99 research outputs found

    Relative risks of chronic kidney disease for mortality and end-stage renal disease across races are similar

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    Some suggest race-specific cutpoints for kidney measures to define and stage chronic kidney disease (CKD), but evidence for race-specific clinical impact is limited. To address this issue, we compared hazard ratios of estimated glomerular filtration rates (eGFR) and albuminuria across races using meta-regression in 1.1 million adults (75% Asians, 21% Whites, and 4% Blacks) from 45 cohorts. Results came mainly from 25 general population cohorts comprising 0.9 million individuals. The associations of lower eGFR and higher albuminuria with mortality and end-stage renal disease (ESRD) were largely similar across races. For example, in Asians, Whites, and Blacks, the adjusted hazard ratios (95% confidence interval) for eGFR 45-59 versus 90-104 ml/min per 1.73 m(2) were 1.3 (1.2-1.3), 1.1 (1.0-1.2), and 1.3 (1.1-1.7) for all-cause mortality, 1.6 (1.5-1.7), 1.4 (1.2-1.7), and 1.4 (0.7-2.9) for cardiovascular mortality, and 27.6 (11.1-68.7), 11.2 (6.0-20.9), and 4.1 (2.2-7.5) for ESRD, respectively. The corresponding hazard ratios for urine albumin-to-creatinine ratio 30-299 mg/g or dipstick 1+ versus an albumin-to-creatinine ratio under 10 or dipstick negative were 1.6 (1.4-1.8), 1.7 (1.5-1.9), and 1.8 (1.7-2.1) for all-cause mortality, 1.7 (1.4-2.0), 1.8 (1.5-2.1), and 2.8 (2.2-3.6) for cardiovascular mortality, and 7.4 (2.0-27.6), 4.0 (2.8-5.9), and 5.6 (3.4-9.2) for ESRD, respectively. Thus, the relative mortality or ESRD risks of lower eGFR and higher albuminuria were largely similar among three major races, supporting similar clinical approach to CKD definition and staging, across races

    Is the Presence of Microalbuminuria a Relevant Marker of Kidney Disease?

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    Levels of urinary albumin excretion that are below the usual limit of detection by qualitative testing, but are above normal levels (microalbuminuria; MA), can be readily identified by simple measures, such as the urinary albumin to creatinine ratio in untimed urine samples. Such measurements, particularly when combined with assessment of estimated glomerular filtration rate (eGFR), have utility as biomarkers for enhanced risk of all-cause mortality, cardiovascular events, progressive chronic kidney disease, and end-stage renal disease in diabetic and nondiabetic subjects. However, it is controversial whether “isolated” MA (MA in the absence of a clear reduction in eGFR, urine sediment abnormalities, or structural renal disease) should be regarded as kidney disease. Such MA could also be regarded as a manifestation of a diffuse endothelial (microvascular) injury and thereby collateral kidney damage. This article reviews the current evidence concerning MA as a marker of kidney disease or kidney damage

    Conversion of Urine Protein-Creatinine Ratio or Urine Dipstick Protein to Urine Albumin-Creatinine Ratio for Use in Chronic Kidney Disease Screening and Prognosis : An Individual Participant–Based Meta-analysis

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    Financial Support: The CKD-PC Data Coordinating Center is funded in part by a program grant from the U.S. National Kidney Foundation and the National Institute of Diabetes and Digestive and Kidney Diseases (R01DK100446). Various sources have supported enrollment and data collection, including laboratory measurements and follow-up, in the collaborating cohorts of the CKD-PC. These funding sources include government agencies, such as national institutes of health and medical research councils, as well as the foundations and industry sponsors listed in Supplemental Appendix 3 (available at Annals.org).Peer reviewedPostprin

    Grams ME, Sang Y, Ballew SH, et al, for the Chronic Kidney Disease Prognosis Consortium. Predicting timing of clinical outcomes in patients with chronic kidney disease and severely decreased glomerular filtration rate. Kidney Int. 2018;93:1442-1451.

