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Defining Insulin Resistance From Hyperinsulinemic-Euglycemic Clamps

2012; American Diabetes Association; Volume: 35; Issue: 7 Linguagem: Inglês

10.2337/dc11-2339

1935-5548

Charmaine S. Tam, Wenting Xie, William D. Johnson, William T. Cefalu, Leanne M. Redman, Éric Ravussin,

Metabolism, Diabetes, and Cancer

OBJECTIVE This study was designed to determine a cutoff point for identifying insulin resistance from hyperinsulinemic-euglycemic clamp studies performed at 120 mU/m2 ⋅ min in a white population and to generate equations from routinely measured clinic and blood variables for predicting clamp-derived glucose disposal rate (GDR), i.e., insulin sensitivity. RESEARCH DESIGN AND METHODS We assembled data from hyperinsulinemic-euglycemic clamps (120 mU/m2 ⋅ min insulin dose) performed at the Pennington Biomedical Research Center between 2001 and 2011. Subjects were divided into subjects with diabetes (n = 51) and subjects without diabetes (n = 116) by self-report and/or fasting glucose ≥126 mg/dL. RESULTS We found that 75% of individuals with a GDR <5.6 mg/kg fat-free mass (FFM) + 17.7 ⋅ min were truly insulin resistant. Cutoff values for GDRs normalized for body weight, body surface area, or FFM were 4.9 mg/kg ⋅ min, 212.2 mg/m2 ⋅ min, and 7.3 mg/kgFFM ⋅ min, respectively. Next, we used classification tree models to predict GDR from routinely measured clinical and biochemical variables. We found that individual insulin resistance could be estimated with good sensitivity (89%) and specificity (67%) from the homeostasis model assessment of insulin resistance (HOMA-IR) >5.9 or 2.8< HOMA-IR <5.9 with HDL <51 mg/dL. CONCLUSIONS We developed a cutoff for defining insulin resistance from hyperinsulinemic-euglycemic clamps. Moreover, we now provide classification trees for predicting insulin resistance from routinely measured clinical and biochemical markers. These findings extend the clamp from a research tool to providing a clinically meaningful message for participants in research studies, potentially providing greater opportunity for earlier recognition of insulin resistance.