학술논문
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.
Document Type
Article
Author
Source
Subject
*TYPE 2 diabetes
*CHRONIC kidney failure
*CHRONICALLY ill
*PREDICTION models
*DISEASE risk factors
*TOBACCO smoke
*SMOKING statistics
*SMOKE
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Language
ISSN
1462-8902
Abstract
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/1.73m2 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/m2, 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. [ABSTRACT FROM AUTHOR]