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      Comparison of creatinine-based equations for estimating glomerular filtration rate in deceased donor renal transplant recipients

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          Abstract

          Background

          Estimating glomerular filtration rate (GFR) is important for clinical management in kidney transplantation recipients (KTR). However, very few studies have evaluated the performance of the new GFR estimating equations (Lund-Malmö Revised–LMR, and Full Age Spectrum–FAS) in KTR.

          Methods

          GFR was estimated (eGFR) using CKD-EPI, MDRD, LMR, and FAS equations and compared to GFR measurement (mGFR) by reference methods (inuline urinary and iohexol plasma clearance) in 395 deceased-donor KTR without corticosteroids. The equations performance was assessed using bias (mean difference of eGFR and mGFR), precision (standard deviation of the difference), accuracy (concordance correlation coefficient—CCC), and agreements (total deviation index—TDI). The area under receiver operating characteristic curves (ROC) and the likelihood ratio for a positive result were calculated.

          Results

          In the total population, the performance of the CKD-EPI, MDRD and FAS equations was significantly lower than the LMR equation regarding the mean [95%CI] difference in bias (-2.0 [-4.0; -1.5] versus 9.0 [7.5; 10.0], 5.0 [3.5; 6.0] and 10.0 [8.5; 11.0] mL/min/1.73m 2, P<0.005) and TDI (17.10 [16.41; 17.88], 25.91 [24.66; 27.16], 21.23 [19.48; 23.13] and 25.84 [24.16; 27.57], respectively). Concerning the CCC, all equation had poor agreement (<0.800) without statically difference between them. However, all equations had excellent area under the ROC curve (>0.900), and LMR equation had the best ability to correctly predict KTR with mGFR<45 mL/min/1.73 m 2 (positive likelihood ratio: 8.87 [5.79; 13.52]).

          Conclusion

          Among a referral group of subjects KTR, LMR equation had the best mean bias and TDI, but with no significant superiority in other agreement tools. Caveat is required in the use and interpretation of PCr-based equations in this specific population.

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          Most cited references21

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          KDIGO clinical practice guideline for the care of kidney transplant recipients.

          (2009)
          The 2009 Kidney Disease: Improving Global Outcomes (KDIGO) clinical practice guideline on the monitoring, management, and treatment of kidney transplant recipients is intended to assist the practitioner caring for adults and children after kidney transplantation. The guideline development process followed an evidence-based approach, and management recommendations are based on systematic reviews of relevant treatment trials. Critical appraisal of the quality of the evidence and the strength of recommendations followed the Grades of Recommendation Assessment, Development, and Evaluation (GRADE) approach. The guideline makes recommendations for immunosuppression, graft monitoring, as well as prevention and treatment of infection, cardiovascular disease, malignancy, and other complications that are common in kidney transplant recipients, including hematological and bone disorders. Limitations of the evidence, especially on the lack of definitive clinical outcome trials, are discussed and suggestions are provided for future research.
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            Comparative performance of the CKD Epidemiology Collaboration (CKD-EPI) and the Modification of Diet in Renal Disease (MDRD) Study equations for estimating GFR levels above 60 mL/min/1.73 m2.

            The Modification of Diet in Renal Disease (MDRD) Study equation underestimates measured glomerular filtration rate (GFR) at levels>60 mL/min/1.73 m2, with variable accuracy among subgroups; consequently, estimated GFR (eGFR)>or=60 mL/min/1.73 m2 is not reported by clinical laboratories. Here, performance of a more accurate GFR-estimating equation, the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, is reported by level of GFR and clinical characteristics. Test of diagnostic accuracy. Pooled data set of 3,896 people from 16 studies with measured GFR (not used for the development of either equation). Subgroups were defined by eGFR, age, sex, race, diabetes, prior solid-organ transplant, and body mass index. eGFR from the CKD-EPI and MDRD Study equations and standardized serum creatinine. Measured GFR using urinary or plasma clearance of exogenous filtration markers. Mean measured GFR was 68+/-36 (SD) mL/min/1.73 m2. For eGFR or=90 mL/min/1.73 m2. Limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI equation is more accurate than the MDRD Study equation overall and across most subgroups. In contrast to the MDRD Study equation, eGFR>or=60 mL/min/1.73 m2 can be reported using the CKD-EPI equation. Copyright (c) 2010 National Kidney Foundation, Inc. All rights reserved.
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              An estimated glomerular filtration rate equation for the full age spectrum.

