Autogenous paneled femoral vein grafts for mycotic thoracic aortic aneurysms
Bibliographic record
Abstract
Objective Mycotic thoracic aortic aneurysms (MTAAs) are rare. The most common management has been aortic resection, wide debridement, and in-line reconstruction using prosthetic grafts. We have used autogenous femoral vein (FV) for the repair of all MTAA in our institution since 2017. This is the initial description of this technique, and the first comparative study of autogenous vein compared with prosthetic for MTAAs. Methods This is a single-center retrospective cohort study of all patients with MTAA who underwent operative repair. Patients were assigned to the FV or prosthetic grafts cohorts. Perioperative and long-term outcomes were collected. Univariate logistic regression models were fitted to quantify the strength of differences between the cohorts. Results Nineteen patients were included. The first 9 consecutive patients had prosthetic grafts, whereas the 10 subsequent patients were treated with FV grafts. Patients in the FV cohort were more likely to have positive intraoperative cultures (90% vs 33.3%; P = .02), receive intraoperative transfusions (10 vs 8 units; P = .08), and have a longer operation (629 vs 500 minutes; P = .07). There was a trend toward improved in-hospital (0 vs 33%; P = .09) and long-term mortality (10% vs 55.6%; P = .57) in the FV cohort. Patients in the FV cohort were more likely to be discharged home (90% vs 44.4%; P = .05). Conclusions Paneled autogenous FV repair is a durable and safe treatment for patients with MTAA. There were no in-hospital deaths in our series and there have been no long-term complications related to the vein graft repair.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".