QUICKI is a useful index of insulin sensitivity in subjects with hypertension. Am J Physiol Endocrinol Metab 284: E804-E812, 2003. First published January 7, 2003 10.1152/ajpendo.00330.2002-Insulin resistance may link disorders of metabolic homeostasis such as diabetes and obesity with disorders of hemodynamic homeostasis such as hypertension. Thus it is of interest to validate simple methods for quantifying insulin sensitivity in hypertensive patients. The quantitative insulin-sensitivity check index (QUICKI) is a novel mathematical transformation of fasting blood glucose and insulin levels. In obese and diabetic subjects, QUICKI has a significantly better linear correlation with glucose clamp determinations of insulin sensitivity than minimal-model estimates. To determine whether QUICKI is also useful in hypertensive subjects, we performed glucose clamps and frequently sampled intravenous glucose tolerance tests (FSIVGTT) on 27 hypertensive subjects taken off antihypertensive medication. Indexes of insulin sensitivity derived from glucose clamp studies (SI Clamp) were compared with QUICKI, minimal-model analysis of FSIVGTTs (SIMM), and homeostasis model assessment (HOMA). The correlation between QUICKI and SIClamp (r ϭ 0.84) was significantly better than that between SIMM and SIClamp (r ϭ 0.65; P Ͻ 0.028). The correlation between QUICKI and SIClamp was comparable to that between 1/HOMA and SIClamp (r ϭ 0.82). When studies were repeated in 14 subjects who had resumed antihypertensive medications, the percent changes in SIClamp for each of these patients were significantly correlated with percent changes in QUICKI (r ϭ 0.61) and HOMA (r ϭ Ϫ0.54) but not SIMM (r ϭ Ϫ0.18). We conclude that QUICKI is a simple, robust index of insulin sensitivity that is useful for evaluating and following the insulin resistance of hypertensive subjects in both research studies and clinical practice. insulin resistance; diabetes; glucose clamp INSULIN RESISTANCE IS A PROMINENT FEATURE of essential hypertension and other cardiovascular diseases (8,15,16,36). Insulin-signaling mechanisms in vascular endothelium-mediating increased production of nitric oxide with subsequent vasodilation and increased blood flow (30, 43, 44) share many features in common with insulin-signaling pathways in skeletal muscle and adipose tissue that promote increased glucose disposal (31, 32). Thus hemodynamic and metabolic homeostasis may be coupled with insulin action in the vasculature. Moreover, insulin resistance may provide a pathophysiological link among hypertension, diabetes, and obesity (22,31). Recent evidence suggests that there is a shared genetic component underlying both hypertension and insulin resistance that is independent of obesity (42). In addition, hypertension greatly increases the risk of developing other vascular complications of diabetes (40). Given the importance of hypertension as a public health problem and the potential contribution of insulin resistance to the pathophysiology of hypertension, it is of great interest to establish...
Insulin resistance contributes to the pathophysiology of diabetes, obesity, and their cardiovascular complications. Mouse models of these human diseases are useful for gaining insight into pathophysiological mechanisms. The reference standard for measuring insulin sensitivity in both humans and animals is the euglycemic glucose clamp. Many studies have compared surrogate indexes of insulin sensitivity and resistance with glucose clamp estimates in humans. However, regulation of metabolic physiology in humans and rodents differs and comparisons between surrogate indexes and the glucose clamp have not been directly evaluated in rodents previously. Therefore, in the present study, we compared glucose clamp-derived measures of insulin sensitivity (GIR and SI(Clamp)) with surrogate indexes, including quantitative insulin-sensitivity check index (QUICKI), homeostasis model assessment (HOMA), 1/HOMA, log(HOMA), and 1/fasting insulin, using data from 87 mice with a wide range of insulin sensitivities. We evaluated simple linear correlations and performed calibration model analyses to evaluate the predictive accuracy of each surrogate. All surrogate indexes tested were modestly correlated with both GIR and SI(Clamp). However, a stronger correlation between body weight per se and both GIR and SI(Clamp) was noted. Calibration analyses of surrogate indexes adjusted for body weight demonstrated improved predictive accuracy for GIR [e.g., R = 0.68, for QUICKI and log(HOMA)]. We conclude that linear correlations of surrogate indexes with clamp data and predictive accuracy of surrogate indexes in mice are not as substantial as in humans. This may reflect intrinsic differences between human and rodent physiology as well as increased technical difficulties in performing glucose clamps in mice.
In comparison to treatment with human insulin 30/70, twice daily administration of Humalog Mix25 resulted in improved postprandial glycemic control, similar overall glycemic control, and the convenience of dosing immediately before meals.
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