Validation of a risk prediction model for early chronic kidney disease in patients with type 2 diabetes: Data from the German/Austrian Diabetes Prospective Follow-up registry.

Autor: Kress S; Medical Clinic I, Diabetes Center, Vinzentius-Hospital, Landau, Germany., Bramlage P; Institute for Pharmacology and Preventive Medicine, Cloppenburg, Germany., Holl RW; Institute for Epidemiology and Medical Biometry, ZIBMT, University of Ulm, Ulm, Germany.; German Center for Diabetes Research (DZD), München-Neuherberg, Germany., Möller CD; Bürgerhospital Frankfurt am Main, Frankfurt am Main, Germany., Mühldorfer S; Gastroenterologie, Klinikum Bayreuth, Bayreuth, Germany., Reindel J; Herz- und Diabeteszentrum, Klinikum Karlsburg, Karlsburg, Germany., Seufert J; Division of Endocrinology and Diabetology, Department of Medicine II, Medical Center, Faculty of Medicine, University of Freiburg, Freiburg, Germany., Landgraf R; German Diabetes Foundation, Munich, Germany., Merker L; Diabetologie im MVZ am Park Ville d'Eu, Haan, Germany., Meyhöfer SM; German Center for Diabetes Research (DZD), München-Neuherberg, Germany.; Institute for Endocrinology & Diabetes, University of Lübeck, Lübeck, Germany., Danne T; Kinderkrankenhaus auf der Bult, Diabeteszentrum für Kinder und Jugendliche, Hannover, Germany., Fasching P; 5th Medical Department for Endocrinology, Rheumatology and Acute Geriatrics, Clinic Ottakring, Vienna, Austria., Mertens PR; Clinic of Nephrology and Hypertension, Diabetes and Endocrinology, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany., Wanner C; Division of Nephrology, Wuerzburg University Clinic, Würzburg, Germany., Lanzinger S; Institute for Epidemiology and Medical Biometry, ZIBMT, University of Ulm, Ulm, Germany.; German Center for Diabetes Research (DZD), München-Neuherberg, Germany.
Jazyk: angličtina
Zdroj: Diabetes, obesity & metabolism [Diabetes Obes Metab] 2023 Mar; Vol. 25 (3), pp. 776-784. Date of Electronic Publication: 2022 Dec 20.
DOI: 10.1111/dom.14925
Abstrakt: Aim: To validate a recently proposed risk prediction model for chronic kidney disease (CKD) in type 2 diabetes (T2D).
Materials and Methods: Subjects from the German/Austrian Diabetes Prospective Follow-up (DPV) registry with T2D, normoalbuminuria, an estimated glomerular filtration rate of 60 ml/min/1.73m 2 or higher and aged 39-75 years were included. Prognostic factors included age, body mass index (BMI), smoking status and HbA1c. Subjects were categorized into low, moderate, high and very high-risk groups. Outcome was CKD occurrence.
Results: Subjects (n = 10 922) had a mean age of 61 years, diabetes duration of 6 years, BMI of 31.7 kg/m 2 , HbA1c of 6.9% (52 mmol/mol); 9.1% had diabetic retinopathy and 16.3% were smokers. After the follow-up (~59 months), 37.4% subjects developed CKD. The area under the curve (AUC; unadjusted base model) was 0.58 (95% CI 0.57-0.59). After adjustment for diabetes and follow-up duration, the AUC was 0.69 (95% CI 0.68-0.70), indicating improved discrimination. After follow-up, 15.0%, 20.1%, 27.7% and 40.2% patients in the low, moderate, high and very high-risk groups, respectively, had developed CKD. Increasing risk score correlated with increasing cumulative risk of incident CKD over a median of 4.5 years of follow-up (P < .0001).
Conclusions: The predictive model achieved moderate discrimination but good calibration in a German/Austrian T2D population, suggesting that the model may be relevant for determining CKD risk.
(© 2022 John Wiley & Sons Ltd.)
Databáze: MEDLINE
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