Risk scores to predict decreased glomerular filtration rate at 10 years in an Asian general population

• Main Authors: Krittika Saranburut, Prin Vathesatogkit, Nisakron Thongmung, Anchalee Chittamma, Somlak Vanavanan, Tuangrat Tangstheanphan, Piyamitr Sritara, Chagriya Kitiyakara
• Format: Article
• Language: English
• Published: BMC 2017-07-01
• Series: BMC Nephrology
• Subjects: Asian; Cohort; Chronic kidney disease; EGAT; Population; Risk score
• Online Access: http://link.springer.com/article/10.1186/s12882-017-0653-z

Abstract Background Asians have among the highest prevalence of chronic kidney disease (CKD) or end-stage renal disease in the world. A risk score capable of identifying high risk individuals at the primary care level could allow targeted therapy to prevent future development of CKD. Risk scores for new CKD have been developed in US general populations, but the impact of various risks factors for development of CKD may differ in Asian subjects. In this study, we aimed to develop risk models and simplified risk scores to predict the development of decreased glomerular filtration rate (GFR) at 10 years in an Asian general population using readily obtainable clinical and laboratory parameters. Methods Employees of EGAT (The Electric Generating Authority of Thailand) were studied prospectively. Multivariable logistic regression models were used to assess risk factors and used to derive risk models and risk scores for developing decreased GFR at 10 years: Model 1 (Clinical only), Model 2 (Clinical + Limited laboratory tests), and Model 3 (Clinical + Full laboratory tests). The performance of the risk models or risk scores to predict incident cases with decreased GFR were evaluated by tests of calibration and discrimination. Results Of 3186 subjects with preserved GFR (eGFR ≥60) at baseline, 271 (8.5%) developed decreased GFR (eGFR < 60) at 10 years. Model 1 (Age, sex, systolic blood pressure, history of diabetes, and waist circumference) had good performance (χ2 = 9.02; AUC = 0.72). Model 2 (Age, Sex, systolic blood pressure, diabetes, glomerular filtration rate) had better discrimination (χ2 = 10.87, AUC = 0.79) than Model 1. Model 3 (Model 2+ Uric acid, Hemoglobin) did not provide significant improvement over Model 2. Based on these findings, simplified categorical risk scores were developed for Models 1 and 2. Conclusions Clinical or combined clinical and laboratory risk models or risk scores using tests readily available in a resource-limited setting had good accuracy and discrimination power to estimate the 10-year probability of developing decreased GFR in a Thai general population. The benefits of the risk scores in identifying high risk individuals in the Thai or other Asian communities for special intervention requires further studies.