Risk factors associated with struvite urolithiasis in dogs evaluated at general care veterinary hospitals in the United States
Bibliographic record
Abstract
OBJECTIVE: To identify factors associated with development of struvite urolithiasis in dogs evaluated at general care veterinary hospitals in the United States. DESIGN: Retrospective case-control study. ANIMALS: 508 dogs with a first-time diagnosis of struvite urolithiasis and 7,135 control dogs. PROCEDURES: Electronic medical records of all dogs evaluated at 787 general care veterinary hospitals in the United States between October 2007 and December 2010 were reviewed to identify dogs that developed struvite urolithiasis and 2 groups of control dogs with no history of urolithiasis. Information extracted included diet, age, sex, neuter status, breed size category, hospital location, and date of diagnosis. Urinalysis results, urolith composition, and other disease conditions were recorded if applicable. Potential risk factors were assessed with univariable and multivariable regression analysis. RESULTS: Toy- or small-sized breeds had significantly greater odds of struvite urolithiasis, compared with medium- or large-sized breeds. Neutering significantly increased the odds of this outcome in females only; sexually intact females were more likely to develop struvite urolithiasis than were sexually intact males, but only up to 5 years of age. Urinary factors significantly associated with the outcome were basic (vs acidic) pH, presence of RBCs or WBCs, protein concentration > 30 mg/dL, and ketone concentration ≥ 5 mg/dL. CONCLUSIONS AND CLINICAL RELEVANCE: Evaluation of demographic characteristics and urinalysis results may be useful in the early identification of struvite urolithiasis in dogs. Periodic urinalysis in dogs is recommended because of the potential health impact of a late diagnosis of urolithiasis.
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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 | 0.000 |
| 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".