Five-Year Outcomes of Hybrid Arch Frozen Elephant Trunk Repair With Novel Multibranched Hybrid Graft
Bibliographic record
Abstract
Background: The objective of this study was to report the 5-year outcomes of hybrid arch frozen elephant trunk (FET) procedures with a multibranched hybrid graft. Methods: Between 2014 and 2020, 50 consecutive patients (63 ± 15 years old; 34% women) underwent hybrid arch FET with Thoraflex hybrid graft (Terumo Aortic) at a single center. Indications included aortic aneurysm (n = 48 [96%]), acute aortic dissection (n = 10 [20%]), and chronic dissection (n = 20 [40%]). Follow-up was complete, and mean follow-up was 1455 ± 664 days. Results: All 50 patients experienced successful device implantation. The 30-day/in-hospital mortality was 2% (n = 1). Stroke and transient neurologic deficits occurred in 1 patient (2%) and 3 patients (6%). Two patients (4%) and 1 patient (2%) experienced transient and permanent spinal cord ischemia. FET thromboembolic complication was observed in 1 patient (2%). In follow-up, 6 patients died of aortic events, and there were 13 reinterventions in the downstream aorta, of which 46% (6/13) were planned second-stage operations. Survival rate at 1 year, 2 years, and 5 years was 96%, 92%, and 85%, and freedom from unplanned distal reintervention at 1 year, 2 years, and 5 years was 98%, 92%, and 81%. Computed tomography follow-up demonstrated positive distal aortic remodeling with aneurysmal regression and stabilized aortic dimensions in patients with aortic dissection. Conclusions: The hybrid arch FET procedure with a novel hybrid graft is associated with good early and midterm outcomes. Longer term outcomes merit further investigation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".