Algorithm identifies risk for chronic kidney disease

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A new algorithm based on a pair of population-based cardiovascular studies of 14,155 men and women helps predict which patients who have currently healthy kidneys are most likely to develop chronic kidney disease (CKD) within a decade.

At baseline, all participants were older than 45 years with an estimated glomerular filtration rate of >60 mL/min/1.73 m2. Overall, CKD developed in 1,605 subjects (11.3%) over nine years (Arch Intern Med. 2008;168:2466-2473) (subscription required).

A scoring system that included eight key risk factors—older age, anemia, female sex, hypertension, diabetes, peripheral vascular disease (PVD), and any history of heart failure or cardiovascular disease (CVD)—accurately predicted which of the older patients would proceed to CKD and which would not.

The model assigns 1, 2, or 3 points for having an age of 50-59, 60-69, or 70 years or more, respectively, and one point for each of the other seven factors. Patients who developed CKD tended to be almost five years older than those who did not. They also were more likely to be white and to have diabetes, PVD, hypertension, and/or a history of CVD. A score of >3 captured approximately 70% of incident cases and accurately predicted a 17% risk of developing CKD.

“We were able to validate the accuracy of the score across different cohorts, suggesting that it remains consistent in a variety of contexts,” the authors note. “Each of the eight components that make up the score is also easy to identify or quickly assess during a clinician-patient interview.”

“Not everyone with a score of 3 or higher will develop CKD,” the authors add. “They are just at a higher-than-average risk for kidney disease in the future.” Such a score should trigger a conversation encouraging patients to address their sugar intake, BP, and other cardiovascular risks.
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