BACKGROUND: Despite the wide availability and low cost of serum creatinine measurement, at-risk populations are not routinely tested for chronic kidney disease (CKD). METHODS: We used a cross-sectional analysis of a nationally representative, population-based survey to develop a system, SCORED (SCreening for Occult REnal Disease), that uses routinely available demographic and medical information to identify individuals with an increased likelihood of CKD. The analysis included 8530 adult participants in the National Health and Nutrition Examination Surveys conducted from 1999 to 2000 and 2001 to 2002 in the United States. Chronic kidney disease was defined as a glomerular filtration rate less than 60 mL/min per 1.73 m(2). Univariate and multivariate associations between a comprehensive set of risk factors and CKD were examined to develop a prediction model. The optimal characteristics of the model were examined with internal measures. External validation was performed using the Atherosclerosis Risk in Communities study. A model-based numeric scoring system was developed. RESULTS: Age (P<.001), female sex (P = .02), and various health conditions (hypertension [P = .03], diabetes [P = .03], and peripheral vascular disease [P = .008]; history of cardiovascular disease [P = .001] and congestive heart failure [P = .04]; and proteinuria [P<.001] and anemia [P = .003]) were associated with CKD. The multivariate model was well validated in the internal and external data sets (area under the receiver operating characteristic curve of 0.88 and 0.71, respectively). A score of 4 or greater was chosen by internal validation as a cutoff point for screening based on the diagnostic characteristics (sensitivity, 92%; specificity, 68%; positive predictive value, 18%; and negative predictive value, 99%). CONCLUSION: This scoring system, weighted toward common variables associated with CKD, may be a useful tool to identify individuals with a high likelihood of occult kidney disease.
BACKGROUND: Despite the wide availability and low cost of serum creatinine measurement, at-risk populations are not routinely tested for chronic kidney disease (CKD). METHODS: We used a cross-sectional analysis of a nationally representative, population-based survey to develop a system, SCORED (SCreening for Occult REnal Disease), that uses routinely available demographic and medical information to identify individuals with an increased likelihood of CKD. The analysis included 8530 adult participants in the National Health and Nutrition Examination Surveys conducted from 1999 to 2000 and 2001 to 2002 in the United States. Chronic kidney disease was defined as a glomerular filtration rate less than 60 mL/min per 1.73 m(2). Univariate and multivariate associations between a comprehensive set of risk factors and CKD were examined to develop a prediction model. The optimal characteristics of the model were examined with internal measures. External validation was performed using the Atherosclerosis Risk in Communities study. A model-based numeric scoring system was developed. RESULTS: Age (P<.001), female sex (P = .02), and various health conditions (hypertension [P = .03], diabetes [P = .03], and peripheral vascular disease [P = .008]; history of cardiovascular disease [P = .001] and congestive heart failure [P = .04]; and proteinuria [P<.001] and anemia [P = .003]) were associated with CKD. The multivariate model was well validated in the internal and external data sets (area under the receiver operating characteristic curve of 0.88 and 0.71, respectively). A score of 4 or greater was chosen by internal validation as a cutoff point for screening based on the diagnostic characteristics (sensitivity, 92%; specificity, 68%; positive predictive value, 18%; and negative predictive value, 99%). CONCLUSION: This scoring system, weighted toward common variables associated with CKD, may be a useful tool to identify individuals with a high likelihood of occult kidney disease.
Authors: A R Pradeep; Rahul Kathariya; P Arjun Raju; R Sushma Rani; Anuj Sharma; N M Raghavendra Journal: Int Urol Nephrol Date: 2011-06-03 Impact factor: 2.370
Authors: Andrew D Rule; Hatem Amer; Lynn D Cornell; Sandra J Taler; Fernando G Cosio; Walter K Kremers; Stephen C Textor; Mark D Stegall Journal: Ann Intern Med Date: 2010-05-04 Impact factor: 25.391
Authors: Pankti A Gheewala; Syed Tabish R Zaidi; Matthew D Jose; Luke Bereznicki; Gregory M Peterson; Ronald L Castelino Journal: J Nephrol Date: 2017-02-08 Impact factor: 3.902
Authors: Andrew D Rule; Kent R Bailey; Gary L Schwartz; Sundeep Khosla; John C Lieske; L Joseph Melton Journal: Kidney Int Date: 2009-01-28 Impact factor: 10.612