Open surgery <i>versus</i> branched endovascular repair of the aortic arch in residual dissections after type A surgical repair
Bibliographic record
Abstract
BACKGROUND: Redo open arch repair is challenging; arch branched endovascular aortic repair (a-BEVAR) offers a less invasive alternative. However, direct comparisons are lacking. The aim of this study was to compare the outcomes of open arch repair versus a-BEVAR in patients with residual aortic dissection after ascending aorta replacement for acute Stanford type A aortic dissection. METHODS: This multicentre retrospective study included patients treated for residual dissection after type A aortic dissection in ten high-volume centres from January 2018 to May 2024. Propensity score matching (1 : 1) was used to adjust for baseline differences. Primary endpoints included 30-day mortality and stroke rates, and secondary endpoints included acute kidney injury, spinal cord ischaemia, reintervention, aortic-related mortality, and hospital length of stay. RESULTS: A total of 183 patients were included: 89 (48.6%) underwent open arch repair and 94 (51.4%) underwent a-BEVAR. After propensity score matching, there were 57 patients in each group. The 30-day mortality rate was 3.5% for open arch repair and 5.3% for a-BEVAR (P = 0.220). The stroke rate was 5.3% for open arch repair and 3.5% for a-BEVAR (P = 0.650). Open arch repair was associated with significantly higher rates of prolonged (>48 h) intubation (28.1% versus 3.5%; P < 0.001), acute kidney injury (31.6% versus 8.8%; P = 0.002), and temporary dialysis (22.8% versus 7.0%; P = 0.002). The median hospital length of stay was 21 days for open arch repair and 10 days for a-BEVAR (P < 0.001). During a median follow-up of 30 months (i.q.r. 7-49), no difference in mortality was observed (10.5% for open arch repair versus 12.3% for a-BEVAR; P = 0.770). CONCLUSION: a-BEVAR provides a less invasive alternative to open arch repair with reduced complications. Long-term studies are needed.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".