Literature DB >> 32098005

Response: Early Assessment of the Risk for Gestational Diabetes Mellitus: Can Fasting Parameters of Glucose Metabolism Contribute to Risk Prediction? (Diabetes Metab J 2019;43:785-93).

Christian S Göbl1, Andrea Tura2.   

Abstract

Entities:  

Year:  2020        PMID: 32098005      PMCID: PMC7043974          DOI: 10.4093/dmj.2020.0029

Source DB:  PubMed          Journal:  Diabetes Metab J        ISSN: 2233-6079            Impact factor:   5.376


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We appreciate the interest in our article and would like to thank the editor to give us the opportunity to respond to the thoughtful comments by Drs Yang und Jung. We agree that fasting (or static) indices of glucose metabolism, which were used in our study, cannot fully reflect the pathophysiology of gestational diabetes mellitus (GDM), although, these indices have some interesting properties [1]. Their major advantage is that they are easy to obtain by a simple blood sample at fasting condition; therefore, they are cheaper and less time consuming as compared to dynamic indices based on frequently sampled intravenous or oral glucose tolerance tests. Especially regarding the estimation of insulin sensitivity, a previous study concluded that static surrogate measures of insulin action appeared to be typically acceptable, and sometimes nearly as good as dynamic indices derived from the oral glucose tolerance test [2]. In line with these findings we observed that a modified quantitative insulin sensitivity check index (QUICKI) showed good properties to identify patients with risk for GDM and especially those with need of glucose lowering medications already at early gestation. As further pointed out by Drs Young and Jung the predictive power may be increased by using one variable representing both the amount of insulin sensitivity and secretion. This could be achieved by the disposition index (an index of β-cell secretion that accounts for insulin resistance), which is traditionally calculated as the product of insulin action and insulin secretion [3]. While this is an interesting idea, we have consciously not included a “modified” disposition index in our study due to several concerns as in detail reviewed by [4]. First, a correct calculation of the disposition index ideally would require that insulin sensitivity and secretion are calculated from different tests (i.e., that they are not intrinsically interdependent). This is generally not true if both indices are derived from fasting conditions as it was the case in our study. Second, the disposition index should assume a hyperbolic relationship between insulin action and secretion, which may not exist for indices derived from fasting condition. Finally, we agree with Drs Young and Jung that the potential clinical benefit of early interventions in women with high risk for GDM needs to be evaluated in prospective studies.
  4 in total

1.  Surrogate measures of insulin sensitivity vs the hyperinsulinaemic-euglycaemic clamp: a meta-analysis.

Authors:  Julia Otten; Bo Ahrén; Tommy Olsson
Journal:  Diabetologia       Date:  2014-06-03       Impact factor: 10.122

2.  Quantification of the relationship between insulin sensitivity and beta-cell function in human subjects. Evidence for a hyperbolic function.

Authors:  S E Kahn; R L Prigeon; D K McCulloch; E J Boyko; R N Bergman; M W Schwartz; J L Neifing; W K Ward; J C Beard; J P Palmer
Journal:  Diabetes       Date:  1993-11       Impact factor: 9.461

Review 3.  Assessment of insulin secretion in relation to insulin resistance.

Authors:  Andrea Mari; Bo Ahrén; Giovanni Pacini
Journal:  Curr Opin Clin Nutr Metab Care       Date:  2005-09       Impact factor: 4.294

4.  Early Assessment of the Risk for Gestational Diabetes Mellitus: Can Fasting Parameters of Glucose Metabolism Contribute to Risk Prediction?

Authors:  Veronica Falcone; Grammata Kotzaeridi; Melanie Hanne Breil; Ingo Rosicky; Tina Stopp; Gülen Yerlikaya-Schatten; Michael Feichtinger; Wolfgang Eppel; Peter Husslein; Andrea Tura; Christian S Göbl
Journal:  Diabetes Metab J       Date:  2019-03-12       Impact factor: 5.376

  4 in total

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