In:
Diabetes, Obesity and Metabolism, Wiley, Vol. 25, No. 3 ( 2023-03), p. 776-784
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
1462-8902
,
1463-1326
Language:
English
Publisher:
Wiley
Publication Date:
2023
detail.hit.zdb_id:
2004918-3
