Therapeutic Management of Cerebral Arteriovenous Malformations. Present Role of Interventional Neuroradiology
Bibliographic record
Abstract
This chapter summarizes the authors' experience in the endovascular therapy of cerebral arteriovenous malformations (AVMs). This clinical series includes 660 patients treated from 1980 to 2005. The first 148 patients were treated at University Hospital, in London, Ontario Canada, in association with Drs. Allan Fox, Dave Pelz, John Girvin and Charles Drake. The next 512 patients were treated at UCLA Medical Center, Los Angeles, California in association with Drs. Gary Duckwiler, Reza Jahan, Jacques Dion, Pierre Gobin, Neil Martin and John Frazee. Only patients treated with superselective endovascular/intraoperative catheterization and embolization of avm arterial feeders were included. Cerebral arteriovenous malformations treated by non-selective injection of beads in ICA or vertebral arteries were excluded. Modern neuroimaging modalities associated to the anatomical, topographic and functional evaluations of cerebral avms such as brain CT and CTA, MRI, MRA and functional MRI are all utilized at UCLA Medical Center. They have become essential in the therapeutic management of avms closely related to cerebral eloquent areas (figure 1).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".