Literature DB >> 16899806

Fasting-based estimates of insulin sensitivity in overweight and obesity: a critical appraisal.

Johannes B Ruige1, Ilse L Mertens, Ellen Bartholomeeusen, Eveline Dirinck, Ele Ferrannini, Luc F Van Gaal.   

Abstract

OBJECTIVE: To identify simple methods to estimate the degree of insulin resistance. RESEARCH METHODS AND PROCEDURES: The performance of a wide range of fasting-based index estimates of insulin sensitivity was compared by receiver operating characteristic analysis (area under curves and their 95% confidence intervals) against the M value from euglycemic insulin clamp studies collected in the San Antonio (non-Hispanic whites and Hispanic residents of San Antonio, TX) and European Group for the Study of Insulin Resistance (non-diabetic white Europeans) databases (n = 638).
RESULTS: Insulin resistance differed substantially between lean (BMI < 25 kg/m2), overweight or obese (BMI > or = 25 kg/m2), and type 2 diabetic individuals. Estimates of insulin resistance were, therefore, assessed in each group separately. In the overweight and obese subgroup (n = 302), the receiver operating characteristic performance of fasting-based indices varied from 0.72 (0.62 to 0.82), in the case of the insulin/glucose ratio, to 0.80 (0.72 to 0.88) in the case of Belfiore free fatty acids. One superior method could not be identified; the confidence intervals overlapped, and no statistically significant differences emerged. All indices performed better when using the whole study population, with fasting plasma insulin, homeostatic model assessment, insulin/glucose ratio, quantitative insulin sensitivity check index, glucose/insulin ratio, Belfiore glycemia, revised quantitative insulin sensitivity check index, McAuley index, and Belfiore free fatty acids showing area under curves of 0.83, 0.90, 0.66, 0.90, 0.66, 0.90, 0.85, 0.83, and 0.86, respectively, because of the inclusion of very insulin sensitive (lean) and very insulin resistant cases (diabetic subjects). DISCUSSION: In conclusion, a superior fasting-based index estimate to distinguish between the presence and absence of insulin resistance in overweight and obesity could not be identified despite the use of the large datasets.

Entities:  

Mesh:

Substances:

Year:  2006        PMID: 16899806     DOI: 10.1038/oby.2006.142

Source DB:  PubMed          Journal:  Obesity (Silver Spring)        ISSN: 1930-7381            Impact factor:   5.002


  8 in total

Review 1.  Risk factors preceding type 2 diabetes and cardiomyopathy.

Authors:  Shamjeet Singh; Sanjiv Dhingra; Dan D Ramdath; Sudesh Vasdev; Vicki Gill; Pawan K Singal
Journal:  J Cardiovasc Transl Res       Date:  2010-07-01       Impact factor: 4.132

2.  Comparison between surrogate indexes of insulin sensitivity/resistance and hyperinsulinemic euglycemic glucose clamps in rhesus monkeys.

Authors:  Ho-Won Lee; Ranganath Muniyappa; Xu Yan; Lilly Q Yue; Ellen H Linden; Hui Chen; Barbara C Hansen; Michael J Quon
Journal:  Endocrinology       Date:  2011-01-05       Impact factor: 4.736

3.  Limited predictive ability of surrogate indices of insulin sensitivity/resistance in Asian-Indian men.

Authors:  Ranganath Muniyappa; Brian A Irving; Uma S Unni; William M Briggs; K Sreekumaran Nair; Michael J Quon; Anura V Kurpad
Journal:  Am J Physiol Endocrinol Metab       Date:  2010-10-13       Impact factor: 4.310

4.  Association of nocturnal melatonin secretion with insulin resistance in nondiabetic young women.

Authors:  Ciaran J McMullan; Gary C Curhan; Eva S Schernhammer; John P Forman
Journal:  Am J Epidemiol       Date:  2013-06-28       Impact factor: 4.897

5.  Insulin resistance.

Authors:  Alan R Sinaiko; Sonia Caprio
Journal:  J Pediatr       Date:  2012-02-14       Impact factor: 4.406

6.  Limitations of insulin resistance assessment in polycystic ovary syndrome.

Authors:  Krzysztof C Lewandowski; Justyna Płusajska; Wojciech Horzelski; Ewa Bieniek; Andrzej Lewiński
Journal:  Endocr Connect       Date:  2018-02-07       Impact factor: 3.335

7.  Evaluation of surrogate measures of insulin sensitivity - correlation with gold standard is not enough.

Authors:  Anna Rudvik; Marianne Månsson
Journal:  BMC Med Res Methodol       Date:  2018-06-26       Impact factor: 4.615

8.  Predictive worth of estimated glucose disposal rate: evaluation in patients with non-ST-segment elevation acute coronary syndrome and non-diabetic patients after percutaneous coronary intervention.

Authors:  Chi Liu; Xiaoli Liu; Xiaoteng Ma; Yujing Cheng; Yan Sun; Dai Zhang; Qi Zhao; Yujie Zhou
Journal:  Diabetol Metab Syndr       Date:  2022-10-06       Impact factor: 5.395

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.