PuSH - Publikationsserver des Helmholtz Zentrums München: Prediction models for incident Type 2 diabetes mellitus in the older population: KORA S4/F4 cohort study.

Informationen

Hinweise zu Qualitätskriterien von Zeitschriften

Open-Access-Richtlinie der Helmholtz-Gemeinschaft 2016

CC Licencences

Metriken für Publikationen

Navigation

Startseite

English

EVA: Veröffentlichen

Neuer EVA Antrag

Recherche

Erweiterte Suche

Durchblättern nach ...

... HMGU-Autoren/Konsortien

... Organisationsstruktur

... Zeitschriften

... Publikationstypen

... Forschungsdaten

... Arbeitsgruppen

... Erscheinungsjahr

Publikationen im Überblick

Statistik

HGF Fortschrittsbericht

OA Publikationen

Eintragen

Neue Publikation eintragen

Neue Publikation holen aus...

...EVA

Fehlende Publikation melden

Highlights

Suche

Hilfe & Kontakt

Ansprechpartner

Hilfe

Datenschutz

Helmholtz Open Science

Bibliometrische Indikatoren

SHERPA/RoMEO

DOAJ

Export:

Text

Endnote (RIS) BIB

BibTeX

Rathmann, W.* ; Kowall, B.* ; Heier, M. ; Herder, C.* ; Holle, R. ; Thorand, B. ; Strassburger, K.* ; Peters, A. ; Wichmann, H.-E. ; Giani, G.* ; Meisinger, C.

Prediction models for incident Type 2 diabetes mellitus in the older population: KORA S4/F4 cohort study.

Diabetic Med. 27, 1116-1123 (2010)

DOI

PMC

Open Access Green möglich sobald Postprint bei der ZB eingereicht worden ist.

Abstract
Metriken
Zusatzinfos

BACKGROUND: The aim was to derive Type 2 diabetes prediction models for the older population and to check to what degree addition of 2-h glucose measurements (oral glucose tolerance test) and biomarkers improves the predictive power of risk scores which are based on non-biochemical as well as conventional clinical parameters. METHODS: Oral glucose tolerance tests were carried out in a population-based sample of 1353 subjects, aged 55-74 years (62% response) in Augsburg (Southern Germany) from 1999 to 2001. The cohort was reinvestigated in 2006-2008. Of those individuals without diabetes at baseline, 887 (74%) participated in the follow-up. Ninety-three (10.5%) validated diabetes cases occurred during the follow-up. In logistic regression analyses for model 1, variables were selected from personal characteristics and additional variables were selected from routinely measurable blood parameters (model 2) and from 2-h glucose, adiponectin, insulin and homeostasis model assessment of insulin resistance (HOMA-IR) (model 3). RESULTS: Age, sex, BMI, parental diabetes, smoking and hypertension were selected for model 1. Model 2 additionally included fasting glucose, HbA(1c) and uric acid. The same variables plus 2-h glucose were selected for model 3. The area under the receiver operating characteristic curve significantly increased from 0.763 (model 1) to 0.844 (model 2) and 0.886 (model 3) (P<0.01). Biomarkers such as adiponectin and insulin did not improve the predictive abilities of models 2 and 3. Cross-validation and bootstrap-corrected model performance indicated high internal validity. CONCLUSIONS: This longitudinal study in an older population provides models to predict the future risk of Type 2 diabetes. The OGTT, but not biomarkers, improved discrimination of incident diabetes.

Impact Factor

Scopus SNIP

Web of Science
Times Cited

Scopus
Cited By

Altmetric

2.871

1.470