Systematic Review on In Situ Laser Fenestrated Repair for the Endovascular Management of Aortic Arch Pathologies
Bibliographic record
Abstract
BACKGROUND: In situ laser-fenestrated thoracic aortic endovascular repair (FTEVAR) has emerged as a valuable alternative for aortic arch management. This review assessed the early and follow-up outcomes of in situ laser-FTEVAR in aortic arch pathologies. METHODS: The PRISMA statement was followed. The English literature was searched, via Ovid, until 15 October 2022. Observational studies, published after 2000, reporting on early and follow-up outcomes for the in situ laser-FTEVAR were eligible. The Newcastle-Ottawa Scale was used to assess the risk of bias. Primary outcomes were the technical success, stroke, and mortality at 30-days, and the secondary were the mortality and reintervention during follow-up. RESULTS: Six retrospective studies from 591 and 247 patients were included. Fifty-nine (23.9%) patients were managed for aortic arch aneurysms and 146 (59.1%) for dissections; 22.6% of them for type A. Technical success was at 98% (range 90-100%). Eight patients died (3.2%) and 11 cases presented any type of stroke (4.5%) during the 30-day follow-up. The mean follow-up was 15 months (1-40 months). Ten deaths were reported (4.2%); one was aortic-related (10%). Thirteen re-interventions (6.0%) were performed. CONCLUSIONS: In situ laser-FTEVAR for aortic arch repair may be performed with high technical success and low 30-day and midterm follow-up mortality, stroke, and re-intervention rates when applied in well selected patients and performed by experienced teams.
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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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".