Serologic and Urinary PCR Survey of Leptospirosis in Healthy Cats and in Cats with Kidney Disease
Bibliographic record
Abstract
BACKGROUND: Although there is serologic evidence of exposure of cats to Leptospira spp., clinical disease is rarely reported in cats. OBJECTIVE: To compare the seropositivity and urinary polymerase chain reaction (PCR) status for Leptospira spp. between healthy (H) cats and cats with kidney disease (KD), to investigate the serovars potentially involved, and to evaluate potential risk factors. ANIMALS: Two hundred and forty client-owned cats. METHODS: Cats were prospectively recruited and classified based on physical examination, complete blood count, serum biochemistry profile, and urinalysis (125 H and 115 KD cats). Leptospira spp. serology (titers ≥1 : 100 considered positive) and urinary PCR were performed in all cats. Data assessing risk factors, obtained from a questionnaire, were evaluated using logistic regression models. RESULTS: Seropositivity for Leptospira spp. was statistically different between groups: 7.2% (9/125) and 14.9% (17/114) in the H and KD, respectively (P = .05). The proportion of PCR-positive cats was not. The most common serovars detected serologically were Pomona (n = 16) and Bratislava (n = 8). Risk factors for seropositivity included outdoor and hunting lifestyles (P = .03 and P < .001, respectively), the presence of another cat in the household (P < .01), and the sampling period, with the greatest number of cases identified between June and August (P =.02). CONCLUSIONS: Seropositivity was significantly greater in KD cats, suggesting that the role of Leptospira spp. in KD in cats should be further investigated. The detection of urinary shedding of leptospires in several cats identifies a potential role in the transmission of the organism.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".