Identification of Impaired Second-Phase Insulin Secretion in Various Degrees of Glucose Tolerance in a Chinese Population

Jiunn Diann Lin, Chung Ze Wu, Dee Pei, Wei Cheng Lian, Chun Hsien Hsu, Chang Hsun Hsieh, Yen Lin Chen

Research output: Contribution to journalArticle

Abstract

Aim: Impaired insulin sensitivity and insulin secretion (ISEC) are major pathophysiologies of type 2 diabetes (T2DM). ISEC has two phases: the first and second phases (second ISEC). In this study, we derived equations to identify patients with second ISEC deficiency (ISEC-D). Methods: Data from 96 patients, namely 19 with a normal fasting plasma glucose (FPG) level, 21 with prediabetes, and 56 with T2DM, were enrolled. They underwent a modified low-dose graded glucose infusion test, which was originally proposed by Polonsky et al. The test results were interpreted as the slopes of the changes of plasma insulin against the glucose levels, which were considered second ISEC. Patients with the lowest quartile of the slopes were defined as having ISEC-D. We built three models: Model 0: FPG, Model 1: FPG + waist circumference, and Model 2: Model 1 + fasting plasma insulin. The area under the receiver operating characteristic (aROC) curve was used to determine the predictive power of these models. Results: Among the metabolic syndrome components, FPG had the largest aROC curve (78.2%). Although aROC curves of Models 1 and 2 (85.2% and 91.5%, respectively) were higher than the aROC curve of FPG, no difference was observed between Models 1 and 0. By contrast, the aROC curve of Model 2 was higher compared with Model 1. Conclusions: FPG showed the largest aROC curve. Model 2 had the highest predictive power, which could identify patients with ISEC-D with a sensitivity and specificity of 94.3% and 82.6%, respectively. These two models could be conveniently used in daily practice.

Original languageEnglish
Pages (from-to)347-353
Number of pages7
JournalMetabolic Syndrome and Related Disorders
Volume14
Issue number7
DOIs
Publication statusPublished - Sep 1 2016

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Insulin
Fasting
Glucose
ROC Curve
Population
Prediabetic State
Waist Circumference
Type 2 Diabetes Mellitus
Insulin Resistance
Sensitivity and Specificity

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism

Cite this

Identification of Impaired Second-Phase Insulin Secretion in Various Degrees of Glucose Tolerance in a Chinese Population. / Lin, Jiunn Diann; Wu, Chung Ze; Pei, Dee; Lian, Wei Cheng; Hsu, Chun Hsien; Hsieh, Chang Hsun; Chen, Yen Lin.

In: Metabolic Syndrome and Related Disorders, Vol. 14, No. 7, 01.09.2016, p. 347-353.

Research output: Contribution to journalArticle

Lin, Jiunn Diann ; Wu, Chung Ze ; Pei, Dee ; Lian, Wei Cheng ; Hsu, Chun Hsien ; Hsieh, Chang Hsun ; Chen, Yen Lin. / Identification of Impaired Second-Phase Insulin Secretion in Various Degrees of Glucose Tolerance in a Chinese Population. In: Metabolic Syndrome and Related Disorders. 2016 ; Vol. 14, No. 7. pp. 347-353.
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abstract = "Aim: Impaired insulin sensitivity and insulin secretion (ISEC) are major pathophysiologies of type 2 diabetes (T2DM). ISEC has two phases: the first and second phases (second ISEC). In this study, we derived equations to identify patients with second ISEC deficiency (ISEC-D). Methods: Data from 96 patients, namely 19 with a normal fasting plasma glucose (FPG) level, 21 with prediabetes, and 56 with T2DM, were enrolled. They underwent a modified low-dose graded glucose infusion test, which was originally proposed by Polonsky et al. The test results were interpreted as the slopes of the changes of plasma insulin against the glucose levels, which were considered second ISEC. Patients with the lowest quartile of the slopes were defined as having ISEC-D. We built three models: Model 0: FPG, Model 1: FPG + waist circumference, and Model 2: Model 1 + fasting plasma insulin. The area under the receiver operating characteristic (aROC) curve was used to determine the predictive power of these models. Results: Among the metabolic syndrome components, FPG had the largest aROC curve (78.2{\%}). Although aROC curves of Models 1 and 2 (85.2{\%} and 91.5{\%}, respectively) were higher than the aROC curve of FPG, no difference was observed between Models 1 and 0. By contrast, the aROC curve of Model 2 was higher compared with Model 1. Conclusions: FPG showed the largest aROC curve. Model 2 had the highest predictive power, which could identify patients with ISEC-D with a sensitivity and specificity of 94.3{\%} and 82.6{\%}, respectively. These two models could be conveniently used in daily practice.",
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AU - Hsu, Chun Hsien

