Literature DB >> 32233598

Former gestational diabetes: Mathematical modeling of intravenous glucose tolerance test for the assessment of insulin clearance and its determinants.

Micaela Morettini1, Christian Göbl2, Alexandra Kautzky-Willer3, Giovanni Pacini4, Andrea Tura4, Laura Burattini1.   

Abstract

Women with a previous history of gestational diabetes mellitus (GDM) have increased risk of developing GDM in future pregnancies (i.e. recurrent GDM) and also Type 2 Diabetes (T2D). Insulin clearance represents one of the processes regulating glucose tolerance but has been scarcely investigated for its possible impairment in high-risk subjects. The aim of this study was to identify possible determinants of insulin clearance in women with a previous history of GDM. A detailed model-based analysis of a regular 3-hour, insulin-modified intravenous glucose tolerance test (IM-IVGTT) has been performed in women with a previous history of GDM (pGDM, n = 115) and in women who had a healthy pregnancy (CNT, n = 41) to assess total, first-phase and second-phase insulin clearance (ClINS-TOT, ClINS-FP and ClINS-SP) and other metabolic parameters (insulin sensitivity SI, glucose effectiveness SG, beta-cell function and disposition index DI). CLINS-SP was found increased in pGDM with respect to CNT and was found significantly inversely linearly correlated with SG (r = -0.20, p = 0.03, slope: -16.2, 95% CI -30.9 to -1.4, intercept: 1.1, 95% CI 0.7-1.4) and also with DI (r = -0.22, p = 0.02, slope: -10.0, 95% CI -18.5 to -1.6, intercept: 0.9, 95% CI 0.7-1.3). Disposition index, accounting for the combined contribution of insulin sensitivity and beta-cell function, and glucose effectiveness were identified as possible determinants of insulin clearance in women with a previous history of GDM. This may be of relevance for more accurate estimation and prevention of the risk for recurrent GDM and T2D.

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Keywords:  C-peptide ; Liver metabolism ; deconvolution ; insulin extraction ; mathematical model ; pregnancy-induced diabetes ; type 2 diabetes risk

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Year:  2019        PMID: 32233598     DOI: 10.3934/mbe.2020084

Source DB:  PubMed          Journal:  Math Biosci Eng        ISSN: 1547-1063            Impact factor:   2.080


  1 in total

1.  Unraveling the Factors Determining Development of Type 2 Diabetes in Women With a History of Gestational Diabetes Mellitus Through Machine-Learning Techniques.

Authors:  Ludovica Ilari; Agnese Piersanti; Christian Göbl; Laura Burattini; Alexandra Kautzky-Willer; Andrea Tura; Micaela Morettini
Journal:  Front Physiol       Date:  2022-02-17       Impact factor: 4.566

  1 in total

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