Literature DB >> 17699284

Risk scores for predicting outcomes in patients with type 2 diabetes and nephropathy: the RENAAL study.

William F Keane1, Zhongxin Zhang, Paulette A Lyle, Mark E Cooper, Dick de Zeeuw, Jean-Pierre Grunfeld, James P Lash, Janet B McGill, William E Mitch, Giuseppe Remuzzi, Shahnaz Shahinfar, Steven M Snapinn, Robert Toto, Barry M Brenner.   

Abstract

Diabetic nephropathy is the most important cause of ESRD. The aim of this study was to develop a risk score from risk predictors for ESRD, with and without death, in the Reduction of Endpoints in NIDDM with the Angiotensin II Antagonist Losartan (RENAAL) study and to compare ability of the ESRD risk score and its components to predict ESRD. The risk score was developed from coefficients of independent risk factors from multivariate analysis of baseline variables and equals (1.96 x log [urinary albumin:creatinine ratio]) - (0.78 serum albumin [g/dl]) + (1.28 x serum creatinine [mg/dl]) - (0.11 x hemoglobin [g/dl]). It was robust with respect to severity of nephropathy, gender, race, and treatment group. The risk score for ESRD or death was comparable. The four risk predictors for progression of kidney disease were independent of therapy. For combined treatment groups, the hazard ratio between the fourth and first quartiles of the ESRD risk score was 49.0, as compared with the corresponding hazard ratios for each component: 14.7 for urinary albumin:creatinine ratio, 9.2 for serum creatinine, 5.5 for hemoglobin, and 10.2 for serum albumin. The RENAAL risk scores for ESRD with or without death emphasize the importance of identification of level of albuminuria, serum albumin, serum creatinine, and hemoglobin to predict development of ESRD in patients with type 2 diabetes and nephropathy. Although albuminuria is a strong risk factor for ESRD, the contribution of serum albumin, serum creatinine, and hemoglobin level further enhances prediction of ESRD. Future trials with a similar patient population and outcomes measures should consider adjusting analyses for baseline risk factors.

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Year:  2006        PMID: 17699284     DOI: 10.2215/CJN.01381005

Source DB:  PubMed          Journal:  Clin J Am Soc Nephrol        ISSN: 1555-9041            Impact factor:   8.237


  75 in total

1.  Applying the Temporal Abstraction Technique to the Prediction of Chronic Kidney Disease Progression.

Authors:  Li-Chen Cheng; Ya-Han Hu; Shr-Han Chiou
Journal:  J Med Syst       Date:  2017-04-11       Impact factor: 4.460

2.  Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes. A collaborative meta-analysis of general and high-risk population cohorts.

Authors:  Ron T Gansevoort; Kunihiro Matsushita; Marije van der Velde; Brad C Astor; Mark Woodward; Andrew S Levey; Paul E de Jong; Josef Coresh
Journal:  Kidney Int       Date:  2011-02-02       Impact factor: 10.612

3.  Effect of hemoglobin target on progression of kidney disease: a secondary analysis of the CHOIR (Correction of Hemoglobin and Outcomes in Renal Insufficiency) trial.

Authors:  Jula K Inrig; Huiman X Barnhart; Donal Reddan; Uptal D Patel; Shelly Sapp; Robert M Califf; Ajay K Singh; Lynda A Szczech
Journal:  Am J Kidney Dis       Date:  2012-04-25       Impact factor: 8.860

4.  Combining GFR and albuminuria to classify CKD improves prediction of ESRD.

Authors:  Stein I Hallan; Eberhard Ritz; Stian Lydersen; Solfrid Romundstad; Kurt Kvenild; Stephan R Orth
Journal:  J Am Soc Nephrol       Date:  2009-04-08       Impact factor: 10.121

5.  Risk prediction of major complications in individuals with diabetes: the Atherosclerosis Risk in Communities Study.

Authors:  C M Parrinello; K Matsushita; M Woodward; L E Wagenknecht; J Coresh; E Selvin
Journal:  Diabetes Obes Metab       Date:  2016-06-14       Impact factor: 6.577

6.  Risk Prediction for Early CKD in Type 2 Diabetes.

Authors:  Daniela Dunkler; Peggy Gao; Shun Fu Lee; Georg Heinze; Catherine M Clase; Sheldon Tobe; Koon K Teo; Hertzel Gerstein; Johannes F E Mann; Rainer Oberbauer
Journal:  Clin J Am Soc Nephrol       Date:  2015-07-14       Impact factor: 8.237

7.  Glomerular and tubular damage markers in individuals with progressive albuminuria.

Authors:  Ferdau L Nauta; Lieneke Scheven; Esther Meijer; Wim van Oeveren; Paul E de Jong; Stephan J L Bakker; Ron T Gansevoort
Journal:  Clin J Am Soc Nephrol       Date:  2013-03-28       Impact factor: 8.237

8.  A simple tool to predict end-stage renal disease within 1 year in elderly adults with advanced chronic kidney disease.

Authors:  Paul E Drawz; Puja Goswami; Reem Azem; Denise C Babineau; Mahboob Rahman
Journal:  J Am Geriatr Soc       Date:  2013-04-25       Impact factor: 5.562

9.  Screening for albuminuria identifies individuals at increased renal risk.

Authors:  Marije van der Velde; Nynke Halbesma; Frank T de Charro; Stephan J L Bakker; Dick de Zeeuw; Paul E de Jong; Ronald T Gansevoort
Journal:  J Am Soc Nephrol       Date:  2009-02-11       Impact factor: 10.121

10.  Prediction of ESRD and death among people with CKD: the Chronic Renal Impairment in Birmingham (CRIB) prospective cohort study.

Authors:  Martin J Landray; Jonathan R Emberson; Lisa Blackwell; Tanaji Dasgupta; Rosita Zakeri; Matthew D Morgan; Charlie J Ferro; Susan Vickery; Puja Ayrton; Devaki Nair; R Neil Dalton; Edmund J Lamb; Colin Baigent; Jonathan N Townend; David C Wheeler
Journal:  Am J Kidney Dis       Date:  2010-10-30       Impact factor: 8.860

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