Next frontier in endovascular aortic therapy: An anatomic analysis of feasibility of endovascular treatment of ascending thoracic aortic aneurysms
Bibliographic record
Abstract
Objectives: Ascending thoracic aortic aneurysms (ATAAs) are the next frontier for endovascular aortic repair. This study evaluates anatomic characteristics of ATAAs to inform future design of ascending aortic endografting. Methods: Treatment In Thoracic Aortic aNeurysm: Surgery versus Surveillance is a multicenter trial randomizing patients with ATAA of 5.0 to 5.4 cm to surgery versus surveillance with a parallel real-world Registry. Computed tomography scans from the Treatment In Thoracic Aortic aNeurysm: Surgery versus Surveillance Registry were assessed by a core imaging lab to determine feasibility of endografting on the basis of Information for Use for the Gore Ascending Aortic graft, the only investigational device currently under trials for the ascending aorta. Results: In total, 150 consecutive patients with ATAA ≥5 cm and high-quality computed tomography scans were included. A diameter between 27 and 48 mm existed in 46% (69/150) of patients at the proximal landing zone and 94% (141/150) at the distal landing zone. Arch branching was normal in 68% (102/150), bovine in 21% (38/150), and other in 6.7% (10/150). Mean greater curvature length was 13.2 ± 1.45 cm versus mean lesser curvature of 6.60 ± 0.81 cm. Discrepancy of >5 mm between proximal and distal landing zone diameters existed in 51% (76/150). Conclusions: For ATAAs of 5.0 to 5.4 cm, 3 important challenges to endografting include approximately 50% of patients having a proximal landing zone diameter >48 mm, a 2-fold discrepancy in greater versus lesser aortic curvature length, and >50% of patients with >5-mm mismatch between proximal and distal landing zones. Future stent designs will need to address these important anatomic features unique to the ascending aorta.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".