Presentation, diagnosis, and outcomes of cats undergoing surgical treatment of ectopic ureters
Bibliographic record
Abstract
OBJECTIVE: To describe the signalment, treatment, complications, and outcomes of cats treated surgically for ectopic ureters. STUDY DESIGN: Retrospective, multi-institutional study. ANIMALS: Twelve client-owned cats. METHODS: Medical records of cats diagnosed with unilateral or bilateral ectopic ureters were reviewed and analyzed. Data reported included signalment, clinical signs, diagnostics, open celiotomy, or cystoscopic surgical interventions, and outcomes. RESULTS: Seven of the 12 cats in the study population were female or female spayed and the median age at time of presentation was 4 years, with an interquartile range (IQR) of 6 months-14 years. Presurgical diagnostic imaging diagnosed ectopic ureters by abdominal ultrasound (8/10), contrast enhanced computed tomography (3/3), fluoroscopic urography (3/4), or cystoscopy (6/7). Eight of 12 cats had extramural ectopic ureters and six cats were affected bilaterally. Eight affected cats underwent ureteroneocystostomy, one cat underwent neoureterostomy, two cats underwent cystoscopic laser ablation, and one cat underwent nephroureterostomy. Immediate postoperative complications occurred in three cats; one cat required additional surgical intervention. Short-term complications occurred in three cats, and long-term complications in two cats. All cats that underwent surgical or cystoscopic intervention had improvement of their urinary incontinence scores, with complete resolution in 11 cats. CONCLUSION: Surgical correction of ectopic ureters in cats is associated with good long-term outcomes. Ectopic ureters in cats are commonly extramural and bilateral. Postoperative outcomes were acceptable and there were few postoperative complications, with varying forms of surgical correction. CLINICAL SIGNIFICANCE: Ectopic ureters in cats are rare but urinary incontinence can be corrected or improved successfully with surgery.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".