Evaluation of risk factors associated with suture-nidus cystoliths in dogs and cats: 176 cases (1999–2006)
Bibliographic record
Abstract
OBJECTIVE: To characterize and evaluate risk factors for suture-associated cystoliths in dogs and cats. DESIGN: Retrospective case-control study. Animals-163 dogs and 13 cats with suture-associated cystoliths and 326 control dogs and 26 control cats with non-suture-associated cystoliths. PROCEDURES: Submissions to the Canadian Veterinary Urolith Centre received from 1999 to 2006 were reviewed. Case dogs and cats had cystoliths associated with visible suture or with hollow, cylindrical channels or suture knot impressions consistent with dissolved suture. Control dogs and cats had at least a single recurrent non-suture-associated cystolith submitted closest in time to the sample case. Associations among cystolith composition, recurrence times, sex, age, and breed were evaluated. RESULTS: Cases consisted of 92 dogs and 7 cats with visible suture and 71 dogs and 6 cats with dissolved suture. Suture-associated cystoliths represented 0.6% of canine cystoliths, 9.4% of recurrent canine cystoliths, 0.17% of feline cystoliths, and 4% of recurrent feline cystoliths. Sexually intact and neutered males were at increased odds of suture-associated cystoliths, relative to spayed female dogs. Shih Tzus, Lhasa Apsos, and Pomeranians were significantly predisposed to form suture-associated cystoliths. In dogs, compound suture-associated cystoliths were significantly more likely than other cystolith types (OR, 8.6). Dogs with suture-associated cystoliths had significantly shorter recurrence times than did control dogs. CONCLUSIONS AND CLINICAL RELEVANCE: Suture remnants in the bladder have an important role in recurrent cystolithiasis in dogs. Identification of risk factors is important for avoiding recurrence of iatrogenic cystoliths.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".