Abstract 19354: Management and Outcomes of Acute Type B Dissection in IRAD Treated with Open Surgery, Endovascular Flap Fenestration or TEVAR
Bibliographic record
Abstract
Background: The debate for the optimal treatment of complicated Type B Acute Aortic Dissection (TBAAD) is primarily focused upon open surgical intervention versus thoracic endovascular aortic repair (TEVAR). The technique of fenestration with stenting has been proposed to resolve malperfusion. This study evaluated post-procedural outcomes of all three approaches for TBAAD. Methods: TBAAD patients enrolled in the International Registry of Acute Aortic Dissection were stratified by management type: TEVAR, fenestration and stenting, and surgery. Results: Of the 552 patients with TBAAD, 231 (41.8%) underwent TEVAR, 214 (38.8%) standard open surgery, and 107 (19.4%) fenestration and stenting. TEVAR or fenestration and stenting were more likely to be performed in classic double barrel aortic dissection when compared to open surgery (73.2%, 76.6%, 52.8% respectively; p<0.001). Patients treated with open repair were less likely to have distal extension into the abdominal aorta than those with TEVAR or fenestration and stenting (47.7%, 62.7%, 86.4%, respectively; p<0.001). In-hospital mortality was similar between groups (11.7% TEVAR, 14.0% fenestration and stenting, 15.9% surgery). At five years, Kaplan-Meier post-discharge all-cause survival estimates were highest for TEVAR, followed by endovascular fenestration and finally open surgical intervention (85.2%, 78.3%, 67.2%, respectively; p=0.039). Conclusion: Patients treated by endovascular approaches, whether with flap fenestration or thoracic endovascular aortic repair, had lower five year mortality when compared to patients who required open repair in the setting of TBAAD. Either endovascular approach may be helpful in the treatment of TBAAD. Further research is needed to determine how much of the observed difference represents patient selection versus differential effects of treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".