We may soon have a safer approach to diagnosing and measuring the progression of chronic kidney disease following new research by the team from the Kolling Institute’s Renal Research Laboratory.
The condition is a global health issue, which now affects more than 13 per cent of the worldwide population.
Chronic kidney disease is a progressive disease that leads to end-stage kidney failure, which is fatal without dialysis or a kidney transplant.
Currently there are tests to detect advanced stages of the disease, but early detection is not possible.
Biopsies are performed to confirm a diagnosis of chronic kidney disease, but this approach brings with it inherent risks such as bleeding, pain and hospitalisation.
Encouragingly, researchers from the Kolling Institute and the University of New South Wales have now developed biomedical technology to provide accurate information around early diagnosis and prognosis, without the risks of an invasive biopsy procedure.
Head of the Kolling’s Renal Research Laboratory Professor Carol Pollock said this exciting new technology provides clear information about kidney pathology by examining kidney cells in urine.
“Having the ability to diagnose patients with a simple urine test represents a significant step forward for those with chronic kidney disease,” she said.
“Importantly, this enables early intervention and effective management.”
Project co-lead Associate Professor Sonia Saad said that being able to assess kidney pathology in a non-invasive way brings a host of benefits.
“It will enable clinicians to examine the effects of new drugs on the kidney and monitor kidney pathology over time. This will provide valuable information on the effectiveness of treatments.”
PhD student Dr Henry Wu has welcomed the chance to be involved in the project.
“It’s been rewarding to have been part of the development of this important new technology. We would like to see it applied broadly across clinical practice given the health and economic benefits of this approach,” he said.
The study is being led by Professor Pollock and Associate Professor Saad from the University of Sydney in collaboration with Professor Ewa Goldys and her team from the University of New South Wales.