Prediction of Diabetes Based on Baseline Metabolic Characteristics in Individuals at High Risk
Year: 2013
Type: article
Abstract: OBJECTIVE: Individuals with impaired glucose tolerance (IGT) are at high risk for developing type 2 diabetes mellitus (T2DM). We examined which characteristics at baseline predicted the development of T2DM versus maintenance of IGT or conversion to normal glucose tolerance. RESEARCH DESIGN AND METHODS: We studied 228 subjects at high risk with IGT who received treatment with placebo in ACT NOW and who underwent baseline anthropometric measures and oral glucose tolerance test (OGTT) at baseline and after a mean follow-up of 2.4 years. RESULTS: In a univariate analysis, 45 of 228 (19.7%) IGT individuals developed diabetes. After adjusting for age, sex, and center, increased fasting plasma glucose, 2-h plasma glucose, G0-120 during OGTT, HbA1c, adipocyte insulin resistance index, ln fasting plasma insulin, and ln I0-120, as well as family history of diabetes and presence of metabolic syndrome, were associated with increased risk of diabetes. At baseline, higher insulin secretion (ln [I0-120/G0-120]) during the OGTT was associated with decreased risk of diabetes. Higher β-cell function (insulin secretion/insulin resistance or disposition index; ln [I0-120/G0-120 × Matsuda index of insulin sensitivity]; odds ratio 0.11; P < 0.0001) was the variable most closely associated with reduced risk of diabetes. CONCLUSIONS: In a stepwise multiple-variable analysis, only HbA1c and β-cell function (ln insulin secretion/insulin resistance index) predicted the development of diabetes (r = 0.49; P < 0.0001).
Source: Diabetes Care
DOI: 10.2337/dc13-0520
Institutions: The University of Texas at San Antonio Health Science Center, Texas Diabetes Institute, Phoenix VA Health Care System, Arizona State University, SUNY Downstate Health Sciences University, Pennington Biomedical Research Center, Louisiana State University, University of Southern California, Georgetown University, University of California San Diego, VA San Diego Healthcare System, University of Tennessee Health Science Center, MedStar Health Research Institute, Istituto di Fisiologia Clinica
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W2164364203
