Background We compared different methods of estimated glomerular filtration rate (eGFR) and their association with cardiovascular death and major bleeding in 14 980 patients with atrial fibrillation in the ARISTOTLE (Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation) trial. Methods and Results eGFR was calculated using equations based on creatinine (Cockcroft-Gault, Modification of Diet in Renal Disease, and Chronic Kidney Disease Epidemiology Collaboration [CKD-EPI]) and/or cystatin C (CKD-EPI and CKD-EPI). These 5 eGFR equations, as well as the individual variables that are used in these equations, were assessed for correlation and discriminatory ability for cardiovascular death and major bleeding. The median age was 70.0 years, and 35.6% were women. The median eGFR was highest with Cockcroft-Gault (74.1 mL/min) and CKD-EPI (74.2 mL/min), and lowest with Modification of Diet in Renal Disease (66.5 mL/min). Correlation between methods ranged from 0.49 (Cockroft-Gault and CKD-EPI) to 0.99 (Modification of Diet in Renal Disease and CKD-EPI). Among the eGFR equations, those based on cystatin C yielded the highest C indices for cardiovascular death and major bleeding: 0.628 (CKD-EPI) and 0.612 (CKD-EPI), respectively. A model based on the variables within the different eGFR equations (age, sex, weight, creatinine, and cystatin C) yielded the highest discriminatory value for both outcomes, with a C index of 0.673 and 0.656, respectively. Conclusions In patients with atrial fibrillation on anticoagulation, correlation between eGFR calculated using different methods varied substantially. Cystatin C-based eGFRs seem to provide the most robust information for predicting death and bleeding. A model based on the individual variables within the eGFR equations, however, provided the highest discriminatory value. Our findings may help refine risk stratification in patients with atrial fibrillation and define how renal function should be determined in future atrial fibrillation studies. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT00412984.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7726979 | PMC |
http://dx.doi.org/10.1161/JAHA.120.017155 | DOI Listing |
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