Role of the Endothelial Lining in Recurrences After Coil Embolization
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Endovascular treatment can improve the outcome of patients treated for ruptured intracranial aneurysms as compared with surgical clipping, but angiographic recurrences are frequent. Endothelial denudation before coil embolization may prevent recanalization and improve results of endovascular treatment. METHODS: We compared angiographic and pathological results 3 months after coil occlusion of paired canine arteries (n=16), with or without previous denudation of the endothelial lining using an endovascular device. The technique was then used to denude the neck of carotid venous pouch bifurcation aneurysms before coil embolization in 8 dogs, and the angiographic evolution at 12 weeks was compared with 7 control aneurysms treated by coiling only. Qualitative scoring systems were used to compare angiographic results with time and neointimal coverage at the neck of aneurysm after necropsy. The evolution of angiographic scores was analyzed using Wilcoxon signed rank tests whereas angiographic and neointimal scores of the 2 groups were compared using the Mann-Whitney test. RESULTS: All arteries embolized with platinum coils recanalized, whereas most arteries (12/16 or 75%) denuded before coil embolization remained occluded at 3 and 12 weeks (P<0.001). Aneurysms treated with coils without previous denudation tended to recur, with angiographic scores significantly worse at 12 weeks as compared with T(0) (P=0.015). Median angiographic and neointimal scores were significantly better at 12 weeks with endothelial denudation (P=0.011 and 0.026, respectively). CONCLUSIONS: Endothelial denudation can prevent recanalization after coil embolization.
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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 | 0.001 | 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".