Erratum: 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 (Kidney International (2018) 93(6) (1442–1451), (S0085253818300978) (10.1016/j.kint.2018.01.009));Predicting timing of clinical outcomes in patients with chronic kidney disease and severely decreased glomerular filtration rate

Kidney International

Volumn 93, Issue 6, 2018, Pages 1442-1451

  Grams, Morgan E ^a,b   Sang, Yingying ^b   Ballew, Shoshana H ^b   Carrero, Juan Jesus ^c   Djurdjev, Ognjenka ^d   Heerspink, Hiddo J L ^e   Ho, Kevin ^f   Ito, Sadayoshi ^g   Marks, Angharad ^h   Naimark, David ⁱ   Nash, Danielle M ^j   Navaneethan, Sankar D ^k   Sarnak, Mark ^l   Stengel, Benedicte ^m   Visseren, Frank L J ⁿ   Wang, Angela Yee Moon ^o   Köttgen, Anna ^b,p   Levey, Andrew S ^l   Woodward, Mark ^b,q,r   Eckardt, Kai Uwe ^s   Hemmelgarn, Brenda ^t   Coresh, Josef ^b   more..

^a JOHNS HOPKINS UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^c KAROLINSKA INSTITUTE   (Sweden)

^d Provincial Health Service Authority   (Canada)

^e UNIVERSITY MEDICAL CENTER GRONINGEN   (Netherlands)

^f GEISINGER MEDICAL CENTER   (United States)

^g TOHOKU UNIVERSITY GRADUATE SCHOOL OF MEDICINE   (Japan)

^h UNIVERSITY OF ABERDEEN   (United Kingdom)

ⁱ UNIVERSITY OF TORONTO   (Canada)

^j INSTITUTE FOR CLINICAL EVALUATIVE SCIENCES   (Canada)

^k BAYLOR COLLEGE OF MEDICINE   (United States)

^l TUFTS MEDICAL CENTER   (United States)

^m CENTRE FOR RESEARCH IN EPIDEMIOLOGY AND POPULATION HEALTH   (France)

ⁿ UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

^o UNIVERSITY OF HONG KONG   (Hong Kong)

^p UNIVERSITY OF FREIBURG   (Germany)

^q UNIVERSITY OF OXFORD   (United Kingdom)

^r UNIVERSITY OF NEW SOUTH WALES   (Australia)

^s CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

^t UNIVERSITY OF CALGARY   (Canada)

more..

Author keywords

albuminuria; cardiovascular disease; chronic kidney disease

Indexed keywords

ADULT; AGE; AGED; ARTICLE; CHRONIC KIDNEY FAILURE; COHORT ANALYSIS; CONTROLLED STUDY; DIABETES MELLITUS; DISEASE SEVERITY; FEMALE; GENDER; GLOMERULUS FILTRATION RATE; HEALTH CARE COST; HUMAN; LIFE EXPECTANCY; MAJOR CLINICAL STUDY; MALE; MARKOV CHAIN; MICROALBUMINURIA; MIDDLE AGED; OUTCOME ASSESSMENT; PATIENT COUNSELING; PREDICTION; PRIORITY JOURNAL; PROGNOSIS; QUALITY OF LIFE; RACE; RENAL REPLACEMENT THERAPY; SENSITIVITY ANALYSIS; SMOKING; SYSTOLIC BLOOD PRESSURE; VERY ELDERLY; CARDIOVASCULAR DISEASE; CLINICAL TRIAL; COMPLICATION; DECISION SUPPORT SYSTEM; DISEASE EXACERBATION; KIDNEY; KIDNEY FAILURE; MONTE CARLO METHOD; MORTALITY; MULTICENTER STUDY; PATHOPHYSIOLOGY; RISK ASSESSMENT; RISK FACTOR; SEVERITY OF ILLNESS INDEX; TIME FACTOR;

ADULT; AGED; CARDIOVASCULAR DISEASES; DECISION SUPPORT TECHNIQUES; DISEASE PROGRESSION; FEMALE; GLOMERULAR FILTRATION RATE; HUMANS; KIDNEY; MALE; MARKOV CHAINS; MIDDLE AGED; MONTE CARLO METHOD; PROGNOSIS; RENAL INSUFFICIENCY; RENAL INSUFFICIENCY, CHRONIC; RENAL REPLACEMENT THERAPY; RISK ASSESSMENT; RISK FACTORS; SEVERITY OF ILLNESS INDEX; TIME FACTORS;

EID: 85044330182     PISSN: 00852538     EISSN: 15231755     Source Type: Journal    
DOI: 10.1016/j.kint.2018.08.009     Document Type: Erratum

References (26)

