Transvenous Treatment of Cranial Dural Arteriovenous Fistulas with Hydrogel Coated Coils
Bibliographic record
Abstract
SUMMARY: Intracranial dural arteriovenous fistulas (DAVF) with cortical venous reflux may become symptomatic due to venous congestion or intracranial hemorrhage. Venous congestion in the orbit can also occur resulting in proptosis, chemosis, double vision and progressive visual loss. The transvenous approach has been used for selective disconnection of the venous drainage to eliminate the venous congestion and future risk of intracranial bleeding and/or neurological deficit. Hydrogel coated coils (Hydro- Coil(R)) expand after contact with blood causing the coils to swell up to five to 11 times a standard 10-system bare platinum coil. Due to this property, HydroCoils could have an advantage over platinum coils in the transvenous approach to embolization of DAVFs. Ten patients with symptomatic cranial DAVF underwent a transvenous embolization using HydroCoils as the only embolic agent or in a combination with bare platinum coils. The patients' characteristics, symptoms, angioarchitecture of the DAVF, treatment, complications and results were analyzed. All the treated DAVFs were disconnected at the end of the procedure. All the patients with orbital symptoms had complete or significant improvement. There were no periprocedural complications. Nine patients had radiological follow-up showing cure. HydroCoils can be used effectively and safely to treat intracranial DAVFs transvenously. The volume expansion of Hydrocoils may have significant advantage over bare platinum coils given the large venous spaces that need to be filled. The use of HydroCoils may decrease the procedure time and consequently reduce the radiation dose to the patient.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".