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Clin J Am Soc Nephrol ; 6(10): 2411-20, 2011 Oct.
Article in English | MEDLINE | ID: mdl-21852668

ABSTRACT

BACKGROUND AND OBJECTIVES: A specific method is required for estimating glomerular filtration rate GFR in hospitalized patients. Our objective was to validate the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation and four cystatin C (CysC)-based equations in this setting. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This was an epidemiologic, cross-sectional study in a random sample of hospitalized patients (n = 3114). We studied the accuracy of the CKD-EPI and four CysC-based equations--based on (1) CysC alone or (2) adjusted by gender; (3) age, gender, and race; and (4) age, gender, race, and creatinine, respectively--compared with GFR measured by iohexol clearance (mGFR). Clinical, biochemical, and nutritional data were also collected. RESULTS: The CysC equation 3 significantly overestimated the GFR (bias of 7.4 ml/min per 1.73 m(2)). Most of the error in creatinine-based equations was attributable to calculated muscle mass, which depended on patient's nutritional status. In patients without malnutrition or reduced body surface area, the CKD-EPI equation adequately estimated GFR. Equations based on CysC gave more precise mGFR estimates when malnutrition, extensive reduction of body surface area, or loss of muscle mass were present (biases of 1 and 1.3 ml/min per 1.73 m(2) for equations 2 and 4, respectively, versus 5.9 ml/min per 1.73 m(2) for CKD-EPI). CONCLUSIONS: These results suggest that the use of equations based on CysC and gender, or CysC, age, gender, and race, is more appropriate in hospitalized patients to estimate GFR, since these equations are much less dependent on patient's nutritional status or muscle mass than the CKD-EPI equation.


Subject(s)
Cystatin C/analysis , Glomerular Filtration Rate , Hospitalization , Kidney Diseases/diagnosis , Kidney/physiopathology , Models, Biological , Adult , Age Factors , Aged , Aged, 80 and over , Biomarkers/blood , Body Surface Area , Chi-Square Distribution , Chronic Disease , Creatinine/blood , Cross-Sectional Studies , Female , Humans , Iohexol , Kidney Diseases/blood , Kidney Diseases/epidemiology , Kidney Diseases/physiopathology , Linear Models , Male , Middle Aged , Muscle, Skeletal/pathology , Nutritional Status , Organ Size , Predictive Value of Tests , Racial Groups , Risk Assessment , Risk Factors , Sex Factors , Spain/epidemiology
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