1. Levin, A., Tonelli, M., Bonventre, J., et al. Global kidney health 2017 and beyond: a roadmap for closing gaps in care, research, and policy. Lancet, 2017.
2. Lozano, R., Naghavi, M., Foreman, K., et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380 (2012), 2095–2128.
3. Grams, M.E., Chow, E.K., Segev, D.L., et al. Lifetime incidence of CKD stages 3-5 in the United States. Am J Kidney Dis 62 (2013), 245–252.
4. United States Renal Data System. 2016 USRDS Annual Data Report: Epidemiology of Kidney Disease in the United States, 2016, National Institutes of Health, Bethesda, MD.
5. Astor, B.C., Matsushita, K., Gansevoort, R.T., et al. Lower estimated glomerular filtration rate and higher albuminuria are associated with mortality and end-stage renal disease. A collaborative meta-analysis of kidney disease population cohorts. Kidney Int 79 (2011), 1331–1340.
6. Chronic Kidney Disease Prognosis Consortium, Matsushita, K., van der Velde, M., et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet 375 (2010), 2073–2081.
7. Tangri, N., Stevens, L.A., Griffith, J., et al. A predictive model for progression of chronic kidney disease to kidney failure. JAMA 305 (2011), 1553–1559.
8. Tangri, N., Grams, M.E., Levey, A.S., et al. Multinational assessment of accuracy of equations for predicting risk of kidney failure: a meta-analysis. JAMA 315 (2016), 164–174.
9. Schroeder, E.B., Yang, X., Thorp, M.L., et al. Predicting 5-year risk of RRT in stage 3 or 4 CKD: development and external validation. Clin J Am Soc Nephrol 12 (2017), 87–94.
10. Weiss, J.W., Platt, R.W., Thorp, M.L., et al. Predicting mortality in older adults with kidney disease: a pragmatic prediction model. J Am Geriatr Soc 63 (2015), 508–515.
11. Johnson, E.S., Thorp, M.L., Yang, X., et al. Predicting renal replacement therapy and mortality in CKD. Am J Kidney Dis 50 (2007), 559–565.
12. Evans M, Grams ME, Sang Y, et al. Risk factors for prognosis in patients with severely decreased GFR. Kidney Int Rep. https://doi.org/10.1016/j.ekir.2018.01.002.
13. Schmidt, M., Mansfield, K.E., Bhaskaran, K., et al. Adherence to guidelines for creatinine and potassium monitoring and discontinuation following renin-angiotensin system blockade: a UK general practice-based cohort study. BMJ Open, 7, 2017, e012818.
14. Matsushita, K., Coresh, J., Sang, Y., et al. Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data. Lancet Diabetes Endocrinol 3 (2015), 514–525.
15. Coresh, J., Turin, T.C., Matsushita, K., et al. Decline in estimated glomerular filtration rate and subsequent risk of end-stage renal disease and mortality. JAMA 311 (2014), 2518–2531.
16. Kovesdy, C.P., Coresh, J., Ballew, S.H., et al. Past decline versus current eGFR and subsequent ESRD risk. J Am Soc Nephrol 27 (2016), 2447–2455.
17. Matsushita, K., Ballew, S.H., Astor, B.C., et al. Cohort profile: the chronic kidney disease prognosis consortium. Int J Epidemiol 42 (2013), 1660–1668.
18. Levey, A.S., Stevens, L.A., Schmid, C.H., et al. A new equation to estimate glomerular filtration rate. Ann Intern Med 150 (2009), 604–612.
19. Moons, K.G., Donders, R.A., Stijnen, T., et al. Using the outcome for imputation of missing predictor values was preferred. J Clin Epidemiol 59 (2006), 1092–1101.
20. White, I.R., Royston, P., Imputing missing covariate values for the Cox model. Stat Med 28 (2009), 1982–1998.
21. White, I.R., Royston, P., Wood, A.M., Multiple imputation using chained equations: issues and guidance for practice. Stat Med 30 (2011), 377–399.
22. Fine, J.P., Gray, R.J., A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc 94 (1999), 496–509.
23. Borenstein, M., Hedges, L.V., Higgins, J.P., et al. Introduction to Meta-analysis. 2009, John Wiley and Sons, Chichester, UK.
24. Higgins, J.P., Thompson, S.G., Deeks, J.J., et al. Measuring inconsistency in meta-analyses. BMJ 327 (2003), 557–560.
25. Riley, R.D., Higgins, J.P., Deeks, J.J., Interpretation of random effects meta-analyses. BMJ, 342, 2011, d549.
26. Grams, M.E., Yang, W., Rebholz, C.M., et al. Risks of adverse events in advanced CKD: the Chronic Renal Insufficiency Cohort (CRIC) study. Am J Kidney Dis 70 (2017), 337–346.