Compaction of flow diverters improves occlusion of experimental wide-necked aneurysms
Bibliographic record
Abstract
INTRODUCTION: Flow diverters (FDs) are increasingly used in the treatment of wide-necked aneurysms. OBJECTIVE: To examine the hypothesis that intentional FD compaction might improve aneurysm occlusion rates. METHODS: Bilateral wide-necked carotid aneurysms were created in 12 dogs. Endovascular treatment was performed 1 month later, using Pipeline embolization devices deployed with compaction across the aneurysm neck (n=12). Group 1a consisted of aneurysms treated with a single compacted FD (n=8), while group 1b aneurysms required two compacted FDs (n=4). Control aneurysms were treated with a single non-compacted FD (group 3; n=6), or not treated (group 4; n=4). Angiographic results were compared at 3 months. Pathology specimens were photographed and the neointimal coverage of devices scored using an ordinal grading system. RESULTS: Twenty-two of 24 aneurysms were patent at 1 month. Deployment with compaction was successful in eight cases (group 1a aneurysms). The compaction maneuver led to immediate FD prolapse into the aneurysm in four cases, rescued by deploying a second, telescoping FD (forming group 1b aneurysms). One compacted device later migrated distally, leaving the aneurysm untreated. Angiographic results differed significantly between groups (p=0.0002). At 3 months, aneurysms successfully treated with a single compacted FD were more often occluded at 3 months (7/7) than aneurysms flow-diverted without compaction (2/6; p=0.021). All aneurysms treated with two compacted FDs were occluded, while all untreated aneurysms remained patent. There were no parent vessel stenoses. CONCLUSIONS: Compaction of FDs can improve angiographic occlusion of experimental wide-necked aneurysms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".