The frozen elephant trunk: seeking a more definitive treatment for acute type A aortic dissection
Bibliographic record
Abstract
OBJECTIVES: Conventional treatment for type A aortic dissection includes replacement of the ascending aorta with an open distal anastomosis in the hemiarch position. The frozen elephant trunk (FET) is a hybrid technique that extends the repair to the descending thoracic aorta. The goal is to improve resolution of malperfusion syndrome and to induce positive aortic remodelling and reduce the need for reintervention on the downstream aorta. We aim to summarize the data on the short and long-term outcomes of this technique. METHODS: A thorough search of the literature was conducted isolating all articles dealing with aortic remodelling after the use of FET in case of type A acute aortic dissection. Keywords 'aortic dissection', 'frozen elephant trunk', 'aortic remodelling' and 'false lumen thrombosis' were used. Data for type B and chronic aortic dissections were excluded. RESULTS: FET use favourably influences aortic remodelling. The main advantages lie in the exclusion of distal entry tears in either the aortic arch or descending aorta thus restoring antegrade blood flow in the true lumen and inducing false lumen thrombosis. False lumen thrombosis is not only induced at the level of the stent deployment but also lower in the distal descending aorta. Moreover, it offers an adequate landing zone in the mid-descending aorta for second-stage endovascular or open surgical aortic repair, if needed. CONCLUSIONS: FET can be advantageous in the treatment of acute type A aortic dissection dealing with extended aortic pathology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".