Temporary surgical clipping of flow-diverted arteries in an experimental aneurysm model
Bibliographic record
Abstract
OBJECTIVE Surgical management of recurrent aneurysms following failed flow diversion may pose difficulties in securing vascular control with temporary clips. The authors tested the efficacy and impact of different types of aneurysm clips on flow-diverted arteries. METHODS Six wide-necked experimental aneurysms were created in canines and treated with Pipeline flow diverters. In 4 aneurysms, occlusion of the artery at the level of the proximal and distal landing zones (n = 2 per aneurysm) was attempted, using temporary, fenestrated, single, and double permanent aneurysm clips. Two aneurysms served as unclipped controls. Serial angiography was performed to investigate the efficacy of clip occlusion, flow diverter deformation, and thrombus formation. After the animals were killed, the flow-diverted aneurysm constructs were opened and photographed to determine neointimal or device damage as a result of clip placement. RESULTS Angiography-confirmed clip occlusion was only possible for 4 of 8 of the tested flow-diverted arterial segments. Clip application attempts led to filling defects consistent with thrombus formation in 2 of 4 flow-diverted constructs, and to minor damage of the flow diverter with neointimal fracture in 1 of 4 cases. CONCLUSIONS Aneurysm clips placed on canine parent arteries bearing a Pipeline flow diverter were unable to reliably stop blood flow. Application of aneurysm clips can cause mild damage to the device and neointima, which might translate into thromboembolic risks. If possible, vascular control should be sought beyond the terminal ends of the implanted device.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".