Insulin resistance contributes to the pathophysiology of diabetes and is a hallmark of obesity, metabolic syndrome, and many cardiovascular diseases. Therefore, quantifying insulin sensitivity/resistance in humans and animal models is of great importance for epidemiological studies, clinical and basic science investigations, and eventual use in clinical practice. Direct and indirect methods of varying complexity are currently employed for these purposes. Some methods rely on steady-state analysis of glucose and insulin, whereas others rely on dynamic testing. Each of these methods has distinct advantages and limitations. Thus, optimal choice and employment of a specific method depends on the nature of the studies being performed. Established direct methods for measuring insulin sensitivity in vivo are relatively complex. The hyperinsulinemic euglycemic glucose clamp and the insulin suppression test directly assess insulin-mediated glucose utilization under steady-state conditions that are both labor and time intensive. A slightly less complex indirect method relies on minimal model analysis of a frequently sampled intravenous glucose tolerance test. Finally, simple surrogate indexes for insulin sensitivity/resistance are available (e.g., QUICKI, HOMA, 1/insulin, Matusda index) that are derived from blood insulin and glucose concentrations under fasting conditions (steady state) or after an oral glucose load (dynamic). In particular, the quantitative insulin sensitivity check index (QUICKI) has been validated extensively against the reference standard glucose clamp method. QUICKI is a simple, robust, accurate, reproducible method that appropriately predicts changes in insulin sensitivity after therapeutic interventions as well as the onset of diabetes. In this Frontiers article, we highlight merits, limitations, and appropriate use of current in vivo measures of insulin sensitivity/resistance. glucose clamp; quantitative insulin sensitivity check index; minimal model; homeostatis model assessment Address for reprint requests and other correspondence: M. J. Quon, Diabetes Unit, NCCAM, NIH, 9 Memorial Drive, Bldg. 9, Rm. 1N-105 MSC 0920, Bethesda, MD 20892 (e-mail: firstname.lastname@example.org )
AJP - Endocrinology and Metabolism – The American Physiological Society
Published: Jan 1, 2008
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