Software predicts kidney disease risk

A study of the Qkidney risk algorithm has shown that it is highly accurate in identifying patients most under threat. The Qkidney risk calculator will allow doctors to decide which patients need testing for the disease or could benefit from assessment, closer monitoring or intervention to reduce their risk.

Chronic Kidney Disease (CKD) is a significant cause of disease and mortality. It is associated with increased risk of death from cardiovascular disease, as well as from End Stage Kidney Failure, which can require dialysis or transplantation.

While the prevention of Chronic Kidney Disease is a key component of the Department of Health NHS Health Checks programme, previously there have been no tools able to identify systematically patients at high risk of moderate or severe Chronic Kidney Disease.

Julia Hippisley-Cox, professor of Clinical Epidemiology, and Carol Coupland, associate professor in medical statistics at Nottingham University, in collaboration with Clinrisk, developed the software to help predict which patients need more detailed assessment, closer monitoring or interventions.

Prof Hippisley-Cox said that the software will identify those most likely to gain from interventions, while reassuring those at low risk.

To create the software, the researchers studied data collected from 364 general practices on 1.57 million patients aged 35-74 years. They followed these patients over a seven-year period and identified factors that predicted increased risk of Chronic Kidney Disease, such as age, ethnicity, deprivation, smoking status, obesity, blood-pressure levels, family history of kidney disease, use of painkillers and other medical conditions such as diabetes, rheumatoid arthritis, health failure and heart disease.

They then incorporated these factors into the algorithm to calculate an individual’s risk of developing moderate or severe Chronic Kidney Disease over the next five years. As part of the research, they successfully validated the algorithm in two separate groups of patients.

A web-based calculator that implements the algorithm can be found at www.qkidney.org. While the calculator has been designed primarily for use by clinicians, it can also be used by patients.

Software-development kits are available so that system suppliers can easily integrate the calculator algorithm into GP, hospital or pharmacy clinical computer systems to alert doctors to patients who might be at risk of developing Chronic Kidney Disease and might need closer monitoring.

Qkidney works well alongside QRISK2 and QDScore − algorithms that predict risk of heart disease (qrisk.org) and diabetes (qdscore.org), respectively.