Cited by 384Diabetes, Cardiovascular Risks, and LipoproteinsAdipokines, Inflammation, and Metabolic DiseasesPancreatic function and diabetes

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Identification of Individuals With Insulin Resistance Using Routine Clinical Measurements

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Stern, Steven E., Williams, Ken, Ferrannini, Eleuterio, DeFronzo, Ralph A., Bogardus, Clifton, Stern, Michael P.·2005·Diabetes

DOI 10.2337/diabetes.54.2.333

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Abstract

Insulin resistance is a treatable precursor of diabetes and potentially of cardiovascular disease as well. To identify insulin-resistant patients, we developed decision rules from measurements of obesity, fasting glucose, insulin, lipids, and blood pressure and family history in 2,321 (2,138 nondiabetic) individuals studied with the euglycemic insulin clamp technique at 17 European sites; San Antonio, Texas; and the Pima Indian reservation. The distribution of whole-body glucose disposal appeared to be bimodal, with an optimal insulin resistance cutoff of <28 μmol/min · kg lean body mass. Using recursive partitioning, we developed three types of classification tree models: the first, based on clinical measurements and all available laboratory determinations, had an area under the receiver operator characteristic curve (aROC) of 90.0% and generated a simple decision rule: diagnose insulin resistance if any of the following conditions are met: BMI >28.9 kg/m2, homeostasis model assessment of insulin resistance (HOMA-IR) >4.65, or BMI >27.5 kg/m2 and HOMA-IR >3.60. The fasting serum insulin concentrations corresponding to these HOMA-IR cut points were 20.7 and 16.3 μU/ml, respectively. This rule had a sensitivity and specificity of 84.9 and 78.7%, respectively. The second model, which included clinical measurements but no laboratory determinations, had an aROC of 85.0% and generated a decision rule that had a sensitivity and specificity of 78.7 and 79.6%, respectively. The third model, which included clinical measurements and lipid measurements but not insulin (and thus excluded HOMA-IR as well), had a similar aROC (85.1%), sensitivity (81.3%), and specificity (76.3%). Thus, insulin-resistant individuals can be identified using simple decision rules that can be tailored to specific needs.

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Homeostasis model assessment: insulin resistance and ?-cell function from fasting plasma glucose and insulin concentrations in man
Matthews, D. R., Hosker, J. P., Rudenski, A. S., Naylor, B. A., Treacher, D. F., & Turner, R. C. (1985) · Diabetologia · doi:10.1007/bf00280883 · Cited by 31,502
Modern Applied Statistics with S
Venables, W. N., & Ripley, B. D. (2002) · Statisctics and computing/Statistics and computing · doi:10.1007/978-0-387-21706-2 · Cited by 25,941
Classification and Regression Trees.
Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984) · Biometrics · doi:10.2307/2530946 · Cited by 23,867
Classification and Regression Trees.
Ryzin, J. V., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1986) · Journal of the American Statistical Association · doi:10.2307/2288003 · Cited by 21,030
Role of Insulin Resistance in Human Disease
Reaven, G. M. (1988) · Diabetes · doi:10.2337/diab.37.12.1595 · Cited by 12,154
Glucose clamp technique: a method for quantifying insulin secretion and resistance.
DeFronzo, R. A., Tobin, J. D., & Andres, R. (1979) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.1979.237.3.e214 · Cited by 7,425
Self-citation
Insulin Resistance: A Multifaceted Syndrome Responsible for NIDDM, Obesity, Hypertension, Dyslipidemia, and Atherosclerotic Cardiovascular Disease
DeFronzo, R. A., & Ferrannini, E. (1991) · Diabetes Care · doi:10.2337/diacare.14.3.173 · Cited by 4,555
Self-citation
Banting lecture 1988. Role of insulin resistance in human disease.
Reaven, G. (1988) · Diabetes · doi:10.2337/diabetes.37.12.1595 · Cited by 3,801
Statistical Models in S
Chambers, J. M., Hastie, T. J., & Pregibon, D. (1990) · Physica-Verlag eBooks · doi:10.1007/978-3-642-50096-1_48 · Cited by 1,784
Relation of central obesity and insulin resistance with high diabetes prevalence and cardiovascular risk in South Asians
McKeigue, P. M., Shah, B., & Marmot, M. G. (1991) · The Lancet · doi:10.1016/0140-6736(91)91164-p · Cited by 1,618

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Self-citation
Identification of Insulin Resistance in Subjects with Normal Glucose Tolerance
Lin, J. D., Chang, J., Wu, C., Pei, D., Hsieh, C. H., Hsieh, A., Chen, Y., Hsu, C. H., & Liu, C. C. (2014) · Annals of the Academy of Medicine Singapore · doi:10.47102/annals-acadmedsg.v43n2p113 · Cited by 12
Identifying measurement-based care practices of VHA co-located collaborative care providers.
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Authors: Stern, S. E., Williams, K., Ferrannini, E., DeFronzo, R. A., Bogardus, C., & Stern, M. P.
Affiliations: Australian National University (AU)
The University of Texas at San Antonio Health Science Center (US)
Istituto di Fisiologia Clinica (IT)
National Institutes of Health (US)
Division of Clinical Epidemiology, Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, Texas
ORCID: Stern, Steven E.
DeFronzo, Ralph A.
Bogardus, Clifton
Venue: Diabetes
Publisher: American Diabetes Association
Published: 2005-02-01
Volume: 54
Issue: 2
Pages: 333-339
ISSN: 0012-1797 (ISSN-L)
1939-327X
DOI: 10.2337/diabetes.54.2.333
OpenAlex: W2151716502
Semantic Scholar: 4e8c3e8e3b4db413e21a0acf7ac1a349884ba391
Cited by: 384
References: 30
Citations by year: 2026: 2 · 2025: 9 · 2024: 19 · 2023: 7 · 2022: 19 · 2021: 10 · 2020: 18 · 2019: 14 · 2018: 27 · 2017: 19 · 2016: 21 · 2015: 29 · 2014: 21 · 2013: 19 · 2012: 22
FWCI: 13.45
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: Diabetes (publishedVersion)
PubMed (publishedVersion)
CINECA IRIS Institutial research information system (University of Pisa) (submittedVersion)
ANU Open Research (Australian National University) (submittedVersion)
Funders: American Diabetes Association
Topics: Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Pancreatic function and diabetes
Keywords: insulin resistance, diabetes prevention, cardiovascular risk, HOMA-IR, decision rules, classification trees, obesity, body mass index, fasting insulin, glucose disposal, hyperinsulinemic-euglycemic clamp, sensitivity and specificity, Pima Indians
MeSH terms: Blood Glucose, Homeostasis, Humans, Hyperinsulinism, Insulin, Insulin Resistance, Glucose Clamp Technique

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Identification of Individuals With Insulin Resistance Using Routine Clinical Measurements

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