Ureteral Segmental Replacement Using Multilayer Porcine Small-Intestinal Submucosa
Bibliographic record
Abstract
PURPOSE: To assess the outcome of segmental ureteral replacement using a new multilayer porcine small-intestinal submucosa (SIS), Surgisis ES (Cook Inc., Stouffville, ON, Canada) designed to provide enhanced strength. MATERIALS AND METHODS: The ureters of five female farm pigs were accessed through a median laparotomy incision. A segment of 2-cm midureter was resected bilaterally. The left ureteral segments were replaced by 10F tubularized SIS segments using 5-0 PDS interrupted sutures. The right ureters were primarily end-to-end anastomosed, serving as controls. Internal pigtail stents were left bilaterally for 6 weeks. One animal at 3 weeks, one animal at 6 weeks, and three animals at 12 weeks were sacrificed. The patency of the ureters was assessed by retrograde pyelography at 6 and 12 weeks, while inflammation and regeneration were assessed grossly and histologically. RESULTS: At 3 and 6 weeks, both experimental and control ureters were patent without extravasation on retrograde studies. Adhesions and signs of ureteral inflammation were found only on the SIS side. The graft was partially and completely epithelialized at 3 and 6 weeks, respectively. However, at 12 weeks, all the ureters on the experimental side were completely occluded, while on the control side, all were patent. Although histologically, urothelium and muscular cells had proliferated over the graft, they were embedded in an intense fibrotic and inflammatory process. At 12 weeks, all animals had developed hydroureteronephrosis above the grafts. CONCLUSIONS: Technically, Surgisis ES was easily modeled, providing conditions for a water-tight anastomosis. None of the animals developed urinary fistula. Regeneration of urothelium and muscle were induced and supported by the graft. However, functional replacement was not successful. A suitable material for this purpose has yet to be discovered.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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".