The Success of Flow Diversion in Large and Giant Sidewall Aneurysms May Depend on the Size of the Defect in the Parent Artery
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Flow diverters are designed to occlude aneurysms while preserving flow to jailed arterial branches. We postulated that treatment success depended on the size of the aneurysm ostium or defect in the parent artery. MATERIALS AND METHODS: Flow diverter expansion and deformation were studied in silicone tubes with wall apertures of various sizes. Large and giant canine sidewall aneurysms, featuring a branch located immediately opposite the aneurysm, and a smaller 6- to 8-mm (group A, n = 6) or a larger 10- to 16-mm (group B, n = 6) ostium were created to study the effects of ostium size on aneurysm or branch occlusion by flow diverters. Angiographic results after deployment and at 3 months were scored by using an ordinal scale. The amount of neointima formation on the segment of the device overlying the aneurysm or the branch ostia was determined by specimen photography. RESULTS: The fusiform deformation of flow diverters was maximal with larger defects in silicone tubes. At 3 months, group B aneurysms showed worse angiographic results than group A aneurysms, with larger residual aneurysm volumes (P = .002). Neointimal coverage of the aneurysm ostia was more complete in group A compared with group B (P = .002). CONCLUSIONS: The effects of flow diversion may vary with the size of the aneurysm ostium.
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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 | 0.002 |
| 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 | 0.001 |
| 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".