Computed tomographic features of canine intramural ureteral stenosis in three dogs.
Bibliographic record
Abstract
Introduction<br/>Stenosis of the intramural portion of the ureter (StIMU) has rarely been reported in dogs1,2 but has been observed in our excretory urinary computed tomography (EUCT) caseload. Purpose of this study was to investigate the prevalence and EUCT features of StIMU in dogs.<br/><br/>Methods<br/>Single institutional archives were searched for dogs with EUCT-identified, surgically confirmed StIMU. The urogenital tract was assessed for size, shape, mineralisation, excretion and peristalsis in EUCT.<br/><br/> Results<br/>Two-hundred-ninety-three EUCT studies were identified. Three dogs met the inclusion criteria, a 1-year-old male Miniature-Schnauzer-Poodle cross with urinary incontinence (case 1), a 3-month-old male Newfoundland dog with haematuria (case 2) and a 4-year-old male Newfoundland dog with pollakiuria (case 3). EUCT examination revealed renal pyelectasia, hydroureter and an abnormal intramural portion of the ureter. Intramural ureteral abnormalities included lack of peristaltic distension, ectopia and aberrant lateral course. Surgical exploration revealed bilateral ureteral stenosis and unilateral ectopia (case 1), bilateral ureteral stenosis and ectopia (case 2) and unilateral stenosis without ectopia (case 3).<br/><br/>Discussion<br/>Stenosis of the intramural portion of the ureter is rarely seen, with young male dogs overrepresented, and should be included in the differential diagnosis of hydroureter.1,2,3 This may represent a congenital malformation or a fibrotic inflammatory reaction but is not necessarily associated with ureteral ectopia. Concurrent urinary tract infection needs to be considered as potential cause or result of StIMU. EUCT may be of value for treatment planning. Further investigation for breed predisposition in Newfoundland dogs is warranted.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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".