Benign cranial dural arteriovenous fistulas: outcome of conservative management based on the natural history of the lesion
Bibliographic record
Abstract
OBJECT: Cranial dural arteriovenous fistulas (DAVFs) can be classified into benign or aggressive, based on their patterns of venous drainage. A benign condition requires the absence of cortical venous drainage (CVD). The clinical and angiographic features of a consecutive single-center group of 117 patients harboring benign cranial DAVFs were evaluated over time to validate the behavior and appropriate management of these lesions. METHODS: At the initial assessment four patients were asymptomatic. Two infants presented with congestive heart failure. All other patients presented with other benign symptoms: chronic headache, bruit, or orbital phenomena. Observational management was instituted in 73 patients (62%). Intolerable bruit or ophthalmological sequelae were deemed indications for palliative embolization in 43 patients and surgical treatment in one patient. A median follow-up period of 27.9 months (range 1 month-17.5 years) was available in 112 patients (95.7%), among whom repeated angiography was performed in 50. Overall, observational and palliative management resulted in a benign and tolerable level of disease in 110 (98.2%) of 112 cases. In two cases managed conservatively CVD developed. In both of these cases the conversion from benign to aggressive DAVF was associated with spontaneous progressive thrombosis of venous outlets. CONCLUSIONS: The disease course of a cranial DAVF without CVD is indeed benign, obviating the need for a cure of these lesions. Symptoms are well tolerated with either observation or palliative treatment. After a long-term follow-up review of 68 patients, this conservative management resulted in a benign and tolerable level of disease in 98.5% of cases. It is noteworthy, however, that a benign DAVF carries a 2% risk of developing CVD, mandating close clinical follow-up review in such cases and renewed radiological evaluation in response to any deterioration in the patient's condition.
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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 | 0.000 |
| 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) | 0.000 | 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".