Hybrid arch frozen elephant trunk repair for acute type A aortic dissection: Extra-anatomic subclavian reconstruction
Bibliographic record
Abstract
Acute type A aortic dissection is a life-threatening condition that confers significant early perioperative risk but is also associated with late aortic disease progression and the need for reintervention. Recent efforts to improve patient outcomes have focused on improving quality of care and extending treatment in the aortic root and arch to reduce late aortic events. The hybrid arch frozen elephant trunk technique facilitates a more aggressive distal aortic repair that may help mitigate the early and late deleterious effects of persistent false lumen perfusion. However, in the acute and emergency settings, management of the left subclavian artery remains a challenge. We present a step-by-step instructional guide on performing an emergency hybrid arch frozen elephant trunk procedure with emphasis on management of the difficult left subclavian artery. Our case report demonstrates a transthoracic aortoaxillary extra-anatomic bypass of the left axillary artery. We discuss the most important considerations when managing the left subclavian artery in an acute type A aortic dissection. Finally, we detail the benefits and limitations of the transthoracic aortoaxillary extra-anatomic technique and discuss other approaches to left subclavian artery reconstruction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".