Jessica Parsh1, Milan Seth2, Herbert Aronow3, Simon Dixon4, Michael Heung5, Roxana Mehran6, Hitinder S Gurm7. 1. Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan. 2. Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan. 3. Michigan Heart and Vascular Institute, St. Joseph Mercy Hospital, Ann Arbor, Michigan. 4. Department of Cardiovascular Medicine, Beaumont Hospital, Royal Oak, Michigan. 5. Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, Michigan. 6. The Zena and Michael A. Wiener Cardiovascular Institute, Mount Sinai Medical Center, New York, New York. 7. Department of Internal Medicine, Division of Cardiovascular Medicine, University of Michigan, Ann Arbor, Michigan; VA Ann Arbor Healthcare System, Ann Arbor, Michigan. Electronic address: hgurm@med.umich.edu.
Abstract
BACKGROUND: Multiple equations exist to estimate glomerular filtration rate (GFR); however, there is no consensus on which is superior for risk classification in patients with chronic kidney disease (CKD) undergoing percutaneous coronary intervention (PCI). OBJECTIVES: The goals of this study were to identify which equation to estimate GFR is superior for predicting adverse outcomes after PCI and to examine how equation selection would impact drug-dosing recommendations. METHODS: Estimated GFR (eGFR) was calculated with the Cockcroft-Gault, Modification of Diet in Renal Disease Study (MDRD), and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations for 128,805 patients undergoing PCI in the state of Michigan. Agreement between patient pre-PCI eGFR estimates and resultant CKD stage classifications, their ability to discriminate post-procedural in-hospital clinical outcomes, and the impact of equation choice on dosing recommendations for commonly used antiplatelet and antithrombotic medications were investigated. RESULTS: CKD-EPI best discriminated post-PCI mortality by receiver operator characteristic analysis. There was wide variability in eGFR, which persisted after grouping by CKD stages. Reclassification by CKD-EPI resulted in net reclassification index improvement for acute kidney injury and new requirement for dialysis. Equation choice affected drug-dosing recommendations, with the formulas agreeing for only 50.3%, 40.0%, and 34.3% of potentially impacted patients for eGFR cutoffs of <60, <50, and <30 ml/min/1.73 m(2), respectively. CONCLUSIONS: Different eGFR equations result in CKD stage reclassification that has major clinical implications for predicting adverse outcomes after PCI and drug-dosing recommendations. Our results support the use of CKD-EPI for risk stratification among patients undergoing PCI.
BACKGROUND: Multiple equations exist to estimate glomerular filtration rate (GFR); however, there is no consensus on which is superior for risk classification in patients with chronic kidney disease (CKD) undergoing percutaneous coronary intervention (PCI). OBJECTIVES: The goals of this study were to identify which equation to estimate GFR is superior for predicting adverse outcomes after PCI and to examine how equation selection would impact drug-dosing recommendations. METHODS: Estimated GFR (eGFR) was calculated with the Cockcroft-Gault, Modification of Diet in Renal Disease Study (MDRD), and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations for 128,805 patients undergoing PCI in the state of Michigan. Agreement between patient pre-PCI eGFR estimates and resultant CKD stage classifications, their ability to discriminate post-procedural in-hospital clinical outcomes, and the impact of equation choice on dosing recommendations for commonly used antiplatelet and antithrombotic medications were investigated. RESULTS: CKD-EPI best discriminated post-PCI mortality by receiver operator characteristic analysis. There was wide variability in eGFR, which persisted after grouping by CKD stages. Reclassification by CKD-EPI resulted in net reclassification index improvement for acute kidney injury and new requirement for dialysis. Equation choice affected drug-dosing recommendations, with the formulas agreeing for only 50.3%, 40.0%, and 34.3% of potentially impacted patients for eGFR cutoffs of <60, <50, and <30 ml/min/1.73 m(2), respectively. CONCLUSIONS: Different eGFR equations result in CKD stage reclassification that has major clinical implications for predicting adverse outcomes after PCI and drug-dosing recommendations. Our results support the use of CKD-EPI for risk stratification among patients undergoing PCI.
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