Endovascular Management of Brain Arteriovenous Malformations
Bibliographic record
Abstract
Due to the risk of cerebral hemorrhage, and its related morbidity-mortality, brain arteriovenous malformations (bAVMs) are a rare and potentially life-threatening disease. Despite this, there is only one randomized controlled trial on bAVM management, A Randomized trial of Unruptured Brain Arteriovenous malformations (ARUBA). The results of the ARUBA trial favor a noninterventional approach in the case of an unruptured bAVM; however, implementation of these findings is challenging in daily practice. Instead, management of bAVM relies on multidisciplinary discussions that lead to patient-specific strategies based on patient preferences, local expertise, and experience in referral centers. Considering the diverse patterns of presentation and numerous treatment modalities, implementing standardized guidelines in this context proves challenging, notwithstanding the recommendations or expert opinions offered. Endovascular treatment (EVT) of bAVM can be curative, or can serve as an adjunct treatment prior to surgery or radiosurgery ("pre-EVT"). EVT practice is in constant evolution (i.e., venous approach, combination with surgery during the same anesthesia, etc.). Liquid embolic agents such as ethylene vinyl alcohol (EVOH) copolymer and cyanoacrylates (CYA), and their method of injection to increase bAVM occlusion have also benefited from technical evolutions such as the use of adjunctive flow arrest techniques (mini balloons, pressure cooker technique, and multiple catheters). Further research is necessary to evaluate the advantages and disadvantages of EVT for bAVM.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".