Recanalization Rates after Endovascular Coil Embolization in a Cohort of Matched Ruptured and Unruptured Cerebral Aneurysms
Bibliographic record
Abstract
The aim of this study was to retrospectively assess the recanalization rate, factors associated with and time taken for recanalization to occur in a matched ruptured and unruptured aneurysm population that were treated with endovascular coiling.Ruptured and unruptured aneurysms treated between 2002 and 2007 were matched for aneurysm location, diameter and neck size. Recanalization rate, time to recanalize, re-treatment rate and clinical outcome were analysed. Ninety-eight matched ruptured and unruptured aneurysms (49 aneurysms in each group) were studied. 46.8% of aneurysms in the ruptured group achieved complete obliteration on the initial post treatment angiogram versus 34.7% in the unruptured group. The ruptured group had a higher rate of recanalization (40.4% versus 20.4%). 25.5% of aneurysms had significant recanalization in the ruptured group versus 6.1% in the unruptured group (p=0.009). The retreatment rate was higher in the ruptured group (21.3% versus 6%). Ruptured aneurysms took a shorter time to recanalize with a mean time of 5.3±3.8 months versus 12.4±7.7months (p=0.003). Multivariate logistic regression analysis found neck size (p=0.0098), wide neck morphology (p=0.0174), aneurysm diameter (p< 0.0001) and ruptured aneurysms (p=0.0372) were significant predictors of recanalization. The majority of patients in both groups had a good outcome with GOS=5 (85.7% and 83.7%) but two deaths occurred in the ruptured group.Ruptured and unruptured aneurysms showed significant differences in rate, degree and timing of recanalization, thus requiring different protocols for imaging follow-up post endovascular treatment. Earlier and more frequent imaging follow-up is recommended for ruptured aneurysms.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".