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Defining Insulin Resistance From Hyperinsulinemic-Euglycemic Clamps.

Authors :
Tam, Charmaine S.
Xie, Wenting
Johnson, William D.
Cefalu, William T.
Redman, Leanne M.
Ravussin, Eric
Source :
Diabetes Care. Jul2012, Vol. 35 Issue 7, p1605-1610. 6p. 2 Diagrams, 2 Charts.
Publication Year :
2012

Abstract

OBJECTIVE--This study was designed to determine a cutoff point for identifying insulin resistance from hyperinsulinemic-euglycemic clamp studies performed at 120 mU/m² z 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 z 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 homeostasismodel 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01495992
Volume :
35
Issue :
7
Database :
Academic Search Index
Journal :
Diabetes Care
Publication Type :
Academic Journal
Accession number :
77369443
Full Text :
https://doi.org/10.2337/dc11-2339