<b>Biocompatibility Studies of the Anaconda Stent-Graft and Observations of Nitinol Corrosion Resistance</b>
Bibliographic record
Abstract
PURPOSE: To validate the deployment, in vivo performance, biostability, and healing capacity of the Anaconda self-expanding endoprosthesis in a canine aortic aneurysm model. METHODS: Aneurysms were surgically created in 12 dogs by sewing a woven polyester patch onto the anterior side of the thoracic or abdominal aorta. Anaconda prostheses were implanted transfemorally for prescheduled periods (1 or 3 months). Aneurysm exclusion and stent-graft patency were monitored angiographically. Healing was assessed with histological analysis and scanning electron microscopy (SEM). Textile analysis determined the physical and chemical stability of the woven polyester material, while the biostability of the nitinol wires was evaluated with SEM and spectroscopy. RESULTS: All prostheses were intact at explantation. After 1 month, endothelial-like cells were migrating in a discontinuous manner both proximally and distally over the internal collagenous pannus at the device-host boundary. After 3 months, endothelialization had reached the midsections of the devices, with a thicker collagenous internal capsule. Patches of endothelial-like cells were sharing the luminal surface with thrombotic deposits. However, the wall of the device at the level of the aneurysm was generally poorly healed, with multiple thrombi scattered irregularly over the luminal surface. The polyester fabric was intact except for some filaments that were ruptured adjacent to the sutures and some abrasion caused by the nitinol wires. No evidence of corrosion was found on the nitinol stents. CONCLUSIONS: This Anaconda stent-graft has demonstrated its ability to exclude arterial aneurysms. The device used in this study was an experimental prototype, and the manufacturer has incorporated new immobilization features into the model for clinical use. The constituent materials appear to be suitable in terms of biocompatibility, biofunctionality, and short-term durability.
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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 | 0.000 | 0.000 |
| 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".