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    The Chronic Kidney Disease (CKD) Prognosis Consortium is a collaborative author of the above-mentioned article. The CKD Prognosis Consortium investigators/collaborators are as follows: ‱ African American Study of Kidney Disease and Hypertension (AASK): Brad Astor, Lawrence J. Appel; Canadian Study of Prediction of Death, Dialysis and Interim Cardiovascular Events (CanPREDDICT): Adeera Levin, Mila Tang, Ognjenka Djurdjev; Cleveland Clinic CKD Registry Study (CCF): Sankar D. Navaneethan, Stacey E. Jolly, Jesse D. Schold, Joseph V. Nally Jr.; Chronic Renal Impairment in Birmingham (CRIB): David C. Wheeler, Jonathan Emberson, John Townend, Martin Landray; Chronic Renal Insufficiency Cohort Study (CRIC): Harold I. Feldman, Chi-yuan Hsu, James P. Lash, Lawrence J. Appel; Chronic Renal Insufficiency Standards Implementation Study (CRISIS): Philip A. Kalra, James P. Ritchie, Raman Maharajan, Rachel J. Middleton, Donal J. O'Donoghue; German Chronic Kidney Disease Study (GCKD): Kai-Uwe Eckardt, Markus P. Schneider, Anna Köttgen, Florian Kronenberg, Barbara BĂ€rthlein; Geisinger Health System: Alex R. Chang, Jamie A. Green, H. Lester Kirchner, Kevin Ho; Grampian Laboratory Outcomes, Morbidity and Mortality Studies – 2 (GLOMMS2): Angharad Marks, Corri Black, Gordon J. Prescott, Nick Fluck; Gonryo Study: Masaaki Nakayama, Mariko Miyazaki, Tae Yamamoto, Gen Yamada; Hong Kong CKD Studies: Angela Yee-Moon Wang, Sharon Cheung, Sharon Wong, Jessie Chu, Henry Wu; Ontario Institute for Clinical Evaluative Sciences, Provincial Kidney, Dialysis and Transplantation program (ICES KDT): Amit X. Garg, Eric McArthur, Danielle M. Nash; Maccabi Health System: Varda Shalev, Gabriel Chodick; Multifactorial Approach and Superior Treatment Efficacy in Renal Patients with the Aid of a Nurse Practitioner (MASTERPLAN): Peter J. Blankestijn, Jack F.M. Wetzels, Arjan D. van Zuilen, Jan A. van den Brand; Modification of Diet in Renal Disease Study (MDRD): Andrew S. Levey, Lesley A. Inker, Mark J. Sarnak, Hocine Tighiouart; Nanjing CKD Network Cohort Study (Nanjing CKD): Haitao Zhang; NephroTest Study (NephroTest): Benedicte Stengel, Marie Metzger, Martin Flamant, Pascal Houillier, Jean-Philippe Haymann; National Renal Healthcare Program – Uruguay (NRHP-URU): Pablo G. Rios, Nelson Mazzuchi, Liliana Gadola, VerĂłnica Lamadrid, Laura Sola; New Zealand Diabetes Cohort Study (NZDCS): John F. Collins, C. Raina Elley, Timothy Kenealy; Parcours de Soins des Personnes AgĂ©es (PSPA): Olivier Moranne, Cecile Couchoud, Cecile Vigneau; Primary-Secondary Care Partnership to Prevent Adverse Outcomes in Chronic Kidney Disease (PSP CKD): Nigel J. Brunskill, Rupert W. Major, David Shepherd, James F. Medcalf; Racial and Cardiovascular Risk Anomalies in CKD Cohort (RCAV): Csaba P. Kovesdy, Kamyar Kalantar-Zadeh, Miklos Z. Molnar, Keiichi Sumida, Praveen K. Potukuchi; Reduction of Endpoints in Non-insulin Dependent Diabetes Mellitus with the Angiotensin II Antagonist Losartan (RENAAL): Hiddo J.L. Heerspink, Dick de Zeeuw, Barry Brenner; Stockholm CREAtinine Measurements Cohort (SCREAM): Juan Jesus Carrero, Alessandro Gasparini, Abdul Rashid Qureshi, Carl-Gustaf Elinder; Second Manifestations of ARTerial Disease Study (SMART): Frank L.J. Visseren, Yolanda van der Graaf; Swedish Renal Registry CKD Cohort (SRR CKD): Marie Evans, Maria Stendahl, Staffan Schön, MĂ„rten Segelmark, Karl-Göran PrĂŒtz; Sunnybrook Cohort: David M. Naimark, Navdeep Tangri; West of Scotland CKD Study: Patrick B. Mark, Jamie P. Traynor, Colin C. Geddes, Peter C. Thomson.‱ CKD Prognosis Consortium Steering Committee: Alex R. Chang, Josef Coresh (Chair), Ron T. Gansevoort, Morgan E. Grams, Anna Köttgen, Andrew S. Levey, Kunihiro Matsushita, Mark Woodward, Luxia Zhang.‱ CKD Prognosis Consortium Data Coordinating Center: Shoshana H. Ballew (Assistant Project Director), Jingsha Chen (Programmer), Josef Coresh (Principal Investigator), Morgan E. Grams (Director of Nephrology Initiatives), Lucia Kwak (Programmer), Kunihiro Matsushita (Director), Yingying Sang (Lead Programmer), Aditya Surapaneni (Programmer), Mark Woodward (Senior Statistician).‱ Kidney Disease Improving Global Outcomes (KDIGO) Controversies Conference on Prognosis and Optimal Management of Patients with Advanced CKD: Kai-Uwe Eckardt (Conference Co-Chair), Brenda R. Hemmelgarn (Conference Co-Chair), David C. Wheeler (KDIGO Co-Chair), Wolfgang C. Winkelmayer (KDIGO Co-Chair), John Davis (CEO), Danielle Green (Managing Director), Michael Cheung (Chief Scientific Officer), Tanya Green (Communications Director), Melissa McMahan (Programs Director)

    Change in albuminuria and subsequent risk of end-stage kidney disease : an individual participant-level consortium meta-analysis of observational studies

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    Background: Change in albuminuria as a surrogate endpoint for progression of chronic kidney disease is strongly supported by biological plausibility, but empirical evidence to support its validity in epidemiological studies is lacking. We aimed to assess the consistency of the association between change in albuminuria and risk of end-stage kidney disease in a large individual participant-level meta-analysis of observational studies. Methods: In this meta-analysis, we collected individual-level data from eligible cohorts in the Chronic Kidney Disease Prognosis Consortium (CKD-PC) with data on serum creatinine and change in albuminuria and more than 50 events on outcomes of interest. Cohort data were eligible if participants were aged 18 years or older, they had a repeated measure of albuminuria during an elapsed period of 8 months to 4 years, subsequent end-stage kidney disease or mortality follow-up data, and the cohort was active during this consortium phase. We extracted participant-level data and quantified percentage change in albuminuria, measured as change in urine albumin-to-creatinine ratio (ACR) or urine protein-to-creatinine ratio (PCR), during baseline periods of 1, 2, and 3 years. Our primary outcome of interest was development of end-stage kidney disease after a baseline period of 2 years. We defined an end-stage kidney disease event as initiation of kidney replacement therapy. We quantified associations of percentage change in albuminuria with subsequent end-stage kidney disease using Cox regression in each cohort, followed by random-effects meta-analysis. We further adjusted for regression dilution to account for imprecision in the estimation of albuminuria at the participant level. We did multiple subgroup analyses, and also repeated our analyses using participant-level data from 14 clinical trials, including nine clinical trials not in CKD-PC. Findings: Between July, 2015, and June, 2018, we transferred and analysed data from 28 cohorts in the CKD-PC, which included 693 816 individuals (557 583 [80%] with diabetes). Data for 675 904 individuals and 7461 end-stage kidney disease events were available for our primary outcome analysis. Change in ACR was consistently associated with subsequent risk of end-stage kidney disease. The adjusted hazard ratio (HR) for end-stage kidney disease after a 30% decrease in ACR during a baseline period of 2 years was 0·83 (95% CI 0·74–0·94), decreasing to 0·78 (0·66–0·92) after further adjustment for regression dilution. Adjusted HRs were fairly consistent across cohorts and subgroups (ie, estimated glomerular filtration rate, diabetes, and sex), but the association was somewhat stronger among participants with higher baseline ACR than among those with lower baseline ACR (pinteraction<0·0001). In individuals with baseline ACR of 300 mg/g or higher, a 30% decrease in ACR over 2 years was estimated to confer a more than 1% absolute reduction in 10-year risk of end-stage kidney disease, even at early stages of chronic kidney disease. Results were generally similar when we used change in PCR and when study populations from clinical trials were assessed. Interpretation: Change in albuminuria was consistently associated with subsequent risk of end-stage kidney disease across a range of cohorts, lending support to the use of change in albuminuria as a surrogate endpoint for end-stage kidney disease in clinical trials of progression of chronic kidney disease in the setting of increased albuminuria. Funding: US National Kidney Foundation and US National Institute of Diabetes and Digestive and Kidney Diseases

    Evolution and Diseases

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