Background: In populations with high prevalences of diabetes and obesity, estimating glomerular filtration rate (GFR) by using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation may predict cardiovascular disease (CVD) risk better than by using the Modification of Diet in Renal Disease (MDRD) Study equation. Study Design: Longitudinal cohort study comparing the association of GFR estimated using either the CKD-EPI or MDRD Study equation with incident CVD outcomes. Setting & Participants: American Indians participating in the Strong Heart Study, a longitudinal population-based cohort with high prevalences of diabetes, CVD, and CKD. Predictor: Estimated GFR (eGFR) predicted using the CKD-EPI and MDRD Study equations. Outcomes: Fatal and nonfatal cardiovascular events, consisting of coronary heart disease, stroke, and heart failure. Measurements: The association between eGFR and outcomes was explored in Cox proportional hazards models adjusted for traditional risk factors and albuminuria; the net reclassification index and integrated discrimination improvement were determined for the CKD-EPI versus MDRD Study equations. Results: In 4,549 participants, diabetes was present in 45%; CVD, in 7%; and stages 3-5 CKD, in 10%. During a median of 15 years, there were 1,280 cases of incident CVD, 929 cases of incident coronary heart disease, 305 cases of incident stroke, and 381 cases of incident heart failure. Reduced eGFR (<90 mL/min/1.73 m(2)) was associated with adverse events in most models. Compared with the MDRD Study equation, the CKD-EPI equation correctly reclassified 17.0% of 2,151 participants without incident CVD to a lower risk (higher eGFR) category and 1.3% (n = 28) were reclassified incorrectly to a higher risk (lower eGFR) category. Limitations: Single measurements of eGFR and albuminuria at study visits. Conclusions: Although eGFR based on either equation had similar associations with incident CVD, coronary heart disease, stroke, and heart failure events, in those not having events, reclassification of participants to eGFR categories was superior using the CKD-EPI equation compared with the MDRD Study equation. Am J Kidney Dis. 60(5):795-803. (C) 2012 by the National Kidney Foundation, Inc.
机构:
Univ Oklahoma, Hlth Sci Ctr, Dept Biostat & Epidemiol, Oklahoma City, OK 73104 USAUniv Oklahoma, Hlth Sci Ctr, Dept Biostat & Epidemiol, Oklahoma City, OK 73104 USA
Eichner, June E.
Wang, Wenyu
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Univ Oklahoma, Hlth Sci Ctr, Ctr Amer Indian Hlth Res, Oklahoma City, OK 73104 USAUniv Oklahoma, Hlth Sci Ctr, Dept Biostat & Epidemiol, Oklahoma City, OK 73104 USA
Wang, Wenyu
Zhang, Ying
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Univ Oklahoma, Hlth Sci Ctr, Ctr Amer Indian Hlth Res, Oklahoma City, OK 73104 USAUniv Oklahoma, Hlth Sci Ctr, Dept Biostat & Epidemiol, Oklahoma City, OK 73104 USA
Zhang, Ying
Lee, Elisa T.
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Univ Oklahoma, Hlth Sci Ctr, Ctr Amer Indian Hlth Res, Oklahoma City, OK 73104 USAUniv Oklahoma, Hlth Sci Ctr, Dept Biostat & Epidemiol, Oklahoma City, OK 73104 USA
Lee, Elisa T.
Welty, Thomas K.
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Missouri Breaks Ind Res Inc, Timber Lake, SD 57656 USAUniv Oklahoma, Hlth Sci Ctr, Dept Biostat & Epidemiol, Oklahoma City, OK 73104 USA
Welty, Thomas K.
[J].
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