Unibody Endograft Using AFX 2 for Less Invasive and Faster Endovascular Aortic Repair: Protocol for a Multicenter Nonrandomized Study
Bibliographic record
Abstract
BACKGROUND: Since the introduction of endovascular aortic repair (EVAR) for treatment of abdominal aortic aneurysms (AAAs), progressive improvements in results have been achieved. However, conventional bifurcated stent grafts have been proven to have a nonnegligible risk of failure and secondary intervention, principally due to the lack of adequate proximal sealing. The unique AFX 2 Endovascular AAA System (Endologix, Irvine, CA) unibody device, which provides different sealing and fixation features compared with conventional devices, seems to overcome these limitations. OBJECTIVE: The aim of this study is to evaluate intraoperative, perioperative, and postoperative results in patients treated with the AFX 2 Endovascular AAA System endografts for elective AAA repair in a large cohort of consecutive patients. METHODS: All eligible EVAR patients will be included in this observational, multicenter, prospective, nonrandomized study. The number of patients to be enrolled is 500. RESULTS: The primary endpoint of the study is to evaluate the technical and clinical success of EVAR with unibody endografts in short- (90-day), mid- (1-year), and long-term (5-year) follow-up periods. The following secondary endpoints will also be addressed: operative time, intraoperative radiation exposure, contrast medium usage, AAA sac shrinkage at 12-month and 5-year follow-up, and any potential role of patients' baseline characteristics and device configuration on primary endpoint. The actual start date of the investigation was November 2019. The final patient is expected to be treated by the end of December 2020, and the estimated study completion date is December 2025. CONCLUSIONS: This study will provide verified real-world data on AAAs treated by AFX 2 endografts and followed for a long-term interval. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/16959.
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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 | 0.021 | 0.011 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".