Treatment of congenital distal ureteral orifice stenosis by endoscopic laser ablation in dogs: 16 cases (2010–2014)
Bibliographic record
Abstract
OBJECTIVE To determine characteristics of and outcomes for dogs with congenital distal ureteral orifice stenosis (CDUOS) treated by cystoscopic-guided laser ablation (CLA). DESIGN Retrospective case series. ANIMALS 16 client-owned dogs with CDUOS treated by CLA at 2 veterinary hospitals between 2010 and 2014. PROCEDURES Medical records were reviewed and data collected regarding clinical findings, imaging results, surgery characteristics, treatment, and outcome. Follow-up information was collected from dog owners and referring veterinarians via standardized interview. RESULTS Dogs included 10 males and 6 females; median age was 11.5 months (range, 4 to 112 months). Labrador Retriever (n = 6; 3 males) was the most common breed. Intramural ectopic ureteral openings were identified at the site of stenosis in 15 dogs (18/20 stenotic ureteral openings). Treatment with CLA to enlarge and relocate the stenotic opening was successful in all dogs. Median duration of anesthesia and hospitalization was 105 minutes and 24 hours, respectively. No complications were noted. Fourteen dogs remained alive (2 lost to follow-up) during a median follow-up period of 14.5 months. Owners of 11 of 13 dogs reported improvement in their dog's quality of life after CLA. The treated ureteral orifice remained patent in the 2 dogs that were reimaged. CONCLUSIONS AND CLINICAL RELEVANCE CDUOS should be considered as a differential diagnosis for dogs with idiopathic distal ureteral obstruction, particularly young male Labrador Retrievers, and was most often associated with an intramural ectopic ureter in this study. Treatment with CLA was safe and effective for opening the ureteral orifice.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".