Literature DB >> 21737852

Relative performance of the MDRD and CKD-EPI equations for estimating glomerular filtration rate among patients with varied clinical presentations.

Kazunori Murata1, Nikola A Baumann, Amy K Saenger, Timothy S Larson, Andrew D Rule, John C Lieske.   

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. DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS: 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.

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Year:  2011        PMID: 21737852      PMCID: PMC3156428          DOI: 10.2215/CJN.02300311

Source DB:  PubMed          Journal:  Clin J Am Soc Nephrol        ISSN: 1555-9041            Impact factor:   8.237


  24 in total

1.  Performance of the modification of diet in renal disease and Cockcroft-Gault equations in the estimation of GFR in health and in chronic kidney disease.

Authors:  Emilio D Poggio; Xuelei Wang; Tom Greene; Frederik Van Lente; Phillip M Hall
Journal:  J Am Soc Nephrol       Date:  2004-12-22       Impact factor: 10.121

2.  Using serum creatinine to estimate glomerular filtration rate: accuracy in good health and in chronic kidney disease.

Authors:  Andrew D Rule; Timothy S Larson; Erik J Bergstralh; Jeff M Slezak; Steven J Jacobsen; Fernando G Cosio
Journal:  Ann Intern Med       Date:  2004-12-21       Impact factor: 25.391

3.  Development and validation of GFR-estimating equations using diabetes, transplant and weight.

Authors:  Lesley A Stevens; Christopher H Schmid; Yaping L Zhang; Josef Coresh; Jane Manzi; Richard Landis; Omran Bakoush; Gabriel Contreras; Saul Genuth; Goran B Klintmalm; Emilio Poggio; Peter Rossing; Andrew D Rule; Matthew R Weir; John Kusek; Tom Greene; Andrew S Levey
Journal:  Nephrol Dial Transplant       Date:  2009-09-30       Impact factor: 5.992

4.  GFR determined by nonradiolabeled iothalamate using capillary electrophoresis.

Authors:  D M Wilson; J H Bergert; T S Larson; R R Liedtke
Journal:  Am J Kidney Dis       Date:  1997-11       Impact factor: 8.860

5.  Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate.

Authors:  Andrew S Levey; Josef Coresh; Tom Greene; Lesley A Stevens; Yaping Lucy Zhang; Stephen Hendriksen; John W Kusek; Frederick Van Lente
Journal:  Ann Intern Med       Date:  2006-08-15       Impact factor: 25.391

6.  Limitations of estimating glomerular filtration rate from serum creatinine in the general population.

Authors:  Andrew D Rule; Richard J Rodeheffer; Timothy S Larson; John C Burnett; Fernando G Cosio; Stephen T Turner; Steven J Jacobsen
Journal:  Mayo Clin Proc       Date:  2006-11       Impact factor: 7.616

7.  Performance of the chronic kidney disease-epidemiology study equations for estimating glomerular filtration rate before and after nephrectomy.

Authors:  Brian R Lane; Sevag Demirjian; Christopher J Weight; Benjamin T Larson; Emilio D Poggio; Steven C Campbell
Journal:  J Urol       Date:  2010-01-18       Impact factor: 7.450

8.  Highly elevated levels of prostaglandin D synthase in the serum of patients with renal failure.

Authors:  D N Melegos; L Grass; A Pierratos; E P Diamandis
Journal:  Urology       Date:  1999-01       Impact factor: 2.649

9.  Impact of creatinine calibration on performance of GFR estimating equations in a pooled individual patient database.

Authors:  Lesley A Stevens; Jane Manzi; Andrew S Levey; Jing Chen; Amy E Deysher; Tom Greene; Emilio D Poggio; Christopher H Schmid; Michael W Steffes; Yaping Lucy Zhang; Frederick Van Lente; Josef Coresh
Journal:  Am J Kidney Dis       Date:  2007-07       Impact factor: 8.860

10.  A new equation to estimate glomerular filtration rate.

Authors:  Andrew S Levey; Lesley A Stevens; Christopher H Schmid; Yaping Lucy Zhang; Alejandro F Castro; Harold I Feldman; John W Kusek; Paul Eggers; Frederick Van Lente; Tom Greene; Josef Coresh
Journal:  Ann Intern Med       Date:  2009-05-05       Impact factor: 25.391

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  56 in total

1.  The Chronic Kidney Disease Epidemiology Collaboration equation improves the detection of hyperfiltration in Chinese diabetic patients.

Authors:  Fangya Zhao; Lei Zhang; Junxi Lu; Kaifeng Guo; Mian Wu; Haoyong Yu; Mingliang Zhang; Yuqian Bao; Haibing Chen; Weiping Jia
Journal:  Int J Clin Exp Med       Date:  2015-12-15

2.  Measurement of renal function in a kidney donor: a comparison of creatinine-based and volume-based GFRs.

Authors:  Don Kyoung Choi; See Min Choi; Bong Hee Park; Byong Chang Jeong; Seong Il Seo; Seong Soo Jeon; Hyun Moo Lee; Han-Yong Choi; Hwang Gyun Jeon
Journal:  Eur Radiol       Date:  2015-05-08       Impact factor: 5.315

Review 3.  Biomarkers in chronic kidney disease, from kidney function to kidney damage.

Authors:  Salvador Lopez-Giacoman; Magdalena Madero
Journal:  World J Nephrol       Date:  2015-02-06

4.  GFR estimating equations: getting closer to the truth?

Authors:  Andrew D Rule; Richard J Glassock
Journal:  Clin J Am Soc Nephrol       Date:  2013-05-23       Impact factor: 8.237

Review 5.  The applicability of eGFR equations to different populations.

Authors:  Pierre Delanaye; Christophe Mariat
Journal:  Nat Rev Nephrol       Date:  2013-07-16       Impact factor: 28.314

6.  Comparison of high glomerular filtration rate thresholds for identifying hyperfiltration.

Authors:  Harini A Chakkera; Aleksandar Denic; Walter K Kremers; Mark D Stegall; Joseph J Larson; Harish Ravipati; Sandra J Taler; John C Lieske; Lilach O Lerman; Joshua J Augustine; Andrew D Rule
Journal:  Nephrol Dial Transplant       Date:  2020-06-01       Impact factor: 5.992

7.  Predictors of Perioperative Acute Kidney Injury in Obese Patients Undergoing Laparoscopic Bariatric Surgery: a Single-Centre Retrospective Cohort Study.

Authors:  Hairil Rizal Abdullah; Tze Ping Tan; Mercedeh Vaez; Chameli Deb; Naguib Farag; Timothy D Jackson; David Tai Wong
Journal:  Obes Surg       Date:  2016-07       Impact factor: 4.129

8.  Chapter 1: Definition and classification of CKD.

Authors: 
Journal:  Kidney Int Suppl (2011)       Date:  2013-01

Review 9.  The implications of anatomical and functional changes of the aging kidney: with an emphasis on the glomeruli.

Authors:  Richard J Glassock; Andrew D Rule
Journal:  Kidney Int       Date:  2012-03-21       Impact factor: 10.612

Review 10.  The renal effects of ALK inhibitors.

Authors:  Hassan Izzedine; Rania Kheder El-Fekih; Mark A Perazella
Journal:  Invest New Drugs       Date:  2016-07-29       Impact factor: 3.850

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