Clinical success of buccal mucosal graft in open ureteroplasty for proximal ureteral stricture
Bibliographic record
Abstract
Proximal ureteric strictures remain problematic in urological cases, with few treatment options. Buccal mucosal grafts (BMGs) are in wide use for urethral reconstruction and provide suitable characteristics for optimal ureteral stricture repair. In this case, a 72-year-old patient was referred for consideration of left proximal ureteric reconstruction with a 4–5 cm stricture after failure of endoscopic management for a neglected stent. The patient had good contralateral kidney function, and he underwent an open ventral onlay ureteroplasty with BMG. Endoluminal visualization and retrograde ureterography reported success of the repair up to 16 weeks post-operatively. The patient remained symptom free at the time of this case report. The favourable outcome of this case is supported by the literature with the caveat of few case reports and varied follow-up. Overall, this case provides a positive outlook for the widespread adoption of BMGs in ureteral reconstruction. Lay Summary: The drainage of urine is important to keep the kidneys functioning well and to remove unwanted substances from the body - this relies on the ureters (the tubes connecting the kidneys to the bladder) to remain open to help drain the urine out of the body. In this case, a 72 year old gentleman suffered from a narrowed ureter causing blockage and loss of function of his left kidney. This was repaired by using tissue the inside of his cheek (called a buccal mucosal graft) to replace the narrowed part of his ureter in an operation. This operation proceeded without complication and the left kidney showed improved drainage sixteen weeks afterwards. We present this case in the hopes that it provides a positive outlook for the widespread adoption of this surgical technique.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".