Anatomical Venous Variants in Children With Cerebral Sinovenous Thrombosis
Bibliographic record
Abstract
Background and Purpose- Literature is sparse on the frequency and significance of anatomical venous variants (AVVs) in pediatric cerebral sinovenous thrombosis (CSVT). Methods- We retrospectively reviewed children with CSVT and controls undergoing computed tomography/magnetic resonance venography from January 2008 to 2014. Clinical features examined included raised intracranial pressure, risk factors, and treatment. Radiological features examined included CSVT location, presence and type of AVVs, hemorrhagic venous infarction, and venous collateralization. Clinical outcome was measured by the pediatric stroke outcome measure and radiological outcome by thrombus recanalization. Results- Fifty-one children with CSVT were identified. Twenty-two (43%) had AVVs at presentation. Nineteen (86%) had hypoplasia/absence of major dural sinus, 5 (23%) had persistent fetal structures, 3 (14%) had duplications/fenestrations, and 1 (5%) had disconnected superficial and deep venous systems. Controls had a slightly higher but nonsignificant prevalence 26 (51%) of AVVs. No significant clinical and radiological differences were observed between children with CSVT and AVVs compared with those with typical venous anatomy. Conclusions- AVVs are seen in many children with and without CSVT and do not seem to alter the presentation or clinical course. The influence of these variations on the brain's ability to tolerate venous congestion because of thrombosis merits further study.
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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 | 0.001 | 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".