Literature DB >> 22694950

Prediction of kidney-related outcomes in patients with type 2 diabetes.

Meg J Jardine1, Jun Hata, Mark Woodward, Vlado Perkovic, Toshiharu Ninomiya, Hisatomi Arima, Sophia Zoungas, Alan Cass, Anushka Patel, Michel Marre, Giuseppe Mancia, Carl E Mogensen, Neil Poulter, John Chalmers.   

Abstract

BACKGROUND: Tools are needed to predict which individuals with diabetes will develop kidney disease and its complications. STUDY
DESIGN: An observational analysis of a randomized controlled trial. SETTING & PARTICIPANTS: The ADVANCE (Action in Diabetes and Vascular Disease: Preterax and Diamicron MR Controlled Evaluation) Study followed up 11,140 participants with type 2 diabetes for 5 years. PREDICTOR: Readily available baseline demographic and clinical variables. OUTCOMES: (1) Major kidney-related events (doubling of serum creatinine to ≥2.26 mg/dL [≥200 μmol/L], renal replacement therapy, or renal death) in all participants, and (2) new-onset albuminuria in participants with baseline normoalbuminuria. MEASUREMENTS: Cox proportional hazard regression models predicting the outcomes were used to generate risk scores. Discrimination of the risk prediction models was compared with that of models based on estimated glomerular filtration rate (eGFR) alone, urinary albumin-creatinine ratio (ACR) alone, and their combination.
RESULTS: Risk scores for major kidney-related events and new-onset albuminuria were derived from 7- and 8-variable models, respectively. Baseline eGFR and ACR were dominant although models based on the 2 factors, alone or combined, had less discrimination (P<0.05) than the risk prediction models containing additional variables (risk prediction model C statistics of 0.847 [95% CI, 0.815-0.880] for major kidney-related events, and 0.647 [95% CI, 0.637-0.658] for new-onset albuminuria). Novel risk factors for new-onset albuminuria included Asian ethnicity and greater waist circumference, and for major kidney-related events, less education. The risk prediction models had acceptable calibration for both outcomes (modified Hosmer-Lemeshow test, P=0.9 and P=0.06, respectively). LIMITATIONS: The follow-up period was limited to 5 years. Results are applicable to people with type 2 diabetes at risk of vascular disease.
CONCLUSIONS: Risk scores have been developed for early and late events in diabetic nephropathy. Although eGFR and urinary ACR are important components of the prediction models, the extra variables considered add significantly to discrimination and, in the case of new-onset albuminuria, are required to achieve satisfactory calibration.
Copyright © 2012 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22694950     DOI: 10.1053/j.ajkd.2012.04.025

Source DB:  PubMed          Journal:  Am J Kidney Dis        ISSN: 0272-6386            Impact factor:   8.860


  49 in total

1.  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
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2.  Incidence and Associations of Chronic Kidney Disease in Community Participants With Diabetes: A 5-Year Prospective Analysis of the EXTEND45 Study.

Authors:  Louisa Sukkar; Amy Kang; Carinna Hockham; Tamara Young; Min Jun; Celine Foote; Roberto Pecoits-Filho; Brendon Neuen; Kris Rogers; Carol Pollock; Alan Cass; David Sullivan; Germaine Wong; John Knight; David Peiris; Martin Gallagher; Meg Jardine
Journal:  Diabetes Care       Date:  2020-03-11       Impact factor: 19.112

3.  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
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4.  Are SGLT2 Inhibitors Safe and Effective in Advanced Diabetic Kidney Disease?

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Review 6.  Glucose targets for preventing diabetic kidney disease and its progression.

Authors:  Marinella Ruospo; Valeria M Saglimbene; Suetonia C Palmer; Salvatore De Cosmo; Antonio Pacilli; Olga Lamacchia; Mauro Cignarelli; Paola Fioretto; Mariacristina Vecchio; Jonathan C Craig; Giovanni Fm Strippoli
Journal:  Cochrane Database Syst Rev       Date:  2017-06-08

7.  Quantification of HDL proteins, cardiac events, and mortality in patients with type 2 diabetes on hemodialysis.

Authors:  Chantal Kopecky; Bernd Genser; Christiane Drechsler; Vera Krane; Christopher C Kaltenecker; Markus Hengstschläger; Winfried März; Christoph Wanner; Marcus D Säemann; Thomas Weichhart
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8.  Improved clinical trial enrollment criterion to identify patients with diabetes at risk of end-stage renal disease.

Authors:  Masayuki Yamanouchi; Jan Skupien; Monika A Niewczas; Adam M Smiles; Alessandro Doria; Robert C Stanton; Andrzej T Galecki; Kevin L Duffin; Nick Pullen; Matthew D Breyer; Joseph V Bonventre; James H Warram; Andrzej S Krolewski
Journal:  Kidney Int       Date:  2017-04-07       Impact factor: 10.612

9.  Diabetes: Assessing renal risk in patients with type 2 diabetes.

Authors:  Merlin C Thomas; Per-Henrik Groop
Journal:  Nat Rev Nephrol       Date:  2013-09-17       Impact factor: 28.314

10.  HDL Cholesterol Efflux Does Not Predict Cardiovascular Risk in Hemodialysis Patients.

Authors:  Chantal Kopecky; Sanam Ebtehaj; Bernd Genser; Christiane Drechsler; Vera Krane; Marlies Antlanger; Johannes J Kovarik; Christopher C Kaltenecker; Mojtaba Parvizi; Christoph Wanner; Thomas Weichhart; Marcus D Säemann; Uwe J F Tietge
Journal:  J Am Soc Nephrol       Date:  2016-09-09       Impact factor: 10.121

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