Long-Term Outcomes in Patients Undergoing Thoracic Endovascular Aortic Repair. Single Center Experience
Bibliographic record
Abstract
Background: To analyze long-term outcomes in patients undergoing thoracic endovascular aortic repair (TEVAR). Methods: All consecutive 97 patients undergoing TEVAR between September 2014 and September 2022 were included in the study. The primary outcome was the long-term incidence of overall death and major adverse cardiovascular and cerebrovascular events (MACCE). Results: Mean age was 70.4 years, and 22 (23.2%) had cerebrovascular disease (CBVD). 49 (51.6%) patients had prior cardiac surgery intervention and 8 (8.5%) had prior aortic valve replacement. Twenty-eight patients (28.8%) presented with aortic dissection, 60 (61.8%) had aortic aneurysm, 4 (4.1%) had intramural hematoma, and 5 (5.1%) had other presentations. An emergent procedure was performed in 6 (6.2%) patients, an urgent procedure in 37 (38.1%) patients and 54 (55.7%) patients had an elective procedure. Intraoperatively, 78.3% had percutaneous TEVAR, 5.1% had ministernotomy TEVAR, while 10.3% had concomitant full sternotomy TEVAR repair. Hospital mortality occurred in 7 patients (7.2%). At 8-year follow-up, 76% were alive, 25.8% had MACCE, 21.6% were diagnosed with endoleaks (13 patients type II and 2 patients type 1) and 10.3% underwent repeat intervention. Conclusions: This single-center study found that patients undergoing TEVAR had good short- and long-term survival and MACCE. Despite almost half of the patients undergoing an urgent/emergent procedure, the clinical outcomes were favorable for TEVAR.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".