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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 Bärthlein; 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, Verónica Lamadrid, Laura Sola; New Zealand Diabetes Cohort Study (NZDCS): John F. Collins, C. Raina Elley, Timothy Kenealy; Parcours de Soins des Personnes Agées (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, Mårten Segelmark, Karl-Göran Prütz; 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).

[This corrects the article DOI: 10.1016/j.ekir.2018.01.002.].

AimsBoth hypo- and hyperkalaemia can have immediate deleterious physiological effects, and less is known about long-term risks. The objective was to determine the risks of all-cause mortality, cardiovascular mortality, and end-stage renal disease associated with potassium levels across the range of kidney function and evaluate for consistency across cohorts in a global consortium.Methods and resultsWe performed an individual-level data meta-analysis of 27 international cohorts [10 general population, 7 high cardiovascular risk, and 10 chronic kidney disease (CKD)] in the CKD Prognosis Consortium. We used Cox regression followed by random-effects meta-analysis to assess the relationship between baseline potassium and adverse outcomes, adjusted for demographic and clinical characteristics, overall and across strata of estimated glomerular filtration rate (eGFR) and albuminuria. We included 1 217 986 participants followed up for a mean of 6.9 years. The average age was 55 ± 16 years, average eGFR was 83 ± 23 mL/min/1.73 m2, and 17% had moderate- to-severe increased albuminuria levels. The mean baseline potassium was 4.2 ± 0.4 mmol/L. The risk of serum potassium of >5.5 mmol/L was related to lower eGFR and higher albuminuria. The risk relationship between potassium levels and adverse outcomes was U-shaped, with the lowest risk at serum potassium of 4-4.5 mmol/L. Compared with a reference of 4.2 mmol/L, the adjusted hazard ratio for all-cause mortality was 1.22 [95% confidence interval (CI) 1.15-1.29] at 5.5 mmol/L and 1.49 (95% CI 1.26-1.76) at 3.0 mmol/L. Risks were similar by eGFR, albuminuria, renin-angiotensin-aldosterone system inhibitor use, and across cohorts.ConclusionsOutpatient potassium levels both above and below the normal range are consistently associated with adverse outcomes, with similar risk relationships across eGFR and albuminuria.

Background New equations to estimate glomerular filtration rate based on creatinine (eGFRcr), cystatin C (eGFRcys) or both (eGFRcr-cys) have been developed by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and the European Kidney Function Consortium (EKFC). There is a need to evaluate the performance of these equations in diverse European settings to inform implementation decisions, especially among people with key comorbid conditions. Methods We performed a cross-sectional study including 6174 adults referred for single-point plasma clearance of iohexol in Stockholm, Sweden, with 9579 concurrent measurements of creatinine and cystatin C. We assessed the performance of the CKD-EPI 2009/2012/2021, EKFC 2021/2023, revised Lund-Malmö (RLM) 2011 and Caucasian, Asian, Pediatric and Adult (CAPA) 2014 equations against measured GFR (mGFR). Results Mean age was 56 years, median mGFR was 62 mL/min/1.73 m2 and 40% were female. Comorbid conditions were common: cardiovascular disease (30%), liver disease (28%), diabetes (26%) and cancer (26%). All eGFRcr-cys equations had small bias and P30 (the percentage of estimated values within 30% of mGFR) close to 90%, and performed better than eGFRcr or eGFRcys equations. Among eGFRcr equations, CKD-EPI 2009 and CKD-EPI 2021 showed larger bias and lower P30 than EKFC 2021 and RLM. There were no meaningful differences in performance across eGFRcys equations. Findings were consistent across comorbid conditions, and eGFRcr-cys equations showed good performance in patients with liver disease, cancer and heart failure. Conclusions In conclusion, eGFRcr-cys equations performed best, with minimal variation among equations in this Swedish cohort. The lower performance of CKD-EPI eGFRcr equations compared with EKFC and RLM may reflect differences in population characteristics and mGFR methods. Implementing eGFRcr equations will require a trade-off between accuracy and uniformity across regions. [ABSTRACT FROM AUTHOR]

Background While American nephrology societies recommend using the 2021 Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) estimated glomerular filtration rate (eGFR) equation without a Black race coefficient, it is unknown how this would impact disease distribution, prognosis and kidney failure risk prediction in predominantly White non-US populations. Methods We studied 1.6 million Stockholm adults with serum/plasma creatinine measurements between 2007 and 2019. We calculated changes in eGFR and reclassification across KDIGO GFR categories when changing from the 2009 to 2021 CKD-EPI equation; estimated associations between eGFR and the clinical outcomes kidney failure with replacement therapy (KFRT), (cardiovascular) mortality and major adverse cardiovascular events using Cox regression; and investigated prognostic accuracy (discrimination and calibration) of both equations within the Kidney Failure Risk Equation. Results Compared with the 2009 equation, the 2021 equation yielded a higher eGFR by a median [interquartile range (IQR)] of 3.9 (2.9–4.8) mL/min/1.73 m2, which was larger at older age and for men. Consequently, 9.9% of the total population and 36.2% of the population with CKD G3a–G5 was reclassified to a higher eGFR category. Reclassified individuals exhibited a lower risk of KFRT, but higher risks of all-cause/cardiovascular death and major adverse cardiovascular events, compared with non-reclassified participants of similar eGFR. eGFR by both equations strongly predicted study outcomes, with equal discrimination and calibration for the Kidney Failure Risk Equation. Conclusions Implementing the 2021 CKD-EPI equation in predominantly White European populations would raise eGFR by a modest amount (larger at older age and in men) and shift a major proportion of CKD patients to a higher eGFR category. eGFR by both equations strongly predicted outcomes. [ABSTRACT FROM AUTHOR]