Derivation and validation of a clinical index for prediction of rapid progression of kidney dysfunction
From the 1Department of Medicine, Division of Nephrology, 2Department of Community Health Sciences, 3Alberta Kidney Disease Network, 4Department of Medicine, Division of General Internal Medicine, and 5Centre for Health and Policy Studies, all University of Calgary, Calgary, Alberta, Canada
Address correspondence to Dr B.R. Hemmelgarn, Division of Nephrology, Foothills Medical Center, 1403 29th St NW, Calgary Alberta, T2N 2T9, Canada. email: brenda.hemmelgarn{at}calgaryhealthregion.ca
Received 18 June 2006 and in revised form 6 November 2006
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Abstract |
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Background: Chronic kidney disease is common among the elderly, and these patients are at risk of progressive kidney dysfunction.
Aim: To develop an index to predict rapid progression of kidney dysfunction.
Design: Community-based cohort divided into derivation (n = 6789) and validation (n = 3395) subsets.
Methods: We identified 10 184 subjects aged 
66 years from computerized laboratory data. Prescription drug data was used to define disease categories and medication exposure, and an index for predicting rapid progression of kidney dysfunction (25% decline in glomerular filtration rate over a 2-year period) was obtained from a logistic regression model in the derivation cohort. The risk score for each subject was calculated by summing the component variables together, which were subsequently categorized into five risk classes.
Results: Five predictors of rapid progression were identified: age >75 years, cardiac disease, diabetes mellitus, gout, and use of anti-emetic medications. Rates of rapid progression for risk classes I through V were 8.6%, 10.9%, 13.9%, 15.6%, and 24.1%, respectively, for the derivation cohort, and 8.4%, 11.6%, 15.5%, 17.3%, 21.9%, respectively, for the validation cohort. The risk index distinguished between low and high risk of rapid progression, with a 2.5-fold greater risk for the highest, compared to the lowest, risk decile.
Discussion: Readily available clinical data can be used to identify most elderly at risk of rapid progression of kidney dysfunction. This simple index could help clinicians to identify patients at risk, and implement strategies to slow the progression of kidney dysfunction.