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.
When the body responds to an infectious insult, it initiates an immune response to eliminate the pathogen. The hallmark of the immune response is an inflammatory cascade that can also do extensive damage to host tissues. Inflammation is a major contributing factor to many vascular events, including atherosclerotic plaque development and rupture, aortic aneurysm formation, angiogenesis, and ischemia/reperfusion damage. The immune response is mediated by both circulating and resident leukocytes and the cells with which they interact (e.g., vascular endothelium and smooth muscle cells). The process is orchestrated by the activity of a changing series of released and displayed mediators. These include the expression of adhesion molecules on leukocytes and underlying vascular endothelium and the release of cytokines, chemokines, and tissue-destructive metalloproteases and reactive oxygen species. This review focuses on the causes, the inflammatory processes involved, and possible strategies for decreasing vascular disease through regulation of the inflammatory response.
The quantitative insulin-sensitivity check index (QUICKI) has an excellent linear correlation with the glucose clamp index of insulin sensitivity (SI Clamp ) that is better than that of many other surrogate indexes. However, correlation between a surrogate and reference standard may improve as variability between subjects in a cohort increases (i.e., with an increased range of values). Correlation may be excellent even when prediction of reference values by the surrogate is poor. Thus, it is important to evaluate the ability of QUICKI to accurately predict insulin sensitivity as determined by the reference glucose clamp method. In the present study, we used a calibration model to compare the ability of QUICKI and other simple surrogates to predict SI Clamp . Predictive accuracy was evaluated by both root mean squared error of prediction as well as a more robust leave-one-out cross-validation-type root mean squared error of prediction (CVPE). Based on data from 116 glucose clamps obtained from nonobese, obese, type 2 diabetic, and hypertensive subjects, we found that QUICKI and log (homeostasis model assessment [HOMA]) were both excellent at predicting SI Clamp (CVPE ؍ 1.45 and 1.51, respectively) and significantly better than HOMA, 1/HOMA, and fasting insulin (CVPE ؍ 3.17, P < 0.001; 1.67, P < 0.02; and 2.85, P < 0.001, respectively). QUICKI and log(HOMA) also had the narrowest distribution of residuals (measured SI Clamp ؊ predicted SI Clamp ). In a subset of subjects (n ؍ 78) who also underwent a frequently sampled intravenous glucose tolerance test with minimal model analysis, QUICKI was significantly better than the minimal model index of insulin sensitivity (SI MM ) at predicting SI Clamp (CVPE ؍ 1.54 vs. 1.98, P ؍ 0.001). We conclude that QUICKI and log(HOMA) are among the most accurate surrogate indexes for determining insulin sensitivity in humans. Diabetes 54: 1914 -1925, 2005 I nsulin resistance contributes significantly to the pathophysiology of type 2 diabetes and is a hallmark of obesity, dyslipidemias, hypertension, and other components of the metabolic syndrome (rev. in 1,2). Some therapies for these conditions, including thiazoladinediones, ACE inhibitors, statins, weight reduction, and exercise, significantly improve insulin sensitivity (3-8). Thus, an accurate method for easily evaluating insulin sensitivity and following changes after therapeutic intervention is needed for epidemiological studies, clinical investigations, and clinical practice. The hyperinsulinemiceuglycemic glucose clamp is the reference method for quantifying insulin sensitivity in humans because it directly measures effects of insulin to promote glucose utilization under steady-state conditions in vivo (9). However, the glucose clamp is a complicated, labor-intensive procedure best suited for small research studies that is difficult to apply in either large-scale investigations or clinical practice. Therefore, a number of surrogate indexes for insulin sensitivity or insulin resistance have been developed. The s...
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