Endoscopic treatment of ureterovesical junction obstructive pathology: A description of the oblique meatotomy technique and results
Bibliographic record
Abstract
BACKGROUND: Benign obstructive pathology of the ureterovesical junction includes congenital and acquired illnesses. The objective of this study was to describe the endoscopic oblique meatotomy technique using scissors and cold cutting to treat benign obstructive pathology of the ureterovesical junction. METHODS: From 2007 to 2012, we treated 18 patients with obstructive pathology of the ureterovesical junction (5 megaureters [3 with lithiasis], 4 iatrogenic stenoses, and 9 ureteroceles with lithiasis). In all cases, oblique meatotomy was performed using endoscopic scissors through an 8.5 Ch ureteroscope. The mean follow-up for all patients was 3 years. Pain, grade of hydronephrosis, and occurrence of vesicoureteral reflux were evaluated before and after treatment. RESULTS: The mean endoscopic treatment time was 13.4 minutes. The procedure was performed on an outpatient basis with 6 hours of hospital admission, and a double J stent was inserted for 6 weeks. We achieved treatment success in 94.5% of patients after 3 years of follow-up. Only 1 patient presented with vesicoureteral reflux at 12 months after treatment; however, this condition did not require further treatment. Overall, 100% of patients remained free from lithiasis. There are 2 main limitations: the small number of patients and the lack of another group to compare the results of this technique; however, the aim of this work was to communicate a new technique to treat ureterovesical junction stricture. INTERPRETATION: Oblique ureteral meatotomy is a safe and effective treatment for benign obstructive pathology of the ureterovesical junction and has a low index of complications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".