By Lilian Anekwe
Primary care researchers have developed a tool to help GPs predict the risk of chronic kidney disease.
The team from the University of Nottingham – the same group who developed the QRISK score and several other risk assessment tools for diabetes and fracture risk – developed the Department of Health-backed tool using information commonly held in practice records.
The researchers used data from 368 general practices to develop the scores, then validated them used two separate cohorts, one of 188 practices and another of 364 practices.
Overall data from over 1.5 million men and women aged 35 to 74 were included in the cohort, with two separate equations used to predict the likelihood of either moderate-severe chronic kidney disease, or end-stage kidney disease, developing.
The final model, QKidney, includes 14 risk factors for moderate to severe chronic kidney disease in men and sixteen in women, and 13 for end-stage renal disease (see box).
The cut off for the top tenth for risk of moderate-severe CKD gives a five year risk threshold of 5.46% in men and 8.01% in women. For end stage kidney failure, the cut off for the top tenth gives a five year risk threshold of 0.49% in men and 0.36% in women.
Using the algorithms to identify the 10% of patients with the highest risk would be expected to identify approximately 457,700 patients over the next five years with moderate to severe CKD, and 25,900 with end-stage renal disease.
Lead researcher Professor Julia Hippisley-Cox, professor of clinical epidemiology and general practice at the University of Nottingham, told Pulse the DH’s renal tsar Dr Donal O’Donoghue had commissioned the development of the tool, in order to compliment the vascular checks programme and allow an easy way to collect data on the incidence of kidney disease.
‘My understanding is that when the National Programme for IT was started they built in some requirement that the system should be able to calculate risk of kidney disease. This does that, and supports the NICE guidance and National Service Framework on kidney disease.’
She added: ‘It has two main applications, in an individual patients and it can be applied across a whole GP database to identify at risk patients and target them for more intensive blood pressure control, for example. It can also have an alert in the system to warn against nephrotoxic drugs.
‘The accuracy is better than the other risk tools. This is the best risk tool we have done so far and it is pretty efficient and more effective than QRISK. It’s a way practices can focus their efforts on those patients in whom they are going to see the most gain.’
Treated hypertension is a risk factor for CKD Predictive risk factors in CKD algorithms
– Systolic blood pressure
– Rheumatoid arthritis
– Cardiovascular disease
– Treated hypertension
– Congestive cardiac failure
– Peripheral vascular disease
– NSAID use
– Family history of kidney disease.
*Systemic lupus erthematosus (SLE) and kidney stones were included in women.
+ The final model for end stage kidney failure did not include NSAID use.
Source: BMC Family Practice 2010, 11:49