The Impact of ARUBA on the Management of Unruptured Brain Arteriovenous Malformations : Review of Literature
Bibliographic record
Abstract
Optimal management of unruptured brain arteriovenous malformations (bAVMs) remains controversial. Unruptured bAVMs are believed to confer a life-long risk of hemorrhage at approximately 1-4% per year. Treatment modalities, such as neurosurgery, radiosurgery and embolization, are able to eliminate the risk of hemorrhage, but are associated with treatment risks. Thus the risk/benefit rationale of treating unruptured bAVMs is unclear. ARUBA (A Randomized Trial of Unruptured Brain Arteriovenous Malformation) was a multi-center randomized controlled trial conducted to compare conservative medical management and active intervention. It was terminated early due to a statistically significant superiority of medical management over interventional treatment, but has itself raised controversy because of its design, results and conclusions. Since its publication in 2014, the implications of ARUBA have already affected neurosurgical practice. However, due to ARUBA's limitations, the findings are not necessarily generalizable to all bAVMs. Treatment of bAVMs should be evaluated on an individual basis, accounting for the location of bAVMs, features of the angio-architecture, patient characteristics, and the individual institutions' experience with each modality of treatment.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".