Angioarchitectural features associated with hemorrhagic presentation in pediatric cerebral arteriovenous malformations
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: To date, there have been few published studies examining the relationship between arteriovenous malformation (AVM) angioarchitecture and hemorrhagic presentation among children with cerebral AVMs. This study examines this relationship in this unique population, in whom symptomatic presentation of cerebral AVM is the norm rather than the exception. METHODS: A cohort of children with AVMs from 2000 to 2011 were included. Predictors studied included patient age, gender and angioarchitectural features, including AVM location, nidus size and morphology, venous drainage, presence of venous outflow lesions and associated aneurysms. Predictors of hemorrhagic presentation were assessed using multivariate logistic regression. RESULTS: 135 children (70 males, mean age 10.1 years) were included. 86/135 (63.7%) children presented with hemorrhage, 18 (13.3%) with seizures, 17 (12.6%) with headaches or neurological deficits and 14 (10.4%) were asymptomatic. AVM location, morphology and the presence of associated aneurysm, venous ectasia, draining vein stenosis and single draining vein were not significantly associated factors. After multivariate analysis, AVM size (OR 0.57, 95% CI 0.43 to 0.77; p<0.01), exclusive deep venous drainage (OR 4.94, 95% CI 1.30 to 18.8; p=0.02) and infratentorial location (OR 9.94, 95% CI 1.71 to 51.76; p=0.01) were independently associated with hemorrhagic presentation. CONCLUSION: Smaller AVM size, exclusive deep venous drainage and infratentorial location are specific angioarchitectural factors independently associated with initial hemorrhagic presentation in children with AVMs.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".