Using demographic information and simple noninvasive medical characteristics from a national representative data set, Bang et al developed a numerical scoring system to predict prevalent chronic kidney disease. The scoring system was developed using the National Health and Nutrition Examination Survey and was validated independently in the Atherosclerosis Risk in Communities Study. Advanced age, female sex, history of hypertension, diabetes mellitus, proteinuria, or cardiovascular disease (including peripheral vascular disease and heart failure) were associated with a glomerular filtration rate less than 60 mL/min per 1.73 m2. After assigning points to each risk factor, a score of 4 or higher was chosen as a numeric cutpoint for screening based on the optimal balance of diagnostic characteristics (sensitivity of 92%, specificity of 68%, positive predictive value of 18%, and negative predictive value of 99%). This scoring system may be a useful tool for identifying individuals with a high likelihood of underlying kidney disease.