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Journal of the American Veterinary Medical Association · 2024

Insights on feline infectious peritonitis risk factors and sampling strategies from polymerase chain reaction analysis of feline coronavirus in large-scale nationwide submissions.

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Barua Subarna, Sarkar Shila, Chenoweth Kelly, Johnson Calvin, Delmain Diane, Wang Chengming

Аннотация

OBJECTIVE: This nationwide study aimed to investigate risk factors associated with FIP and determine optimal sample submission strategies for its diagnosis.

METHODS: A total of 14,035 clinical samples from cats across the US were analyzed by means of reverse transcriptase quantitative PCR to detect replicating feline coronavirus (FCoV). χ2 and logistic regression analyses were conducted to assess the association between FCoV detection rates and risk factors such as age, gender, breed, and types of submitted samples.

RESULTS: Higher FCoV detection rates were observed in younger cats, particularly those aged 0 to 1 year, and in male cats. Purebred cats, notably British Shorthairs [OR: 2.81; P < .001], showed a higher incidence of FCoV infection than other cats. Peritoneal fluid (OR, 7.51; P < .001) exhibited higher FCoV detection rates than other samples, while lower rates were seen in blood samples (OR, 0.08; P < .001) than in other samples. High FCoV detection rates were found in urine, kidney, and lymph node samples.

CONCLUSIONS: The study identified significant risk factors associated with FIP. Optimal sample submission strategies, particularly emphasizing the use of peritoneal fluid, kidney, and lymph node, were identified to improve FIP detection rates. Urine yielded a relatively high frequency of infection and viral loads compared with most other samples.

CLINICAL RELEVANCE: Understanding the risk factors and optimizing sample selection for FIP diagnosis can aid in the early detection and management of the disease, ultimately improving outcomes for affected cats. These findings contribute valuable insights to FIP epidemiology and underscore the importance of continued research to enhance diagnostic strategies and disease management approaches.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты