Literature DB >> 19021089

Tools for predicting the risk of type 2 diabetes in daily practice.

P E H Schwarz1, J Li, J Lindstrom, J Tuomilehto.   

Abstract

The discussion about the diagnosis and treatment of type 2 diabetes - and, more generally, dysglycaemia - should be framed in terms of a continuum of risk. A variety of tools have been developed to identify individuals with an increased risk of developing type 2 diabetes and to quantify the probability of type 2 diabetes either cross-sectionally or prospectively. Such scores are based on traditional risk factors for diabetes, such as age, body mass index (BMI), and family history, while others also evaluate metabolic risk factors such as lipid levels. The performance of a diabetes risk-prediction tool is generally assessed by measuring its accuracy, availability, practicability, and costs. This review discusses the validity and use of today's available major risk-prediction tools for clinical practice, and assesses the scope and cost-effectiveness of available tools. Among these prediction tools, American Diabetes Association (ADA) Risk Tools, Finnish Diabetes Risk Score (FINDRISC), National Health and Nutrition Examination Survey (NHANES) Risk Score, and Study to Prevent Non-Insulin Dependents Diabetes Mellitus (STOP-NIDDM) Risk Score were of our concern. We conclude that the FINDRISC tool is currently the best available tool for use in clinical practice in Caucasian populations, but modifications may be required if applied to other ethnic groups.

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Year:  2008        PMID: 19021089     DOI: 10.1055/s-0028-1087203

Source DB:  PubMed          Journal:  Horm Metab Res        ISSN: 0018-5043            Impact factor:   2.936


  67 in total

Review 1.  Prevention of type 2 diabetes: the strategic approach for implementation.

Authors:  P E H Schwarz; A L Albright
Journal:  Horm Metab Res       Date:  2011-12-07       Impact factor: 2.936

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3.  [Screening and prevention of diabetes].

Authors:  P E H Schwarz
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Journal:  J Diabetes Sci Technol       Date:  2009-07-01

Review 5.  Computational intelligence in early diabetes diagnosis: a review.

Authors:  Devang Odedra; Subir Samanta; Ambarish S Vidyarthi
Journal:  Rev Diabet Stud       Date:  2011-02-10

6.  Effect of familial diabetes status and age at diagnosis on type 2 diabetes risk: a nation-wide register-based study from Denmark.

Authors:  Omar Silverman-Retana; Adam Hulman; Jannie Nielsen; Claus T Ekstrøm; Bendix Carstensen; Rebecca K Simmons; Lasse Bjerg; Luke W Johnston; Daniel R Witte
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Journal:  AIDS       Date:  2018-11-28       Impact factor: 4.177

8.  Improvements in ability to detect undiagnosed diabetes by using information on family history among adults in the United States.

Authors:  Quanhe Yang; Tiebin Liu; Rodolfo Valdez; Ramal Moonesinghe; Muin J Khoury
Journal:  Am J Epidemiol       Date:  2010-04-25       Impact factor: 4.897

9.  Cross-sectional validation of diabetes risk scores for predicting diabetes, metabolic syndrome, and chronic kidney disease in Taiwanese.

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10.  Validation of a type 2 diabetes screening tool in rural Honduras.

Authors:  Evan C Milton; William H Herman; Allison E Aiello; Kris R Danielson; Milton O Mendoza-Avelarez; John D Piette
Journal:  Diabetes Care       Date:  2009-11-16       Impact factor: 19.112

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