Nadim Mahmud1,2,3,4, Sumeet K Asrani5, Peter P Reese6,7,8, David E Kaplan9,10, Tamar H Taddei11,12, Mitra K Nadim13, Marina Serper9,10,6. 1. Division of Gastroenterology and Hepatology, University of Pennsylvania Perelman School of Medicine, 3400 Civic Center Boulevard, 4th Floor, South Pavilion, Philadelphia, PA, 19104, USA. nadim@pennmedicine.upenn.edu. 2. Gastroenterology Section, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA. nadim@pennmedicine.upenn.edu. 3. Leonard David Institute of Health Economics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. nadim@pennmedicine.upenn.edu. 4. Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA. nadim@pennmedicine.upenn.edu. 5. Baylor University Medical Center, Baylor Scott and White, Dallas, TX, USA. 6. Leonard David Institute of Health Economics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. 7. Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA. 8. Renal-Electrolyte and Hypertension Division, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. 9. Division of Gastroenterology and Hepatology, University of Pennsylvania Perelman School of Medicine, 3400 Civic Center Boulevard, 4th Floor, South Pavilion, Philadelphia, PA, 19104, USA. 10. Gastroenterology Section, Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA. 11. Division of Digestive Diseases, Yale University School of Medicine, New Haven, CT, USA. 12. VA Connecticut Healthcare System, West Haven, CT, USA. 13. Division of Nephrology and Hypertension, Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Abstract
BACKGROUND: Accuracy of glomerular filtration rate estimating (eGFR) equations has significant implications in cirrhosis, potentially guiding simultaneous liver kidney allocation and drug dosing. Most equations adjust for Black race, partially accounted for by reported differences in muscle mass by race. Patients with cirrhosis, however, are prone to sarcopenia which may mitigate such differences. We evaluated the association between baseline eGFR and incident acute kidney injury (AKI) in patients with cirrhosis with and without race adjustment. METHODS: We conducted a retrospective national cohort study of veterans with cirrhosis. Baseline eGFR was calculated using multiple eGFR equations including Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), both with and without race adjustment. Poisson regression was used to investigate the association between baseline eGFR and incident AKI events per International Club of Ascites criteria. RESULTS: We identified 72,267 patients with cirrhosis, who were 97.3% male, 57.8% white, and 19.7% Black. Over median follow-up 2.78 years (interquartile range 1.22-5.16), lower baseline eGFR by CKD-EPI was significantly associated with higher rates of AKI in adjusted models. For all equations this association was minimally impacted when race adjustment was removed. For example, removal of race adjustment from CKD-EPI resulted in a 0.1% increase in the association between lower eGFR and higher rate of AKI events per 15 mL/min/1.73 m2 change (p < 0.001). CONCLUSIONS: Race adjustment in eGFR equations did not enhance AKI risk estimation in patients with cirrhosis. Further study is warranted to assess the impacts of removing race from eGFR equations on clinical outcomes and policy.
BACKGROUND: Accuracy of glomerular filtration rate estimating (eGFR) equations has significant implications in cirrhosis, potentially guiding simultaneous liver kidney allocation and drug dosing. Most equations adjust for Black race, partially accounted for by reported differences in muscle mass by race. Patients with cirrhosis, however, are prone to sarcopenia which may mitigate such differences. We evaluated the association between baseline eGFR and incident acute kidney injury (AKI) in patients with cirrhosis with and without race adjustment. METHODS: We conducted a retrospective national cohort study of veterans with cirrhosis. Baseline eGFR was calculated using multiple eGFR equations including Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), both with and without race adjustment. Poisson regression was used to investigate the association between baseline eGFR and incident AKI events per International Club of Ascites criteria. RESULTS: We identified 72,267 patients with cirrhosis, who were 97.3% male, 57.8% white, and 19.7% Black. Over median follow-up 2.78 years (interquartile range 1.22-5.16), lower baseline eGFR by CKD-EPI was significantly associated with higher rates of AKI in adjusted models. For all equations this association was minimally impacted when race adjustment was removed. For example, removal of race adjustment from CKD-EPI resulted in a 0.1% increase in the association between lower eGFR and higher rate of AKI events per 15 mL/min/1.73 m2 change (p < 0.001). CONCLUSIONS: Race adjustment in eGFR equations did not enhance AKI risk estimation in patients with cirrhosis. Further study is warranted to assess the impacts of removing race from eGFR equations on clinical outcomes and policy.
Authors: Jeong-Ju Yoo; Sang Gyune Kim; Young Seok Kim; Bora Lee; Min Hee Lee; Soung Won Jeong; Jae Young Jang; Sae Hwan Lee; Hong Soo Kim; Young Don Kim; Gab Jin Cheon Journal: J Hepatol Date: 2019-01-08 Impact factor: 25.083
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