P.119 Minimally invasive surgical disconnection of a spinal dural arteriovenous fistula with the use of intraoperative digital subtraction angiography
Bibliographic record
Abstract
Background: Spinal dural arteriovenous fistulas (dAVF) are a significant but treatable cause of progressive myelopathy. The goal of treatment is disconnection of the fistula, which is often accomplished through an open surgical approach. We report two cases using a minimally invasive surgical (MIS) approach for dAVF ligation with intraoperative digital subtraction angiography (DSA) to confirm occlusion. Methods: Case report. Results: Two patients presented with progressive thoracic myelopathy and were identified to have fistulous connections at the left L1 and T8 levels respectively. Intraoperatively, a left femoral puncture was performed and a 5-French (40 cm) sheath was inserted. Patients were positioned prone and intraoperative spinal DSA was performed using the Siemens Zeego. Once the feeding radicular artery was visualized, image overlay and cross-hair laser was used to trace and localize the fistulous zone. A unilateral single level MIS hemi-laminectomy was performed. The fistulous zone and accompanying nerve root were exposed and small hemostatic clips were applied followed by surgically disconnection. Finally, intraoperatively video angiography as well as spinal DSA were performed for confirmation. Conclusions: MIS disconnection with intraoperative DSA is a safe and effective technique for treating spinal dAVFs. Patients benefit from quicker recovery and shorter hospital stay.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".