title: Relative performance of the MDRD and CKD-EPI equations for estimating glomerular filtration rate among patients with varied clinical presentations.
abstract: BACKGROUND
  The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation was developed using both CKD and non-CKD patients to potentially replace the Modification of Diet in Renal Disease (MDRD) equation that was derived with only CKD patients. The objective of our study was to compare the accuracy of the MDRD and CKD-EPI equations for estimating GFR in a large group of patients having GFR measurements for diverse clinical indications.
  
  
  METHODS
  A cross-sectional study was conducted of patients who underwent renal function assessment for clinical purposes by simultaneous measurements of serum creatinine and estimation of GFR using the MDRD and CKD-EPI equations and renal clearance of iothalamate (n = 5238).
  
  
  RESULTS
  Bias compared with measured GFR (mGFR) varied for each equation depending on clinical presentation. The CKD-EPI equation demonstrated less bias than the MDRD equation in potential kidney donors (-8% versus -18%) and postnephrectomy donors (-7% versus -15%). However, the CKD-EPI equation was slightly more biased than the MDRD equation in native CKD patients (6% versus 3%), kidney recipients (8% versus 1%), and other organ recipients (9% versus 3%). Among potential kidney donors, the CKD-EPI equation had higher specificity than the MDRD equation for detecting an mGFR <60 ml/min per 1.73 m(2) (98% versus 94%) but lower sensitivity (50% versus 70%).
  
  
  CONCLUSIONS
  Clinical presentation influences the estimation of GFR from serum creatinine, and neither the CKD-EPI nor MDRD equation account for this. Use of the CKD-EPI equation misclassifies fewer low-risk patients as having reduced mGFR, although it is also less sensitive for detecting mGFR below specific threshold values used to define CKD stages.
authors: Mayo Clinic Division of Nephrology and Hypertension, 200 First Street SW, Rochester, MN 55905, USA.
authors: Kazunori
authors: K
authors: Murata
authors: Nikola A
authors: NA
authors: Baumann
authors: Amy K
authors: AK
authors: Saenger
authors: Timothy S
authors: TS
authors: Larson
authors: Andrew D
authors: AD
authors: Rule
authors: John C
authors: JC
authors: Lieske
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D015415:Biomarkers / Q000097:blood; D003287:Contrast Media; D003404:Creatinine / Q000097:blood; D003430:Cross-Sectional Studies; D003951:Diagnostic Errors; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007483:Iothalamic Acid; D007668:Kidney / Q000503:physiopathology*; D007674:Kidney Diseases / Q000097:blood / Q000175:diagnosis* / Q000503:physiopathology; D016018:Least-Squares Analysis; D008297:Male; D008875:Middle Aged; D008910:Minnesota; D008954:Models, Biological; D011237:Predictive Value of Tests; D012044:Regression Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index
chemical_list: D015415:Biomarkers; D003287:Contrast Media; D007483:Iothalamic Acid; D003404:Creatinine