1,751 research outputs found

    Why a Cluster is Truly a Cluster: Insulin Resistance and Cardiovascular Disease

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    The 2 major definitions of the metabolic syndrome (MetS) are based ondisparate views as to the etiology o

    Insulin resistance:Impact on therapeutic developments in diabetes

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    Insulin resistance has a broad pathogenic impact affecting metabolic, cardio-renal and other disease areas. Extensive studies to dissect the mechanisms of insulin resistance have provided valuable insights to shape current clinical awareness and advance therapeutic practice. However, the development of direct interventions against insulin resistance has been hindered by its complex and highly variable presentations, especially in type 2 diabetes. Among glucose-lowering agents, metformin and thiazolidinediones provide cellular actions that counter some effects of insulin resistance: reduced glucotoxicity and weight-lowering with antidiabetic therapies also improve insulin action, except that endogenously- or exogenously-created hyperinsulinaemia may partially compromise these benefits. Increasing awareness of the pervasiveness and damaging ramifications of insulin resistance heightens the need for more specifically targeted and more effective therapies

    Adipose Tissue Plasticity in Catch-Up–Growth Trajectories to Metabolic Syndrome: Hyperplastic Versus Hypertrophic Catch-Up Fat

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    In the mid-1980s, at a time when the concept ofsyndrome X was being introduced by Reaven (1)to draw attention to the cardiovascular risks as-sociated with insulin resistance and compensatory hyperinsulinemia, Tanner (2) was emphasizing a funda-mental property of human growth as a target-seeking function: Children, no less than rockets, have their trajectories, governed by control systems of their genetic constitution and powered by the energy absorbed from the environment. De-flect the child from its natural growth trajectory (by acute malnutrition or a sudden lack of a hormone), and a restoring force develops, so that as soon as the missing food or the absent hormone is supplied again, the child hastens to catch-up toward its original growth curve. When it gets there, the child slows again, to adjust its path onto the old trajectory once more. How the child does this we do not know. What was also unknown (and unforeseen) then was tha

    Comparison of two surrogate estimates of insulin resistance to predict cardiovascular disease in apparently healthy individuals

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    Background and aims: Insulin resistance is associated with a cluster of abnormalities that increase cardiovascular disease (CVD). Several indices have been proposed to identify individuals who are insulin resistant, and thereby at increased CVD risk. The aim of this study was to compare the abilities of 3 indices to accomplish that goal: 1) plasma triglyceride × glucose index (TG × G); 2) plasma triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-C); and 3) Metabolic Syndrome (MetS). Methods and results: In a population sample of 723 individuals (486 women and 237 men, 50 ± 16 and 51 ± 16 years old, respectively), baseline demographic and metabolic variables known to increase CVD risk and incident CVD were compared among individuals defined as high vs. low risk by: TG × G; TG/HDL-C; or MetS. CVD risk profiles appeared comparable in high risk subjects, irrespective of criteria. Crude incidence of CVD events was increased in high risk subjects: 12.2 vs. 5.3% subjects/10 years, p = 0.005 defined by TG/HDL-C; 13.4 vs. 5.3% subjects/10 years, p = 0.002 defined by TG × G; and 13.4% vs. 4.5% of subjects/10 years, p < 0.001 in subjects with the MetS. The area under the ROC curves to predict CVD were similar, 0.66 vs. 0.67 for TG/HDL-C and TG × G, respectively. However, when adjusted by age, sex and multiple covariates, hazard ratios for incident CVD were significantly increased in high risk patients classified by either TG/HDL-C ratio (2.18, p = 0.021) or MetS (1.93, p = 0.037), but not by TG × G index (1.72, p = 0.087). Conclusion: Although the 3 indices identify CVD risk comparably, the TG × G index seems somewhat less effective at predicting CVD.Facultad de Ciencias Médica
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