Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.

By A. Katz, Sridhar S. Nambi, K. Mather, Alain D Baron, D. Follmann, G. Sullivan, M. Quon. Journal of Clinical Endocrinology and Metabolism, 2000

3,979 citations recorded by the source corpus.

Insulin resistance plays an important role in the pathophysiology of diabetes and is associated with obesity and other cardiovascular risk factors. The "gold standard" glucose clamp and minimal model analysis are two established methods for determining insulin sensitivity in vivo, but neither is easily implemented in large studies. Thus, it is of interest to develop a simple, accurate method for assessing insulin sensitivity that is useful for clinical investigations. We performed both hyperinsulinemic isoglycemic glucose clamp and insulin-modified frequently sampled iv glucose tolerance tests on 28 nonobese, 13 obese, and 15 type 2 diabetic subjects. We obtained correlations between indexes of insulin sensitivity from glucose clamp studies (SI(Clamp)) and minimal model analysis (SI(MM)) that were comparable to previous reports (r = 0.57). We performed a sensitivity analysis on our data and discovered that physiological steady state values [i.e. fasting insulin (I(0)) and glucose (G(0))] contain critical information about insulin sensitivity. We defined a quantitative insulin sensitivity check index (QUICKI = 1/[log(I(0)) + log(G(0))]) that has substantially better correlation with SI(Clamp) (r = 0.78) than the correlation we observed between SI(MM) and SI(Clamp). Moreover, we observed a comparable overall correlation between QUICKI and SI(Clamp) in a totally independent group of 21 obese and 14 nonobese subjects from another institution. We conclude that QUICKI is an index of insulin sensitivity obtained from a fasting blood sample that may be useful for clinical research.

Subfields: Endocrinology, Diabetes and Metabolism, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/d211fb4e1bf333f20b976d255c8b78c76a475417

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Endocrinology, Diabetes and Metabolism

1. C. Day
2. S. Bellentani
3. L. Sidossis
4. M. Quon
5. E. Ford
6. S. Grundy

In Molecular Biology

1. L. Sidossis

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