Torcular Dural Arteriovenous Fistula: A Retrospective Observational Study of Patient, Angiographic, and Treatment Characteristics
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Torcular dural arteriovenous fistulas (dAVFs) are rare, often have an aggressive natural history, and present unique challenges because of complex vascular supply and involvement of bilateral venous sinuses. The study audits the authors' institutional experience treating patients with torcular dAVFs. METHODS: All patients with torcular dAVFs from January 2013 to July 2024 were included. Baseline patient and angioarchitecture characteristics were recorded, alongside treatment strategy. Functional outcome at last clinical follow-up was measured using modified Rankin Scale (mRS) score. Univariate and multivariable logistic regressions assessed association between patient characteristics and dichotomized mRS. RESULTS: Seventeen patients (mean age 65 ± 17 years) were included; 53% were female. Most patients (88%) were symptomatic: 18% presented with hemorrhage, 47% with nonhemorrhagic global neurological deficit, and 24% with focal nonhemorrhagic neurological deficit. Most (14/17, 82%) had high-grade dAVFs (Borden II/III and Cognard IIb-IV). Endovascular embolization was used in 71%, whereas surgery was used in 12%. Angiographic cure was achieved in 63% of patients. Overall, 76% of patients had good functional outcomes (mRS 0-2). On univariate and multivariate analysis, both focal nonhemorrhagic neurological deficit ( P = .015) and baseline mRS ( P = .044) were associated with improved functional outcome. CONCLUSION: Borden II/Cognard 2A/B lesions are best treated by transarterial or combined transarterial/transvenous embolization, whereas Borden III/Cognard III/IV lesions are best treated by transarterial embolization or surgical disconnection. Transvenous approaches are reserved for lesions where the fistulous point is accessible. Patients with good functional status at presentation or focal neurological deficits improved after treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".