Literature DB >> 18779039

The "metabolic syndrome" is less useful than random plasma glucose to screen for glucose intolerance.

Eman A El Bassuoni1, David C Ziemer, Paul Kolm, Mary K Rhee, Viola Vaccarino, Circe W Tsui, Jack M Kaufman, G Eileen Osinski, David D Koch, K M Venkat Narayan, William S Weintraub, Lawrence S Phillips.   

Abstract

AIMS: To compare the utility of metabolic syndrome (MetS) to random plasma glucose (RPG) in identifying people with diabetes or prediabetes.
METHODS: RPG was measured and an OGTT was performed in 1155 adults. Test performance was measured by area under the receiver-operating-characteristic curve (AROC).
RESULTS: Diabetes was found in 5.1% and prediabetes in 20.0%. AROC for MetS with fasting plasma glucose (FPG) was 0.80 to detect diabetes, and 0.76 for diabetes or prediabetes--similar to RPG alone (0.82 and 0.72). However, the AROC for MetS excluding fasting plasma glucose was lower: 0.69 for diabetes (p<0.01 vs. both RPG and MetS with FPG), and 0.69 for diabetes or prediabetes. AROCs for MetS with FPG and RPG were comparable and higher for recognizing diabetes in blacks vs. whites, and females vs. males. MetS with FPG was superior to RPG for identifying diabetes only in subjects with age <40 or BMI <25.
CONCLUSIONS: MetS features can be used to identify risk of diabetes, but predictive usefulness is driven largely by FPG. Overall, to identify diabetes or prediabetes in blacks and whites with varying age and BMI, MetS is no better than RPG--a more convenient and less expensive test.

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Year:  2008        PMID: 18779039      PMCID: PMC2638987          DOI: 10.1016/j.pcd.2008.04.005

Source DB:  PubMed          Journal:  Prim Care Diabetes        ISSN: 1878-0210            Impact factor:   2.459


  41 in total

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2.  Components of the metabolic syndrome and risk of cardiovascular disease and diabetes in Beaver Dam.

Authors:  Barbara E K Klein; Ronald Klein; Kristine E Lee
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3.  Predicting impaired glucose tolerance using common clinical information: data from the Third National Health and Nutrition Examination Survey.

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4.  A risk score for predicting incident diabetes in the Thai population.

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Journal:  Diabetes Care       Date:  2006-08       Impact factor: 19.112

5.  Identification of persons at high risk for type 2 diabetes mellitus: do we need the oral glucose tolerance test?

Authors:  Michael P Stern; Ken Williams; Steven M Haffner
Journal:  Ann Intern Med       Date:  2002-04-16       Impact factor: 25.391

6.  The metabolic syndrome: prevalence and associated risk factor findings in the US population from the Third National Health and Nutrition Examination Survey, 1988-1994.

Authors:  Yong-Woo Park; Shankuan Zhu; Latha Palaniappan; Stanley Heshka; Mercedes R Carnethon; Steven B Heymsfield
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7.  Contribution of abdominal adiposity to age-related differences in insulin sensitivity and plasma lipids in healthy nonobese women.

Authors:  W F DeNino; A Tchernof; I J Dionne; M J Toth; P A Ades; C K Sites; E T Poehlman
Journal:  Diabetes Care       Date:  2001-05       Impact factor: 19.112

8.  Detection of undiagnosed diabetes and other hyperglycemia states: the Atherosclerosis Risk in Communities Study.

Authors:  Maria Inês Schmidt; Bruce B Duncan; Alvaro Vigo; James Pankow; Christie M Ballantyne; David Couper; Frederick Brancati; Aaron R Folsom
Journal:  Diabetes Care       Date:  2003-05       Impact factor: 19.112

9.  Economic costs of diabetes in the US in 2002.

Authors:  Paul Hogan; Tim Dall; Plamen Nikolov
Journal:  Diabetes Care       Date:  2003-03       Impact factor: 19.112

Review 10.  Epidemiology of the metabolic syndrome, 2002.

Authors:  James B Meigs
Journal:  Am J Manag Care       Date:  2002-09       Impact factor: 2.229

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  3 in total

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Journal:  J Diabetes Sci Technol       Date:  2014-09-26

2.  Distribution of hyperglycaemia and related cardiovascular disease risk factors in low-income countries: a cross-sectional population-based survey in rural Uganda.

Authors:  Dermot Maher; Laban Waswa; Kathy Baisley; Alex Karabarinde; Nigel Unwin; Heiner Grosskurth
Journal:  Int J Epidemiol       Date:  2010-10-05       Impact factor: 7.196

Review 3.  Systematic Review and Meta-Analysis of Response Rates and Diagnostic Yield of Screening for Type 2 Diabetes and Those at High Risk of Diabetes.

Authors:  Kamlesh Khunti; Hamidreza Mani; Felix Achana; Nicola Cooper; Laura J Gray; Melanie J Davies
Journal:  PLoS One       Date:  2015-09-01       Impact factor: 3.240

  3 in total

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