Prevalence and risk factors for urinary incontinence in bitches five years after ovariohysterectomy
Bibliographic record
Abstract
ABSTRACT Ovariohysterectomy (OHE) is the most performed elective surgery in veterinary medicine. Although this procedure brings benefits both to the animal and public health, acquired urinary incontinence is a possible complication resultant from it. The aim of this study was to determine the prevalence of urinary incontinence and evaluate size, breed, and time of surgery as risk factors in a population of spayed female dogs in the Hospital de Clínicas Veterinárias da Universidade Federal do Rio Grande do Sul, in the year of 2013, through the use of a multiple-choice screening instrument. Identified estimated prevalence was 11.27% and main risk factors were as follows: large size (OR = 7.12 IC95% = 1.42 - 35.67), Rottweiler breed (OR = 8.92; IC95% = 5.25 - 15.15), Pit-bull breed (OR = 4.14; IC95% = 2.19 - 7.83), and Labrador breed (OR = 2.73; IC95% = 1.53 - 4.87). Time of surgery was not considered a risk factor for urinary incontinence in this population (OR = 1.45; IC95% = 0.86 - 2.40). Even though most owners reported a small impact on their relationship with the animal, urinary incontinence hazard should be addressed before spaying.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.315 | 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 teacher head, 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".