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.
Austria
Germany
chronic kidney disease
risk prediction model
type 2 diabetes
Journal
Diabetes, obesity & metabolism
ISSN: 1463-1326
Titre abrégé: Diabetes Obes Metab
Pays: England
ID NLM: 100883645
Informations de publication
Date de publication:
03 2023
03 2023
Historique:
revised:
11
11
2022
received:
02
10
2022
accepted:
21
11
2022
pubmed:
30
11
2022
medline:
4
2
2023
entrez:
29
11
2022
Statut:
ppublish
Résumé
To validate a recently proposed risk prediction model for chronic kidney disease (CKD) in type 2 diabetes (T2D). 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 Subjects (n = 10 922) had a mean age of 61 years, diabetes duration of 6 years, BMI of 31.7 kg/m 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.
Substances chimiques
Glycated Hemoglobin
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
776-784Informations de copyright
© 2022 John Wiley & Sons Ltd.
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