Analysis of Explanted Latecba Modular Stent-grafts Deployed Transrenally to Repair AAAs with Short Necks in 29 Dogs
Bibliographic record
Abstract
Twenty-nine modular stent-grafts deployed transrenally to repair AAAs with short necks in dogs were harvested at autopsy of the animals after scheduled durations of implantations of 10 days, one month, three months, and six months. Analyses of the explanted devices included non-destructive techniques such as gross observations, X-rays CT scan, IVUS and angioscopy. Further to appropriate dissection, histological investigations were carried out by means of scanning electron microscopy (SEM) and light microscopy. All the 29 specimens were extensively encapsulated with fibrous tissues but the fibrous capsule was thin in six of them; four capsules were ulcerated. The X-rays confirmed the stability of the devices that were still straight (12), slightly bent (12) or bent (4). The modules were misaligned in only one case. IVUS and angioscopy confirmed the patency of all the stent-grafts with thin internal capsules both proximally and distally with variable capsulation in the mid-section of the grafts. The left renal artery orifices were found to be patent at dissection with no obstruction to flow. The luminal flow surface of the stent-grafts was smooth and glistening proximally and distally containing endothelial like cells and vasa-vasorum. Poor healing was noted in the aneurysm area. Transrenal deployment of this modular stent-graft is feasible and gave excellent results with regard to biofunctionality and biocompatibility. The device proved to be safe and efficient.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".