Percutaneous Treatment of Concomitant Severe Aortic Stenosis and Thoracoabdominal Aortic Aneurysm
Bibliographic record
Abstract
PURPOSE: Although rare in occurrence, symptomatic severe aortic stenosis and large thoracoabdominal aortic aneurysm (TAAA) found in combination pose a real therapeutic challenge, especially in elderly frail patients. Surgical approaches for combined treatment are complex and at high risk of complications while staged procedures carry the risk of an unfavorable evolution of the condition temporarily left untreated. Minimally invasive approaches may therefore prove a more suitable strategy for these patients. CASE REPORT: We present the case of a 78-year-old woman with symptomatic severe aortic stenosis (AS) and a TAAA of 7.8 cm in diameter. Transcatheter treatment of both conditions was successfully performed in a staged manner. The first intervention consisted of combined transfemoral transcatheter aortic valve implantation (TAVI) immediately followed by a zone 3 thoracic endovascular aortic endoprosthesis deployment. In order to reduce the extent of intercostal arteries coverage and mitigate the risk of medullar ischemia, a second-stage percutaneous endovascular treatment of the TAAA was performed with a customized 4-fenestration prosthesis. Early and 12-month clinical and radiologic follow-up were favorable. CONCLUSION: This case demonstrates how a strong multidisciplinary collaboration allows for successful resolution of complex clinical scenarios.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".