P.144 Dural arteriovenous fistulas with associated intracranial tumors: review of literature
Bibliographic record
Abstract
Background: Intracranial dural arteriovenous fistulas (DAVF) are relatively rare vascular malformations. While the pathophysiology of their formation is unknown, they are believed to be acquired lesions related to intracranial venous hypertension and dura sinus thrombosis. There have been rare reports of intracranial tumors associated with DAVF. Here we complete a systematic search of the literature. Methods: A systematic PRISMA search of the literature was conducted to identify papers in which an intracranial tumor was associated with sinus thrombosis and DAVF. 24 relevant studies were identified and analyzed, along with a case illustration. Results: A total of 38 cases of DAVF formation with concomitant intracranial tumor were identified. The median age was 60, the majority of tumors being meningiomas (71%), and involved primarily the transverse sigmoid sinus (52%) and superior sagittal sinus (16%). The most cases involved an occlusion (39%) or partial occlusion (24%) of the related sinus. The DAVF were classified as Borden Types I (35%), II (32%) or III (24%). Endovascular treatment was the most common intervention (56%), followed by a combined approach (28%) vs surgery alone (16%), all reporting resolution. Conclusions: This highlights that DAVFs can be rarely associated with intracranial tumors, and highlights the patterns of these lesions and their treatments.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".