Results and Challenges for the Endovascular Repair of Aortic Arch Aneurysms
Bibliographic record
Abstract
Endovascular aortic arch reconstruction provides an attractive alternative to treat aortic arch disease in high-risk patients who would otherwise be unsuitable for open repair. Success with multibranched stent grafts in the thoracoabdominal aorta along with recent advances in design such as the precurved inner nitinol cannula have simplified the endovascular reconstruction of aortic arch aneurysms with multibranched stent grafts. These devices allow for greater flexibility in conforming to difficult anatomy and preserving important side branches. During the first surgical stage, a left carotid -subclavian bypass or left subclavian artery transposition is performed. The second stage is the endovascular procedure. The device is inserted through a transfemoral approach, and crossing of the aortic valve with the device is necessary. The stent graft is deployed during brief periods of rapid pacing. Bridging from the branches to the innominate and left common carotid arteries requires a suitable covered stent. In the case of a large-diameter innominate artery, a custom-made bridging limb has to be used to ensure that adequate length and size are available. Direct flow to the innominate and left common carotid arteries do not cease for any significant time during the procedure. Initial experience with mean follow up more than 6 months is encouraging. The method is not suitable for patients with extensive atheromatous involvement of the aortic arch. Careful preoperative planning (preoperative imaging, device construction, and access issues), high endovascular skills, and appropriate imaging equipment are imperative for a successful result. Long-term follow-up is necessary to evaluate the efficacy and safety of these new devices.
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 | 0.030 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 0.007 |
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".