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Published in: Diabetology & Metabolic Syndrome 1/2013

Open Access 01-12-2013 | Research

Predictive models for type 2 diabetes onset in middle-aged subjects with the metabolic syndrome

Authors: Michal Ozery-Flato, Naama Parush, Tal El-Hay, Žydrūnė Visockienė, Ligita Ryliškytė, Jolita Badarienė, Svetlana Solovjova, Milda Kovaitė, Rokas Navickas, Aleksandras Laucevičius

Published in: Diabetology & Metabolic Syndrome | Issue 1/2013

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Abstract

Objective

To investigate the predictive value of different biomarkers for the incidence of type 2 diabetes mellitus (T2DM) in subjects with metabolic syndrome.

Methods

A prospective study of 525 non-diabetic, middle-aged Lithuanian men and women with metabolic syndrome but without overt atherosclerotic diseases during a follow-up period of two to four years. We used logistic regression to develop predictive models for incident cases and to investigate the association between various markers and the onset of T2DM.

Results

Fasting plasma glucose (FPG), body mass index (BMI), and glycosylated haemoglobin can be used to predict diabetes onset with a high level of accuracy and each was shown to have a cumulative predictive value. The estimated area under the receiver-operating characteristic curve (AUC) for this combination was 0.92. The oral glucose tolerance test (OGTT) did not show cumulative predictive value. Additionally, progression to diabetes was associated with high values of aortic pulse-wave velocity (aPWV).

Conclusion

T2DM onset in middle-aged metabolic syndrome subjects can be predicted with remarkable accuracy using the combination of FPG, BMI, and HbA1c, and is related to elevated aPWV measurements.
Appendix
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Metadata
Title
Predictive models for type 2 diabetes onset in middle-aged subjects with the metabolic syndrome
Authors
Michal Ozery-Flato
Naama Parush
Tal El-Hay
Žydrūnė Visockienė
Ligita Ryliškytė
Jolita Badarienė
Svetlana Solovjova
Milda Kovaitė
Rokas Navickas
Aleksandras Laucevičius
Publication date
01-12-2013
Publisher
BioMed Central
Published in
Diabetology & Metabolic Syndrome / Issue 1/2013
Electronic ISSN: 1758-5996
DOI
https://doi.org/10.1186/1758-5996-5-36

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