Positive Predictive Value of a Single Assessment of Estimated GFR in the Diagnosis of Chronic Kidney Disease. Issue 6 (June 2016) - Satchidanand, Nikhil; Withiam-Leitch, Matthew; Dickinson, Miriam; Pace, Wilson; Bublitz-Emsermann, Caroline; Allen, Geoffrey M.; Yang, Min; Vassalotti, Joseph; Arora, Pradeep; Glasgow, Patrick; Fox, Chester
Abstract : Objectives: The positive predictive value (PPV) of a single assessment of estimated glomerular filtration rate (eGFR) in the diagnosis of chronic kidney disease (CKD) is not known. Our objective was to determine the PPV of a single assessment of eGFR among adults with at least one eGFR <60 mL/min in their lifetime, using the Distributed Area Research and Therapeutics Network CKD natural history dataset. Methods: In all, 47, 104 adults who were cared for by 113 practices in the United States were included. Proportions of patients in eGFR categories at baseline were calculated using the following categories: <15 mL/min, 15 to 29.99 mL/min, 30 to 44.99 mL/min, and 45 to 59.99 mL/min. Comparisons were then made between the baseline and the endpoint to identify patients who had a follow-up eGFR that remained at <60 mL/min. The proportions of patients in each eGFR category were compared baseline to endpoint using cross-tabulations. To test the proposed cutpoint, the proportions of patients who had an eGFR that remained at <60 mL/min were measured, using the cutpoints that included the highest cumulative proportion of patients. The sensitivity and specificity of that cutpoint were calculated. Results: A cutpoint of <45 mL/min was identified, yielding a PPV of 93% with a sensitivity of 28% and a specificity of 94%. Conclusions: A valid cutpoint to screen for CKD was identified. This cutpoint may prove important to early screening for CKD while reducing the burden on the healthcare system and patients suspected of having CKD. Abstract : The objective of this study was to determine the positive predictive value of a single assessment of glomerular filtration rate in the diagnosis of chronic kidney disease. Using a large, national primary care dataset, the authors set out to determine the utility of this assessment in the context of diagnosis and classification of chronic kidney disease.