ESPE Abstracts

Introduction: Obesity is associated with an increased risk of developing several metabolic disorders, such as type 2 diabetes. The Children’s Lifestyle Medicine Centre at the Jeroen Bosch Hospital is a national reference center for the personalized treatment of children (aged 5-18 years) with severe obesity. As part of this personalized program, patients undergo an extensive oral glucose tolerance test (OGTT), in which both glucose and insulin levels are determined at seven different timepoints to distinguish muscle from liver insulin resistance (IR). The conventional classification of liver IR (LIR) relies on the magnitude of the rise of both glucose and plasma insulin levels during the first 30 minutes of an OGTT. The formula uses predetermined criteria based on adult population averages, which assumes maximum glucose levels fixed on 30 minutes, without accounting for variations in glucose and insulin responses. The aim of this study is to develop a new metric for quantifying liver IR in children with obesity by analyzing and interpreting their personal glucose and insulin responses from the OGTTs, considering both the timing and amplitude of the peak measurements.

Methods: A total of 242 complete OGTTs from 211 patients underwent an OGTT. Blood glucose and insulin levels were determined at seven timepoints (t= -15, 0, 15, 30, 60, 90 and 120 minutes). Measurements of liver enzymes, plasma lipids, blood pressure, and BMI were obtained concurrently. Descriptive analysis of the population and comparison of the current and newly developed liver IR metric were conducted using Python 3.8 with Numpy (1.20) and Pandas (0.28).

Results: Glucose and insulin responses from the OGTT were heterogeneous within the patient population, showing large distributions at every timepoint. Analysis of the peak and nadir glucose and insulin measurements revealed that almost half of the patients (49%) did not have their maximum glucose measurement at 30 minutes. For insulin this was 61%. The new metric (C) is a weighted criterion in which the patient’s timepoint and amplitude of the maximum glucose and insulin measurements are divided by the nominal peak time and amplitude of the entire patient population. Both C- glucose and C- insulin showed better correlations with the patient’s BMI, plasma lipid profile, liver enzymes and blood pressure, compared to the correlations of the conventional LIR classification with the same parameters.

Conclusion: This alternative calculation method seems more appropriate to determine liver IR in children as it reflects the patient’s personal glucose and insulin responses more accurately.