AI tool predicts kidney disease in cats two years before traditional diagnosis

Chronic kidney disease (CKD) is the number one cause of death for cats over five and affects 30-40 percent of all cats over the age of 10. (pxfuel)

​Good news, cat owners! There is now a new diagnostic tool that can predict the deadly chronic kidney disease (CKD) in cats before it's too late to make intervention and treatment.

Antech Diagnostics, a veterinary laboratory owned by Mars Petcare, has launched RenalTech that allows the accurate prediction of the disease in cats. The RenalTech™ tool is now available to veterinarians in the US. Veterinarians will now be able to create tailored proactive care plans for cats and work to delay the onset of CKD.

Chronic kidney disease (CKD) is the number one cause of death for cats over five and affects 30-40 percent of all cats over the age of 10. It is a highly complex disease that historically has been difficult to diagnose. The current methods are only able to confirm the disease in a pet once significant and irreversible kidney damage has occurred, which makes any intervention and treatment challenging.

The RenalTech™ tool was developed from a research project led by Richard Bradley at WALTHAM that was published in Journal of Veterinary Internal Medicine (Bradley et al., 2019). The project involved mining the veterinary records of more than 150,000 cats that visited BANFIELD® Pet Hospitals to create a biomarker of six common feline health measurements (creatinine, blood urea nitrogen, white blood cell count, urine specific gravity, urine protein, urine pH–along with approximate age) to predict CKD up to two years before traditional diagnosis. Access to large data sets allows data scientists to use computers to search for patterns that can predict an event occurring in the future. In this case, historic health records spanning 20 years from 750,000 veterinary hospital visits for over 150,000 cats were examined to hunt for changes that were characteristic of the pets that were known to go on to develop CKD, when compared to those who remained healthy. This approach also allows for these predictive patterns to be tested to determine how accurate the diagnosis is. For the RenalTech™ tool, they found the accuracy was greater than 95 percent.

Stages of CKD in cats.

“When we looked at the historic data from thousands of pets, it was clear that the data had a story to tell” explains Richard Bradley, author and Data Science Technical Lead at WALTHAM. There were subtle changes in several of the blood and urine parameters long before disease was diagnosed, but they were different from pet to pet. Machine learning allowed us to imprint all the subtleties of the changes in a computer algorithm, which was then able to spot the small abnormalities and make a robust prediction.”

A promising future for preventive veterinary medicine
“This is a paradigm shifting moment for veterinary medicine” says Jonathan Elliott, MA, Vet MB, PhD, Cert SAC, Dip ECVPT, MRCVS and Vice Principal for Research and Innovation at the University of London Royal Veterinary College and partner in the development of the tool. “The ability to use artificial intelligence on data collected in practice as part of routine health screens to address chronic kidney disease well before the disease becomes clinically apparent gives us an opportunity to leverage best practice medicine for cats not previously available to veterinarians. It’s also exciting that we were able to move so quickly from publication in the Journal of Veterinary Internal Medicine to making the tool available in practice.”

The development of RenalTech™ tool signals the beginning of a new wave of predictive diagnostics. There are many more diseases and conditions that in future may be managed proactively, allowing veterinarians and pet owners together extend the health span of their pets.