Clinical Impairment in Patients Followed with or without Interventional Therapy in a Randomized Trial of Unruptured Brain AVMs (ARUBA) (S7.007)
Bibliographic record
Abstract
Background and Purpose A Randomized trial of Unruptured Brain Arteriovenous malformations (ARUBA) compared outcome of unbled brain AVMs with medical management with and without interventional treatment. Follow-up data and pre-specified secondary analyses are presented which assessed functional impairment after primary outcome events by treatment group and by Spetzler-Martin grade. Methods We examined functional impairment defined by the modified Rankin scale score (mRS ≥2) at the time of primary outcome (death or stroke), and compared the frequency of such functional impairment and its association with both the Spetzler-Martin Grade and primary outcome events by treatment group. Analyses were performed both by “as randomized” (intention to treat) 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’ in MM were 1 (IQR: 1,5) versus IT 4 (IQR: 2,5). As measured by mRS ≥2, the risk of functional impairment, after a primary outcome event was significantly lower (HR 0.26. 95[percnt]CI 0.12-0.57) for patients ‘as randomized’ to MM compared to IT, and even lower for those ‘as treated’ (HR 0.09, 95[percnt]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, 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. Outcome events were both far less frequent and of lower severity for those having no intervention, irrespective of the Spetzler-Martin Grades,
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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) | 0.003 | 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".