Signalment Changes in Canine Leptospirosis between 1970 and 2009
Bibliographic record
Abstract
BACKGROUND: Previous studies have identified large breed, male, outdoor dogs of herding or working groups to be at increased risk for Leptospira infection. Exposure risk factors may change over time, altering the signalment of dogs most commonly diagnosed with leptospirosis. OBJECTIVES: The objectives of this study were to evaluate possible signalment changes by decade in canine leptospirosis cases diagnosed at university veterinary hospitals in the United States and Canada using reports to the Veterinary Medical DataBase (VMDB) over a 40-year period (1970-2009). ANIMALS: One thousand and ninety-one dogs with leptospirosis diagnosed among 1,659,146 hospital visits. METHODS: Hospital prevalence of leptospirosis by decade was determined by age, sex, weight, and breed groups. Multivariable logistic regression models were created to evaluate the association between variables and the odds of disease for each decade. RESULTS: Veterinary Medical DataBase hospital prevalence of leptospirosis in dogs, after a marked decrease in the 1970s and low rates in the 1980s, began increasing in the 1990s. Hospital prevalence significantly increased in dogs between 2 and 9.9 years of age (P < .05) and in male dogs (P < .05) in each decade since the 1980s. Among weight groups in the most recent decade (2000-2009), dogs weighing <15 pounds had the greatest odds of being diagnosed with leptospirosis (P = .003). CONCLUSIONS AND CLINICAL IMPORTANCE: Hospital prevalence rates by age, weight, sex, and breed groups differed by decade. These changes may reflect changes in exposure risk, Leptospira vaccination practices for dogs, or both.
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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 | 0.004 |
| 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 | 0.001 | 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".