The Role of Glycemic Index and Glycemic Load in the Development of Real-Time Postprandial Glycemic Response Prediction Models for Patients With Gestational Diabetes.

Evgenii Pustozerov,Anna Anopova,Ekaterina Shilova,Elena Vasukova,Elena Grineva,Aleksandra Dronova,Elena Vasilieva,Faina Piven,Polina Popova,Tatiana Pervunina,Aleksandra Tkachuk

doi:10.3390/nu12020302

Abstract

The incorporation of glycemic index (GI) and glycemic load (GL) is a promising way to improve the accuracy of postprandial glycemic response (PPGR) prediction for personalized treatment of gestational diabetes (GDM). Our aim was to assess the prediction accuracy for PPGR prediction models with and without GI data in women with GDM and healthy pregnant women. The GI values were sourced from University of Sydney’s database and assigned to a food database used in the mobile app DiaCompanion. Weekly continuous glucose monitoring (CGM) data for 124 pregnant women (90 GDM and 34 control) were analyzed together with records of 1489 food intakes. Pearson correlation (R) was used to quantify the accuracy of predicted PPGRs from the model relative to those obtained from CGM. The final model for incremental area under glucose curve (iAUC120) prediction chosen by stepwise multiple linear regression had an R of 0.705 when GI/GL was included among input variables and an R of 0.700 when GI/GL was not included. In linear regression with coefficients acquired using regularization methods, which was tested on the data of new patients, R was 0.584 for both models (with and without inclusion of GI/GL). In conclusion, the incorporation of GI and GL only slightly improved the accuracy of PPGR prediction models when used in remote monitoring.

Highlights

Gestational diabetes mellitus (GDM) has become a common condition during pregnancy, affecting up to 17.8% of pregnancies [1]
We demonstrated that prediction accuracy for postprandial glycemic response (PPGR) prediction models in women this and study, we demonstrated that prediction accuracy for PPGR
The small impact of glycemic index (GI)/glycemic load (GL) into the individual PPGR may be explained by the substantial variability in individual responses to GI value determinations [30] and intraindividual variability of PPGR to specific foods [6,8]

Summary

Introduction

Gestational diabetes mellitus (GDM) has become a common condition during pregnancy, affecting up to 17.8% of pregnancies [1]. GDM is associated with a higher risk of developing serious complications for the mother and the offspring. Apart from promoting the future development of type 2 diabetes (T2D) in the mother [2], GDM is supposed to be an important factor that predisposes an offspring to obesity and type 2 diabetes mellitus (T2D) [3,4]. Given this forecast, maintaining normal blood glucose (BG) levels during pregnancy is critical to curb and reverse the epidemic rise of these conditions [4]. Even if the recommendations are more detailed, these diets description concerns only characteristics of the foods and does not take into account the individual features of patients

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