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      Longitudinal change in estimated GFR among CKD patients: A 10-year follow-up study of an integrated kidney disease care program in Taiwan

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          Abstract

          Background

          This study examined the progression of chronic kidney disease (CKD) by using average annual decline in estimated GFR (eGFR) and its risk factors in a 10-year follow-up CKD cohort.

          Methods

          A prospective, observational cohort study, 4600 individuals fulfilled the definition of CKD, with or without proteinuria, were followed for 10 years. The eGFR was estimated by the MDRD equation. Linear regression was used to estimate participants’ annual decline rate in eGFR. We defined subjects with annual eGFR decline rate <1 ml/min/1.73 m 2 as non-progression and the decline rate over 3 ml/min/1.73 m 2 as rapid progression.

          Results

          During the follow-up period, 2870 (62.4%) individuals had annual eGFR decline rate greater than 1 ml/min/1.73 m 2. The eGFR decline rate was slower in individuals with CKD diagnosed over the age of 60 years than those with onset at a younger age. Comparing to subjects with decline rate <1 ml/min/1.73 m 2/year, the odds ratio (OR) of developing rapid CKD progression for diabetes, proteinuria and late onset of CKD was 1.72 (95% CI: 1.48–2.00), 1.89(1.63–2.20) and 0.68 (0.56–0.81), respectively. When the model was adjusted for the latest CKD stage, comparing to those with CKD stage 1, patients with stage 4 and stage 5 have significantly higher risks for rapid progression (OR, 5.17 (2.60–10.25), 19.83 (10.05–39.10), respectively). However, such risk was not observed among patients with the latest CKD stage 2 and 3. The risk for incident ESRD was 17% higher for each 1 ml/min/1.73 m 2 increasing in annual decline rate.

          Conclusions

          Not everyone with CKD develops ESRD after a 10-year follow-up. Absolute annual eGFR decline rate can help clinicians to better predict the progression of CKD. Individuals with renal function decline rate over 3 ml/min/1.73 m 2/year require intensive CKD care.

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          Most cited references27

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          Decline in estimated glomerular filtration rate and subsequent risk of end-stage renal disease and mortality.

          The established chronic kidney disease (CKD) progression end point of end-stage renal disease (ESRD) or a doubling of serum creatinine concentration (corresponding to a change in estimated glomerular filtration rate [GFR] of −57% or greater) is a late event. To characterize the association of decline in estimated GFR with subsequent progression to ESRD with implications for using lesser declines in estimated GFR as potential alternative end points for CKD progression. Because most people with CKD die before reaching ESRD, mortality risk also was investigated. Individual meta-analysis of 1.7 million participants with 12,344 ESRD events and 223,944 deaths from 35 cohorts in the CKD Prognosis Consortium with a repeated measure of serum creatinine concentration over 1 to 3 years and outcome data. Transfer of individual participant data or standardized analysis of outputs for random-effects meta-analysis conducted between July 2012 and September 2013, with baseline estimated GFR values collected from 1975 through 2012. End-stage renal disease (initiation of dialysis or transplantation) or all-cause mortality risk related to percentage change in estimated GFR over 2 years, adjusted for potential confounders and first estimated GFR. The adjusted hazard ratios (HRs) of ESRD and mortality were higher with larger estimated GFR decline. Among participants with baseline estimated GFR of less than 60 mL/min/1.73 m2, the adjusted HRs for ESRD were 32.1 (95% CI, 22.3-46.3) for changes of −57% in estimated GFR and 5.4 (95% CI, 4.5-6.4) for changes of −30%. However, changes of −30% or greater (6.9% [95% CI, 6.4%-7.4%] of the entire consortium) were more common than changes of −57% (0.79% [95% CI, 0.52%-1.06%]). This association was strong and consistent across the length of the baseline period (1 to 3 years), baseline estimated GFR, age, diabetes status, or albuminuria. Average adjusted 10-year risk of ESRD (in patients with a baseline estimated GFR of 35 mL/min/1.73 m2) was 99% (95% CI, 95%-100%) for estimated GFR change of −57%, was 83% (95% CI, 71%-93%) for estimated GFR change of −40%, and was 64% (95% CI, 52%-77%) for estimated GFR change of −30% vs 18% (95% CI, 15%-22%) for estimated GFR change of 0%. Corresponding mortality risks were 77% (95% CI, 71%-82%), 60% (95% CI, 56%-63%), and 50% (95% CI, 47%-52%) vs 32% (95% CI, 31%-33%), showing a similar but weaker pattern. Declines in estimated GFR smaller than a doubling of serum creatinine concentration occurred more commonly and were strongly and consistently associated with the risk of ESRD and mortality, supporting consideration of lesser declines in estimated GFR (such as a 30% reduction over 2 years) as an alternative end point for CKD progression.
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            Predictors of the progression of renal disease in the Modification of Diet in Renal Disease Study.

