Abstract 156: Embolization Followed by Radiosurgery for the Treatment of Brain Arteriovenous Malformations (AVMs)
Bibliographic record
Abstract
Purpose: Multimodality therapy of brain AVMs with embolization followed by radiosurgery is controversial. We present the largest case series to date of AVM patients treated with embolization and radiosurgery. Methods: Retrospective review of our institutional AVM database identified 92 patients treated from 1995-2009 with embolization followed by radiosurgery. Patients treated with surgery or radiosurgery prior to embolization were excluded. Pre- and post-embolization AVM volumes were calculated using angiography. The modified Pollock-Flickinger (PF) score was also calculated pre and post-embolization. PF scores from pre-embolization volumes were used to report obliteration rates. Post-radiosurgical obliteration was assessed using angiography or MRI. Results: Mean AVM volume went from 19.95 ml (IQR, 10.3 - 32.75) to 10.17 (3.15 - 20.65) following embolization (p<0.001) and mean PF scores decreased from 2.78 (1.77-3.94) to 1.83 (1.07 - 2.79), p<0.001. 2/92 (2.2 %) had new fixed deficits following embolization, however no patient had new disabling deficits (mRS>2). 61/92 (66%) have had ≥3 year follow-up and 35/61 (57%) had excellent outcomes (complete obliteration without neurologic decline). Excellent outcome was seen in 88% of patients with modified PF score <1, 67% of patients with score 1-1.5, 44% patients with score 1.5-2, and 48% of patients with score >2. In addition 16 patients had complete obliteration with further treatment (total 51/61 patients- 84%). Two patients died in the follow-up period due to AVM bleed. Conclusion: These data suggest that embolization of brain AVMs can safely and effectively reduce the treatment volume prior to radiosurgery. Combined therapy with embolization and radiosurgery does not adversely affect rates of excellent outcome.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".