PuSH - Publication Server of Helmholtz Zentrum München

Kowall, B.* ; Rathmann, W.* ; Bongaerts, B.* ; Thorand, B. ; Belcredi, P. ; Heier, M. ; Huth, C. ; Rückert, I.-M. ; Stöckl, D. ; Peters, A. ; Meisinger, C.

Are diabetes risk scores useful for the prediction of cardiovascular diseases? Assessment of seven diabetes risk scores in the KORA S4/F4 cohort study.

J. Diab. Complic. 27, 340-345 (2013)
DOI Order publishers version
Open Access Green as soon as Postprint is submitted to ZB.
AIM: To evaluate the utility of diabetes prediction models for CVD prediction as stated in two earlier studies. METHODS: 845 subjects from the population based German KORA (Cooperative Health Research in the Region of Augsburg) S4/F4 cohort study (aged 55 to 74years, without diabetes, former stroke, and former myocardial infarction at baseline) were followed for up to ten years for incident stroke and myocardial infarction. Seven diabetes risk scores developed from four different studies were applied to the KORA cohort to assess their predictive ability for CVD. RESULTS: Areas under the receiver-operating curve (AROCs) for the prediction of CVD ranged from 0.60 to 0.65 when diabetes risk scores were applied to the KORA cohort. When diabetes risk scores were used to predict CVD and type 2 diabetes, respectively, AROCs for the prediction of CVD were 0.09 to 0.24 lower than AROCs for the prediction of type 2 diabetes. Furthermore, we used KORA data to develop prediction models for either diabetes or CVD, and found that they differed widely in selected predictor variables. CONCLUSION: In the older population, diabetes risk scores are not useful for the prediction of CVD, and prediction models for diabetes and CVD, respectively, require different parameters.
Altmetric
Additional Metrics?
Edit extra informations Login
Publication type Article: Journal article
Document type Scientific Article
Keywords Diabetes Mellitus ; Cardiovascular Disease ; Stroke ; Myocardial Infarction ; Risk Scores; Metabolic Syndrome ; Mellitus ; Models ; Adults ; Tool
ISSN (print) / ISBN 1056-8727
e-ISSN 1056-8727
Quellenangaben Volume: 27, Issue: 4, Pages: 340-345 Article Number: , Supplement: ,
Publisher Elsevier
Reviewing status Peer reviewed