical features that aid diagnosis. Better imaging methods, including vessel wall imaging, are needed for improved classification of focal cerebral arteriopathy of childhood.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".