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AI developed to detect leptospirosis
"My hope is that this technology will be able to recognize cases of leptospirosis in near real time" - Dr Krystle Reagan.

Scientists at UC Davis created the model for early detection.

Scientists and veterinary surgeons at the University of California, Davis (UC Davis) have created an artificial intelligence model for early detection of leptospirosis.

Caused by dogs drinking water contaminated with Leptospira bacteria, leptospirosis ultimately leads to kidney failure, liver disease and severe bleeding in the lungs. Early detection of the disease is vital to give dogs the greatest chance of survival and recovery. 

Explaining the need for a better detection method, lead author Dr Krystle Reagan said: “Traditional testing for Leptospira lacks sensitivity early in the disease process.

“Detection also can take more than two weeks because of the need to demonstrate a rise in the level of antibodies in a blood sample. 

“Our AI model eliminates those two roadblocks to a swift and accurate diagnosis.”

Researcher used historical data of patients at the UC Davis Veterinary Medical Teaching Hospital that had been tested for leptospirosis. Routinely collected blood samples from 413 dogs was used to train the AI prediction model. 

Of the 53 dogs brought in for suspected leptospirosis over the next year, the AI model correctly identified all nine dogs that were positive for leptospirosis. Of the 44 leptospirosis negative dogs, the AI model correctly identified 90 per cent. 

Dr Reagan commented: “My hope is this technology will be able to recognize cases of leptospirosis in near real time, giving clinicians and owners important information about the disease process and prognosis.

“As we move forward, we hope to apply AI methods to improve our ability to quickly diagnose other types of infections.”

As a zoonotic disease, leptospirosis can transfer from animals to humans, and is difficult to diagnose in humans. The researcher hope that the developed technology will be able to be used in human medicine.

The research for this project has been published in the Journal of Veterinary Diagnostic Investigation.

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Practices urged to audit neutering data

News Story 1
 RCVS Knowledge has called on vet practices to audit their post-operative neutering outcomes.

It follows the release of the 2024 NASAN benchmarking report, which collates data from neutering procedures performed on dogs, cats and rabbits.

The benchmarking report enables practices in the UK and Ireland to compare their post-operative outcomes to the national average. This includes the rate of patients lost to follow-up, which in 2024 increased to 23 per cent.

Anyone from the practice can submit the data using a free template. The deadline for next report is February 2026.

Visit the RCVS Knowledge website to complete an audit. 

Click here for more...
News Shorts
New guidance for antibiotic use in rabbits

New best practice guidance on the responsible use of antibiotics in rabbits has been published by the BSAVA in collaboration with the Rabbit Welfare Association & Fund (RWA&F).

The guidance is free and has been produced to help veterinary practitioners select the most appropriate antibiotic for rabbits. It covers active substance, dose and route of administration all of which are crucial factors when treating rabbits owing to the risk of enterotoxaemia.

For more information and to access the guide, visit the BSAVALibrary.