Gamma Knife surgery for arteriovenous malformations within or adjacent to the ventricles
Bibliographic record
Abstract
OBJECT: The outcomes of stereotactic radiosurgery for arteriovenous malformations (AVMs) within or adjacent to the ventricular system are largely unknown. This study assessed the long-term outcomes and hemorrhage risks for patients with AVMs within this region who underwent Gamma Knife surgery (GKS) at the University of Pittsburgh. METHODS: The authors retrospectively identified 188 patients with ventricular-region AVMs who underwent a single-stage GKS procedure during a 22-year interval. The median patient age was 32 years (range 3-80 years), the median target volume was 4.6 cm(3) (range 0.1-22 cm(3)), and the median marginal dose was 20 Gy (range 13-27 Gy). RESULTS: Arteriovenous malformation obliteration was confirmed by MRI or angiography in 89 patients during a median follow-up of 65 months (range 2-265 months). The actuarial rates of total obliteration were 32% at 3 years, 55% at 4 years, 60% at 5 years, and 64% at 10 years. Higher rates of AVM obliteration were obtained in the 26 patients with intraventricular AVMs. Twenty-five patients (13%) sustained a hemorrhage during the initial latency interval after GKS, indicating an annual hemorrhage rate of 3.4% prior to AVM obliteration. No patient experienced a hemorrhage after AVM obliteration was confirmed by imaging. Permanent neurological deficits due to adverse radiation effects developed in 7 patients (4%). CONCLUSIONS: Although patients in this study demonstrated an elevated hemorrhage risk that remained until complete obliteration, GKS still proved to be a generally safe and effective treatment for patients with these high-risk intraventricular and periventriclar AVMs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".