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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".