Triple-Branched Stent Graft for Acute Type A Aortic Dissection Complicated by Imaging Cerebral Malperfusion: A Multicentre Retrospective Study
Bibliographic record
Abstract
BACKGROUND: Patients with acute type A aortic dissection (ATAAD) complicated by imaging cerebral malperfusion (ICM) have poor prognoses. In this study we aimed to evaluate the clinical efficacy of the modified triple-branched stent graft (MTBSG) in these patients. METHODS: In this retrospective comparative study we analyzed consecutive patients with ATAAD complicated by ICM between 2010 and 2019 who underwent either MTBSG implantation or conventional total arch replacement with frozen elephant trunk. The feasibility was assessed on the basis of intraoperative cerebral blood flow evaluation, early outcomes, long-term survival, neurological prognosis, long-term patency rate, and stent-related complications. The differences between clinical ICM and subclinical ICM patients were compared. RESULTS: Among 145 enrolled patients, 48 underwent conventional total arch replacement with frozen elephant trunk and 97 received MTBSG implantation, with comparable baseline characteristics including preoperative neurological function, severity of carotid involvement, and state. After MTBSG implantation, all patients showed significant improvement in cerebral perfusion, accompanied by shorter cardiopulmonary bypass time and reduced selective cerebral perfusion duration. Although no differences were observed in hospital mortality or permanent neurological deficit rates, the MTBSG group showed potentially favourable trends including less incidence of intracerebral hemorrhage, better neurological recovery reflected by reduced National Institutes of Health Stroke Scale (NIHSS) scores, and improved 5-year survival. Long-term stent patency was well maintained (only 2 patients required intervention), and the stent-related complication rate was low (1 case). CONCLUSIONS: This technique simplifies the surgical procedure, enhances safety, and provides a new strategy for managing ATAAD complicated by ICM. Future prospective studies with larger sample sizes are needed to further validate its long-term benefits.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".