Abstract 52: Clinical Impairment in Patients Followed With or Without Interventional Therapy in a Randomized Trial of Unruptured Brain Avms (aruba)
Bibliographic record
Abstract
Background and Purpose: A Randomized trial of Unruptured Brain Arteriovenous malformations (ARUBA) compared outcome after interventional treatment of unbled brain AVMs with medical management. Follow-up data to assess pre-specified functional impairment after primary outcome events by treatment group and exploratory analyses by Spetzler-Martin grade are presented. Methods: We examined functional impairment using the modified Rankin scale score (mRS ≥2) at the time of primary outcome (death or stroke) by treatment group, and an exploratory analysis with these outcomes by Spetzler-Martin Grade. Analyses were performed both by intention to treat (as randomized) and as treated. Results: After a median of 42 months of follow-up, the median post-primary outcome event mRS for those ‘ as randomized ’ to medical management (MM) was 2 (IQR: 1,4) versus 3 (IQR: 1,5) in the interventional therapy (IT) arm. Values for those ‘ as treated’ , were 1 (IQR: 1,5) versus 4 (IQR: 2,5). The risk of functional impairment, as measured by an mRS ≥2 after a primary outcome event, was significantly lower for patients ‘ as randomized’ to MM (8/110, 7%) compared to IT (27/116, 23%) (HR 0.26, 95%CI 0.12, 0.57), and even lower for those ‘as treated’ (4/122, 3% vs 31/104, 30%; HR 0.09, 95% CI 0.03,0.27). Spetzler-Martin Grade and primary outcome events were not associated in the medical arm (p=0.80) but were so with increasing grades in the interventional arm (p=0.0002). Conclusion: In ARUBA, a death or stroke with a significant increase in functional impairment was more common for patients undergoing preventive intervention compared to those randomized to medical management.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".