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      A comparison of estimated glomerular filtration rates using Cockcroft−Gault and the Chronic Kidney Disease Epidemiology Collaboration estimating equations in HIV infection

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          Abstract

          Objectives

          The aim of this study was to determine whether the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI)- or Cockcroft−Gault (CG)-based estimated glomerular filtration rates (eGFRs) performs better in the cohort setting for predicting moderate/advanced chronic kidney disease (CKD) or end-stage renal disease (ESRD).

          Methods

          A total of 9521 persons in the EuroSIDA study contributed 133 873 eGFRs. Poisson regression was used to model the incidence of moderate and advanced CKD (confirmed eGFR < 60 and < 30 mL/min/1.73 m 2, respectively) or ESRD (fatal/nonfatal) using CG and CKD-EPI eGFRs.

          Results

          Of 133 873 eGFR values, the ratio of CG to CKD-EPI was ≥ 1.1 in 22 092 (16.5%) and the difference between them (CG minus CKD-EPI) was ≥ 10 mL/min/1.73 m 2 in 20 867 (15.6%). Differences between CKD-EPI and CG were much greater when CG was not standardized for body surface area (BSA). A total of 403 persons developed moderate CKD using CG [incidence 8.9/1000 person-years of follow-up (PYFU); 95% confidence interval (CI) 8.0–9.8] and 364 using CKD-EPI (incidence 7.3/1000 PYFU; 95% CI 6.5–8.0). CG-derived eGFRs were equal to CKD-EPI-derived eGFRs at predicting ESRD ( n = 36) and death ( n = 565), as measured by the Akaike information criterion. CG-based moderate and advanced CKDs were associated with ESRD [adjusted incidence rate ratio (aIRR) 7.17; 95% CI 2.65–19.36 and aIRR 23.46; 95% CI 8.54–64.48, respectively], as were CKD-EPI-based moderate and advanced CKDs (aIRR 12.41; 95% CI 4.74–32.51 and aIRR 12.44; 95% CI 4.83–32.03, respectively).

          Conclusions

          Differences between eGFRs using CG adjusted for BSA or CKD-EPI were modest. In the absence of a gold standard, the two formulae predicted clinical outcomes with equal precision and can be used to estimate GFR in HIV-positive persons.

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          Most cited references46

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          A new equation to estimate glomerular filtration rate.

          Equations to estimate glomerular filtration rate (GFR) are routinely used to assess kidney function. Current equations have limited precision and systematically underestimate measured GFR at higher values. To develop a new estimating equation for GFR: the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Cross-sectional analysis with separate pooled data sets for equation development and validation and a representative sample of the U.S. population for prevalence estimates. Research studies and clinical populations ("studies") with measured GFR and NHANES (National Health and Nutrition Examination Survey), 1999 to 2006. 8254 participants in 10 studies (equation development data set) and 3896 participants in 16 studies (validation data set). Prevalence estimates were based on 16,032 participants in NHANES. GFR, measured as the clearance of exogenous filtration markers (iothalamate in the development data set; iothalamate and other markers in the validation data set), and linear regression to estimate the logarithm of measured GFR from standardized creatinine levels, sex, race, and age. In the validation data set, the CKD-EPI equation performed better than the Modification of Diet in Renal Disease Study equation, especially at higher GFR (P < 0.001 for all subsequent comparisons), with less bias (median difference between measured and estimated GFR, 2.5 vs. 5.5 mL/min per 1.73 m(2)), improved precision (interquartile range [IQR] of the differences, 16.6 vs. 18.3 mL/min per 1.73 m(2)), and greater accuracy (percentage of estimated GFR within 30% of measured GFR, 84.1% vs. 80.6%). In NHANES, the median estimated GFR was 94.5 mL/min per 1.73 m(2) (IQR, 79.7 to 108.1) vs. 85.0 (IQR, 72.9 to 98.5) mL/min per 1.73 m(2), and the prevalence of chronic kidney disease was 11.5% (95% CI, 10.6% to 12.4%) versus 13.1% (CI, 12.1% to 14.0%). The sample contained a limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI creatinine equation is more accurate than the Modification of Diet in Renal Disease Study equation and could replace it for routine clinical use. National Institute of Diabetes and Digestive and Kidney Diseases.
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            Statistical methods for assessing agreement between two methods of clinical measurement.

            In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
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              STATISTICAL METHODS FOR ASSESSING AGREEMENT BETWEEN TWO METHODS OF CLINICAL MEASUREMENT

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                Author and article information

                Journal
                HIV Med
                HIV Med
                hiv
                HIV Medicine
                BlackWell Publishing Ltd (Oxford, UK )
                1464-2662
                1468-1293
                March 2014
                03 October 2013
                : 15
                : 3
                : 144-152
                Affiliations
                [1 ]Department of Infection and Population Health, University College London London, UK
                [2 ]Copenhagen HIV Program, University of Copenhagen Copenhagen, Denmark
                [3 ]Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet Copenhagen, Denmark
                [4 ]Academisch Medisch Centrum bij de Universiteit van Amsterdam Amsterdam, The Netherlands
                [5 ]Department of Infectious Diseases, Bern University Hospital and University of Bern Bern, Switzerland
                [6 ]Infectious and Tropical Diseases Institute, Department of Health Sciences, San Paolo Hospital, University of Milan Milan, Italy
                [7 ]Hospital Clinic i Provincial Barcelona, Spain
                [8 ]Saint-Pierre Hospital Brussels, Belgium
                [9 ]HIV and AIDS Outpatient Clinic, Szpital Specjalistyczny Chorzow, Poland
                Author notes
                Correspondence: Professor Amanda Mocroft, Department of Infection and Population Health, University College London, Rowland Hill St, London NW3 2PF, UK. Tel: +44 20 7794 0500 ext 33194; fax: +44 20 7472 6871; e-mail: a.mocroft@ 123456ucl.ac.uk
                [*]

                See Appendix S1 for study group.

                Article
                10.1111/hiv.12095
                4228765
                24118916
                9b133580-42d6-4653-a7fe-3afee439a0e0
                © 2013 The Authors. HIV Medicine published by John Wiley & Sons Ltd on behalf of British HIV Association.

                This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                : 26 August 2013
                Categories
                Original Research

                Infectious disease & Microbiology
                chronic kidney disease,end stage renal disease,egfr,renal function

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