Abstract 195: The Natural History and Predictive Factors of Hemorrhage from Choroidal (Intraventricular) Brain Arteriovenous Malformations
Bibliographic record
Abstract
Background: The natural history and risk of hemorrhage for patients harbouring choroidal/ intraventricular AVMs is poorly understood. We examined the impact of demographic and angiographic features on the likelihood of future hemorrhage. Methods: A prospectively maintained database from the Toronto Western Hospital was analyzed. Inclusion criteria were AVMS that were entirely intraventricular and supplied predominantly from choroidal arteries (anterior/ posterior). The rate of hemorrhage over long term follow up was calculated. The impact of baseline clinical and angio-architectural on time to hemorrhage were analyzed using survival analysis and compared with the total AVM population (n = 1018). Results: 44 patients (median age 27, range 2 - 72 years) identified with choroidal AVMs (4.4% of all AVMs) were followed for 151 patient years. 36 patients (82%) presented with hemorrhage (vs 39% for all AVMs), 28 (77%) of which were predominantly intraventricular. Hemorrhage rates were 7.3%/ year (vs 1.7%/year for all AVMs, HR 2.3, p<0.001). The presence of venous reflux into thalamostriate or cortical veins was a significant independent risk factor for future hemorrhage (HR 1.80, p =0.047) with intranidal aneurysms not significantly associated with future hemorrhage risk (HR = 1.3, p =0.18). Conclusion: Choroidal AVMs are more likely to present with hemorrhage, particularly of the intraventricular type and are associated with approximately 2-fold greater likelihood of future hemorrhage, especially in the presence of venous reflux.
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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 | 0.001 | 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) | 0.003 | 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".