Repair of acute type A dissection with distal malperfusion using a novel hybrid arch device
Bibliographic record
Abstract
Acute type A aortic dissection remains a high-risk surgical condition, and mortality among those presenting with malperfusion is up to 3-fold higher. Despite the added technical challenge of distal aortic arch interventions in the acute setting, it may be necessary to resolve distal malperfusion in patients with this disorder. The ideal arch intervention to address acute type A aortic dissection complicated by malperfusion should address the following objectives: (1) to relieve distal malperfusion by expanding the distal true lumen and depressurizing the false lumen; (2) to avoid compromising arch branches without requiring additional arch branch interventions; (3) to minimize the risk of spinal cord ischemia; and (4) to minimize the operative duration and circulatory arrest time. The use of an uncovered aortic arch stent that is delivered in an antegrade manner during circulatory arrest, concomitantly with hemiarch replacement, therefore represents an attractive solution in the management of acute type A aortic dissection complicated by malperfusion. This strategy does not require complex arch reconstruction and may thus be a feasible option among cardiac and vascular surgeons in lower volume aortic centers. Here we present a step-by-step approach to acute type A aortic dissection repair with hemiarch repair and delivery of an uncovered arch stent for a patient presenting with malperfusion.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".