International Journal of Artificial Intelligence, Machine Learning and Data Science (IJAIMLDS)

PROBING GLYCEMIC VARIABILITY WITH ORAL GLUCOSE TOLERANCE TESTING

Authors

  • Dr. Jean-Pierre Kouamé Bamba Institut Pasteur de Côte d‟Ivoire

Abstract

The Oral Glucose Tolerance Test (OGTT) has traditionally served as a valuable diagnostic tool for conditions such as diabetes mellitus, gestational diabetes, glucose intolerance, reactional hypoglycemia, and diabetes associated with cystic fibrosis. However, over the past decade, its application has been predominantly restricted to fasting blood glucose measurements and glycated hemoglobin levels, sparking controversial debates. Recent studies, in contrast, reaffirm the significance of OGTT as a reference diagnostic tool for assessing glycemic variations, identifying a decrease in glucose tolerance (a marker for cardiovascular complications and type 2 diabetes), and diagnosing gestational diabetes. Moreover, OGTT has been proposed as a quantitative method to assess insulin secretion and insulin sensitivity, offering the advantage of dynamic measurements under stimulation conditions, which sets it apart from tests like fasting blood glucose measurements. This study aims to analyze the OGTT profiles of patients referred to the Institut Pasteur of Côte d'Ivoire (IPCI) between 2013 and 2016. By examining OGTT results in this cohort, we seek to contribute to the management and prevention of diabetes and its associated cardiovascular risks.

Keywords:

Oral Glucose Tolerance Test (OGTT), Diabetes Mellitus, Gestational Diabetes, Insulin Sensitivity, Cardiovascular Complications

Downloads

Published

2023-11-02

How to Cite

Bamba, J.-P. K. (2023). PROBING GLYCEMIC VARIABILITY WITH ORAL GLUCOSE TOLERANCE TESTING. International Journal of Artificial Intelligence, Machine Learning and Data Science (IJAIMLDS), 6(4), 7–15. Retrieved from https://zapjournals.com/Journals/index.php/ijaimlds/article/view/1507