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      Global Prevalence of Chronic Kidney Disease – A Systematic Review and Meta-Analysis

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          Abstract

          Chronic kidney disease (CKD) is a global health burden with a high economic cost to health systems and is an independent risk factor for cardiovascular disease (CVD). All stages of CKD are associated with increased risks of cardiovascular morbidity, premature mortality, and/or decreased quality of life. CKD is usually asymptomatic until later stages and accurate prevalence data are lacking. Thus we sought to determine the prevalence of CKD globally, by stage, geographical location, gender and age. A systematic review and meta-analysis of observational studies estimating CKD prevalence in general populations was conducted through literature searches in 8 databases. We assessed pooled data using a random effects model. Of 5,842 potential articles, 100 studies of diverse quality were included, comprising 6,908,440 patients. Global mean(95%CI) CKD prevalence of 5 stages 13·4%(11·7–15·1%), and stages 3–5 was 10·6%(9·2–12·2%). Weighting by study quality did not affect prevalence estimates. CKD prevalence by stage was Stage-1 (eGFR>90+ACR>30): 3·5% (2·8–4·2%); Stage-2 (eGFR 60–89+ACR>30): 3·9% (2·7–5·3%); Stage-3 (eGFR 30–59): 7·6% (6·4–8·9%); Stage-4 = (eGFR 29–15): 0·4% (0·3–0·5%); and Stage-5 (eGFR<15): 0·1% (0·1–0·1%). CKD has a high global prevalence with a consistent estimated global CKD prevalence of between 11 to 13% with the majority stage 3. Future research should evaluate intervention strategies deliverable at scale to delay the progression of CKD and improve CVD outcomes.

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          Most cited references123

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          Measuring inconsistency in meta-analyses.

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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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              Meta-analysis of Observational Studies in EpidemiologyA Proposal for Reporting

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                6 July 2016
                2016
                : 11
                : 7
                : e0158765
                Affiliations
                [1 ]Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, United Kingdom
                [2 ]Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom
                Mario Negri Institute for Pharmacological Research and Azienda Ospedaliera Ospedali Riuniti di Bergamo, ITALY
                Author notes

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

                Conceived and designed the experiments: NH DL FDRH. Performed the experiments: SF NH DL COC FDRH. Analyzed the data: NH SF JO JH. Wrote the paper: NH SF COC JO JH DL FDRH.

                Author information
                http://orcid.org/0000-0001-7927-8678
                Article
                PONE-D-15-50536
                10.1371/journal.pone.0158765
                4934905
                27383068
                f667a6db-14fd-4728-b30c-21b18057567b
                © 2016 Hill 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
                : 19 November 2015
                : 21 June 2016
                Page count
                Figures: 3, Tables: 1, Pages: 18
                Funding
                NH is funded by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre based at Oxford University Hospitals NHS Trust and University of Oxford. FDRH is part funded as Director of the National Institute for Health Research (NIHR) School for Primary Care Research (SPCR), Theme Leader in the NIHR Oxford Biomedical Research Centre (BRC), and Director of the NIHR Collaboration for Leadership in Applied Health Research and Care (CLAHRC) Oxford. DSL is part funded by the NIHR Oxford Diagnostic Evidence Co-operative and NIHR Oxford BRC. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Nephrology
                Chronic Kidney Disease
                Biology and Life Sciences
                Biochemistry
                Biomarkers
                Creatinine
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Meta-Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Meta-Analysis
                Research and Analysis Methods
                Research Assessment
                Systematic Reviews
                Biology and Life Sciences
                Physiology
                Renal Physiology
                Glomerular Filtration Rate
                Medicine and Health Sciences
                Physiology
                Renal Physiology
                Glomerular Filtration Rate
                Medicine and Health Sciences
                Cardiovascular Medicine
                Cardiovascular Diseases
                Research and Analysis Methods
                Database and Informatics Methods
                Database Searching
                Biology and Life Sciences
                Anatomy
                Renal System
                Medicine and Health Sciences
                Anatomy
                Renal System
                Custom metadata
                All data are from Dryad (datadryad.org); the DOI number is doi: 10.5061/dryad.3s7rd.

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