            The Modification of Diet in Renal Disease (MDRD) Study examined the effects of dietary protein restriction and strict blood pressure control on the decline in glomerular filtration rate (GFR) in 840 patients with diverse renal diseases. We describe a systematic analysis to determine baseline factors that predict the decline in GFR, or which alter the efficacy of the diet or blood pressure interventions. Univariate analysis identified 18 of 41 investigated baseline factors as significant (P < 0.05) predictors of GFR decline. In multivariate analysis, six factors--greater urine protein excretion, diagnosis of polycystic kidney disease (PKD), lower serum transferrin, higher mean arterial pressure, black race, and lower serum HDL cholesterol--independently predicted a faster decline in GFR. Together with the study interventions, these six factors accounted for 34.5% and 33.9% of the variance between patients in GFR slopes in Studies A and B, respectively, with proteinuria and PKD playing the predominant role. The mean rate of GFR decline was not significantly related to baseline GFR, suggesting an approximately linear mean GFR decline as renal disease progresses. The 41 baseline predictors were also assessed for their interactions with the diet and blood pressure interventions. A greater benefit of the low blood pressure intervention was found in patients with higher baseline urine protein. None of the 41 baseline factors were shown to predict a greater or lesser effect of dietary protein restriction.
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              The effect of age on creatinine clearance in men: a cross-sectional and longitudinal study.

              Standard true 24-hour creatinine clearance determinations were performed on 884 subjects of the Baltimore Longitudinal Study. On the basis of clinical data, subjects were placed in categories indicating the presence of specific diseases or medications which might alter glomerular filtration rate. Subjects not included in these categories were considered normal (N=548). In the normals, cross-sectional analysis by 10-year age groups showed a progressive linear decline in clearance from 140 ml/min/1.73m2 at age 30 to 97 at age 80. Three or more serial clearances were obtained at 12- to 18-mo. intervals on 293 normal subjects. These longitudinal data showed an acceleration of the rate of decline in creatinine clearance with advancing age. The decrease in creatinine clearance with age seen in this study represents true renal aging and is not secondary to diseases which become increasingly prevalent in the elderly. A nomogram constructed from these data provides normative age-corrected standards for creatinine clearance.
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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
                5 April 2017
                2017
                : 12
                : 4
                : e0173843
                Affiliations
                [1 ]Division of Nephrology and Kidney Institute, Department of Internal Medicine, China Medical University Hospital, Taichung, Taiwan
                [2 ]School of Medicine, College of Medicine, China Medical University, Taichung, Taiwan
                [3 ]Big Data Center, China Medical University Hospital, Taichung, Taiwan
                The University of Tokyo, JAPAN
                Author notes

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

                • Conceptualization: CWT CCK.

                • Data curation: CWT IWT HCY CCK.

                • Formal analysis: CWT.

                • Funding acquisition: CWT IWT HCY CCK.

                • Investigation: CWT CCK.

                • Methodology: CWT.

                • Project administration: CWT IWT HCY CCK.

                • Resources: CWT IWT HCY CCK.

                • Software: CWT.

                • Supervision: CWT CCK.

                • Validation: CWT CCK.

                • Visualization: CWT CCK.

                • Writing – original draft: CWT.

                • Writing – review & editing: CWT CCK.

                Article
                PONE-D-17-00398
                10.1371/journal.pone.0173843
                5381774
                28380035
                8ee4abef-ec18-4330-b9cd-a1592e3f9350
                © 2017 Tsai 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
                : 4 January 2017
                : 27 February 2017
                Page count
                Figures: 2, Tables: 5, Pages: 14
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Medicine and Health Sciences
                Nephrology
                Chronic Kidney Disease
                Medicine and Health Sciences
                Diagnostic Medicine
                Signs and Symptoms
                Proteinuria
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Signs and Symptoms
                Proteinuria
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Metabolic Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Cardiovascular Medicine
                Cardiovascular Diseases
                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
                Physiology
                Renal Physiology
                Glomerular Filtration Rate
                Medicine and Health Sciences
                Physiology
                Renal Physiology
                Glomerular Filtration Rate
                Medicine and Health Sciences
                Vascular Medicine
                Blood Pressure
                Custom metadata
                Due to patient privacy, data cannot be publicly deposited or included in the supporting information. Data are available from the CMUH Big Data Center Data Access / Ethics Committee for researchers who meet the criteria for access to confidential data. Researchers can contact the first author (Ching-Wei Tsai, cwtsai2007@ 123456gmail.com ), the corresponding author (Chin-Chi Kuo, chinchik@ 123456gmail.com ) or CMUH Big Data Center Data Access / Ethics Committee ( bdc@ 123456mail.cmuh.org.tw ) to apply for access to confidential data.

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