Fibromuscular dysplasia and childhood stroke
Bibliographic record
Abstract
Arteriopathies are the leading cause of childhood stroke but mechanisms are poorly understood. Fibromuscular dysplasias are non-inflammatory arteriopathies classically described in adults with a cerebral-renal distribution and distinct 'string-of-beads' angiographic appearance. Diagnostic characteristics of paediatric fibromuscular dysplasia are uncharacterized. We aimed to compare pathologically proven versus clinically suspected paediatric fibromuscular dysplasia stroke cases to elucidate diagnostic features. Children in the Canadian Paediatric Ischaemic Stroke Registry, Calgary Paediatric Stroke Program, and published literature were screened for stroke associated with fibromuscular dysplasias or renal arteriopathy. Comparison variables included pathological classification, presentations, stroke types, imaging/angiography, treatments, and outcomes. We report 81 cases (15 new, 66 from the literature). For pathologically proven fibromuscular dysplasia (n = 27), intimal fibroplasia predominated (89%) and none had typical adult medial fibroplasia. Ischaemic strokes predominated (37% haemorrhagic) and were often multifocal (40%). Children often presented early (33% <12 months). Angiography demonstrated focal, stenotic arteriopathy (78%) rather than 'string-of-beads'. Renal arteriopathy (63%) with hypertension (92%) was common, with systemic arteriopathy in 72%, and moyamoya in 35%. Anti-inflammatory (29%) and anti-thrombotic (27%) therapies were inconsistently applied. Outcomes (mean 43 months) were poor in 63%, with stroke recurrence in 36%. Clinically suspected fibromuscular dysplasias (n = 31) were usually older, normotensive with string-of-beads angiography and good outcome. We conclude that fibromuscular dysplasia causes childhood stroke with distinctive clinic-radiological features including hypertension and systemic arteriopathy. Intimal fibroplasia predominates while 'string of beads' angiography is rare. Accurate clinical diagnosis is currently challenging.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".