              Glomerular filtration rate (GFR) is accepted as the best indicator of kidney function and is commonly estimated from serum creatinine (SCr)-based equations. Separate equations have been developed for children (Schwartz equation), younger and middle-age adults [Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation] and older adults [Berlin Initiative Study 1 (BIS1) equation], and these equations lack continuity with ageing. We developed and validated an equation for estimating the glomerular filtration rate that can be used across the full age spectrum (FAS).
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Supervision
                Role: ConceptualizationRole: Data curationRole: InvestigationRole: Methodology
                Role: InvestigationRole: Methodology
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: Validation
                Role: ConceptualizationRole: Formal analysisRole: Methodology
                Role: Formal analysis
                Role: Data curationRole: Methodology
                Role: Data curationRole: Investigation
                Role: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: Project administration
                Role: Data curationRole: InvestigationRole: MethodologyRole: Project administrationRole: Validation
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                28 April 2020
                2020
                : 15
                : 4
                : e0231873
                Affiliations
                [1 ] Néphrologie, Dialyse, Hypertension et Exploration Fonctionnelle Rénale, Groupement Hospitalier Edouard Herriot, Hospices Civils de Lyon, Lyon, France
                [2 ] Universidade de Caxias do Sul—Programa de Pós-Graduação em Ciências da Saúde, Caxias do Sul, Brazil
                [3 ] Hospital Geral de Caxias do Sul, Caxias do Sul, Brazil
                [4 ] Université Lyon 1, Lyon, France
                [5 ] CarMeN: Cardiovasculaire, Métabolisme, Diabétologie & Nutrition-INSERM U1060/Lyon 1, Lyon, France
                [6 ] Service de Transplantation, Néphrologie et Immunologie Clinique, Hôpital Edouard Herriot, Lyon, France
                [7 ] Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil
                [8 ] Service d'anesthésie-réanimation, hôpital Edouard-Herriot, Lyon, France
                [9 ] Unité INSERM U1111, Lyon, France
                [10 ] Service d’Urologie et Transplantation, Hôpital Edouard Herriot, Lyon, France
                [11 ] Laboratoire de Biologie Tissulaire et d’ingénierie Thérapeutique (LBTI), UMR 5305 CNRS, Université Claude Bernard Lyon 1, Lyon, France
                Istituto Di Ricerche Farmacologiche Mario Negri, ITALY
                Author notes

                Competing Interests: No. The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-0152-0636
                Article
                PONE-D-19-27908
                10.1371/journal.pone.0231873
                7188287
                32343691
                36ba551a-d69a-4cd1-a560-ebfdf75448d6
                © 2020 Selistre et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 25 October 2019
                : 26 March 2020
                Page count
                Figures: 4, Tables: 4, Pages: 14
                Funding
                The study had no specific public or private financial support. In the study period, only the author L.S. benefited from a postdoctoral scholarship grant from the Brazilian government (CAPES Foundation, Ministry of Education of Brazil, grant number: 88881.156638/2017-01). The Brazilian funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Physiology
                Renal Physiology
                Glomerular Filtration Rate
                Medicine and Health Sciences
                Physiology
                Renal Physiology
                Glomerular Filtration Rate
                Medicine and Health Sciences
                Nephrology
                Chronic Kidney Disease
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Transplantation
                Organ Transplantation
                Renal Transplantation
                Medicine and Health Sciences
                Surgical and Invasive Medical Procedures
                Urinary System Procedures
                Renal Transplantation
                Biology and Life Sciences
                Anatomy
                Renal System
                Kidneys
                Medicine and Health Sciences
                Anatomy
                Renal System
                Kidneys
                Biology and Life Sciences
                Biochemistry
                Biomarkers
                Creatinine
                Biology and Life Sciences
                Nutrition
                Diet
                Medicine and Health Sciences
                Nutrition
                Diet
                Medicine and Health Sciences
                Nephrology
                Renal Diseases
                Medicine and Health Sciences
                Clinical Medicine
                Clinical Immunology
                Transplantation Immunology
                Biology and Life Sciences
                Immunology
                Clinical Immunology
                Transplantation Immunology
                Medicine and Health Sciences
                Immunology
                Clinical Immunology
                Transplantation Immunology
                Custom metadata
                The data may be accessed through Dataverse, doi: 10.7910/DVN/SKSPSY.

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