AU - Hsieh, Chang Hsun

AU - Chen, Yen Lin

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N2 - Aim: Impaired insulin sensitivity and insulin secretion (ISEC) are major pathophysiologies of type 2 diabetes (T2DM). ISEC has two phases: the first and second phases (second ISEC). In this study, we derived equations to identify patients with second ISEC deficiency (ISEC-D). Methods: Data from 96 patients, namely 19 with a normal fasting plasma glucose (FPG) level, 21 with prediabetes, and 56 with T2DM, were enrolled. They underwent a modified low-dose graded glucose infusion test, which was originally proposed by Polonsky et al. The test results were interpreted as the slopes of the changes of plasma insulin against the glucose levels, which were considered second ISEC. Patients with the lowest quartile of the slopes were defined as having ISEC-D. We built three models: Model 0: FPG, Model 1: FPG + waist circumference, and Model 2: Model 1 + fasting plasma insulin. The area under the receiver operating characteristic (aROC) curve was used to determine the predictive power of these models. Results: Among the metabolic syndrome components, FPG had the largest aROC curve (78.2%). Although aROC curves of Models 1 and 2 (85.2% and 91.5%, respectively) were higher than the aROC curve of FPG, no difference was observed between Models 1 and 0. By contrast, the aROC curve of Model 2 was higher compared with Model 1. Conclusions: FPG showed the largest aROC curve. Model 2 had the highest predictive power, which could identify patients with ISEC-D with a sensitivity and specificity of 94.3% and 82.6%, respectively. These two models could be conveniently used in daily practice.

AB - Aim: Impaired insulin sensitivity and insulin secretion (ISEC) are major pathophysiologies of type 2 diabetes (T2DM). ISEC has two phases: the first and second phases (second ISEC). In this study, we derived equations to identify patients with second ISEC deficiency (ISEC-D). Methods: Data from 96 patients, namely 19 with a normal fasting plasma glucose (FPG) level, 21 with prediabetes, and 56 with T2DM, were enrolled. They underwent a modified low-dose graded glucose infusion test, which was originally proposed by Polonsky et al. The test results were interpreted as the slopes of the changes of plasma insulin against the glucose levels, which were considered second ISEC. Patients with the lowest quartile of the slopes were defined as having ISEC-D. We built three models: Model 0: FPG, Model 1: FPG + waist circumference, and Model 2: Model 1 + fasting plasma insulin. The area under the receiver operating characteristic (aROC) curve was used to determine the predictive power of these models. Results: Among the metabolic syndrome components, FPG had the largest aROC curve (78.2%). Although aROC curves of Models 1 and 2 (85.2% and 91.5%, respectively) were higher than the aROC curve of FPG, no difference was observed between Models 1 and 0. By contrast, the aROC curve of Model 2 was higher compared with Model 1. Conclusions: FPG showed the largest aROC curve. Model 2 had the highest predictive power, which could identify patients with ISEC-D with a sensitivity and specificity of 94.3% and 82.6%, respectively. These two models could be conveniently used in daily practice.

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