Urothelial-based reconstructive surgery for upper- and mid-ureteral defects: Long-term results
Bibliographic record
Abstract
INTRODUCTION: Ureteral strictures can result in obstructive nephropathy and renal function deterioration. Surgical management of ureteral defects, especially in the proximal- and mid-ureter, is particularly challenging. Our purpose was to analyze the long-term outcomes of urothelial-based reconstructive surgery for upper- and mid-ureteral defects. METHODS: We conducted a retrospective analysis of a single tertiary centre's database, including 149 patients treated for ureteral defects between 2001 and 2011. Thirty-one patients (21%) underwent complex urothelial-based surgical repairs for upper- and mid-ureter defects. Patients' median age was 61 years. The mean length of the ureteral strictures was 2.5 cm, located in upper-, mid-ureter, or in between in 19 (61%), 10 (32%), and two (6%) patients, respectively. All patients were treated with a primary urothelial-based repair. Median followup time was 26 months. The primary outcome of the study was the long-term preservation of renal function and lack of clinical obstruction. The secondary endpoint of the study was the assessment of the intra- and postoperative complication rates. RESULTS: , respectively. Success rate was 84%, defined as lack of need for re-operation or kidney drainage at the last followup. CONCLUSIONS: Upper- and mid-ureteral defects present a complex pathology necessitating experienced reconstructive surgical skills. Our data suggest good long-term results for primary urothelial-based reconstructions for these pathologies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".