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Predictors of undiagnosed prevalent type 2 diabetes - The Danish General Suburban Population Study.
Heltberg, Andreas; Andersen, John Sahl; Sandholdt, Håkon; Siersma, Volkert; Kragstrup, Jakob; Ellervik, Christina.
Afiliação
  • Heltberg A; Section of General Practice, Department of Public Health and Research Unit for General Practice, University of Copenhagen, Denmark. Electronic address: anhe@sund.ku.dk.
  • Andersen JS; Section of General Practice, Department of Public Health and Research Unit for General Practice, University of Copenhagen, Denmark.
  • Sandholdt H; Section of General Practice, Department of Public Health and Research Unit for General Practice, University of Copenhagen, Denmark.
  • Siersma V; Section of General Practice, Department of Public Health and Research Unit for General Practice, University of Copenhagen, Denmark.
  • Kragstrup J; Section of General Practice, Department of Public Health and Research Unit for General Practice, University of Copenhagen, Denmark.
  • Ellervik C; Department of Production, Research, and Innovation, Region Zealand, Sorø, Denmark; Department of Laboratory Medicine, Boston Children's Hospital & Harvard Medical School, Boston, MA, USA; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark.
Prim Care Diabetes ; 12(1): 13-22, 2018 02.
Article em En | MEDLINE | ID: mdl-28964672
AIMS: To investigate how self-reported risk factors (including socioeconomic status) predict undiagnosed, prevalent type 2 diabetes mellitus (T2DM). To externally validate Leicester Risk Assessment Score (LRAS), Finnish Diabetes Risk Score (FINDRISC) and Danish Diabetes Risk Score (DDRS), and to investigate how these predict a European Heart SCORE≥5% in a Danish population study. METHODS: We included 21,205 adults from the Danish General Suburban Population Study. We used relative importance calculations of self-reported variables in prediction of undiagnosed T2DM. We externally validated established prediction models reporting ROC-curves for undiagnosed T2DM, pre-diabetes and SCORE. RESULTS: More than 20% of people with T2DM were undiagnosed. The 7 most important self-rated predictors in sequential order were high BMI, antihypertensive-therapy, age, cardiovascular disease, waist-circumference, fitness compared to peers and family disposition for T2DM. The Area Under the Curve for prediction of undiagnosed T2DM was 77.1 for LRAS; 75.4 for DDRS and 67.9 for FINDRISC. AUCs for SCORE was 75.1 for LRAS; 62.3 for DDRS and 54.3 for FINDRISC. CONCLUSIONS: BMI and self-reported cardiovascular disease are important risk factors for undiagnosed T2DM. LRAS performed better than DDRS and FINDRISC in prediction of undiagnosed T2DM and SCORE≥5%. SCORE performed best in predicting pre-diabetes.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Estado Pré-Diabético / Fatores Socioeconômicos / Saúde Suburbana / Diabetes Mellitus Tipo 2 / Autorrelato Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Estado Pré-Diabético / Fatores Socioeconômicos / Saúde Suburbana / Diabetes Mellitus Tipo 2 / Autorrelato Idioma: En Ano de publicação: 2018 Tipo de documento: Article