We have located links that may give you full text access.
Identification of glucose and insulin patterns during A 5-H glucose tolerance test and association with cardiometabolic risk factors.
Background: Insulin resistance is key in the pathogenesis of the metabolic syndrome and cardiovascular disease.
Objective: We aimed to identify glucose and insulin patterns after a 5-h oral glucose tolerance test (OGTT) in individuals without diabetes and to explore cardiometabolic risk factors, beta-cell function, and insulin sensitivity in each pattern.
Methods: We analyzed the 5-h OGTT in a tertiary healthcare center. We identified classes using latent class trajectory analysis and evaluated their association with cardiometabolic risk factors, beta-cell function, and insulin sensitivity surrogates by multinomial logistic regression analysis.
Results: We included 1088 5-h OGTT performed between 2013 and 2020 and identified four classes. Class one was associated with normal insulin sensitivity and secretion. Class two showed hyperglycemia, dysinsulinism, and a high-risk cardiometabolic profile (obesity, hypertriglyceridemia, and low high-density lipoprotein [HDL] cholesterol). Class three included older individuals, a higher proportion of males, and a greater prevalence of hypertension, hyperglycemia, hyperinsulinemia, and postprandial hypoglycemia. Finally, class four showed hyperglycemia, dysinsulinism, and hyperinsulinemia; this class had the worst cardiometabolic profile (a high proportion of males, greater age, hypertension, obesity, hypertriglyceridemia, and low HDL cholesterol, p < 0.001 vs. other classes).
Conclusions: The latent class analysis approach allows the identification of groups with an adverse cardiometabolic risk factor, and who might benefit from frequent follow-ups and timely multidisciplinary interventions.
Objective: We aimed to identify glucose and insulin patterns after a 5-h oral glucose tolerance test (OGTT) in individuals without diabetes and to explore cardiometabolic risk factors, beta-cell function, and insulin sensitivity in each pattern.
Methods: We analyzed the 5-h OGTT in a tertiary healthcare center. We identified classes using latent class trajectory analysis and evaluated their association with cardiometabolic risk factors, beta-cell function, and insulin sensitivity surrogates by multinomial logistic regression analysis.
Results: We included 1088 5-h OGTT performed between 2013 and 2020 and identified four classes. Class one was associated with normal insulin sensitivity and secretion. Class two showed hyperglycemia, dysinsulinism, and a high-risk cardiometabolic profile (obesity, hypertriglyceridemia, and low high-density lipoprotein [HDL] cholesterol). Class three included older individuals, a higher proportion of males, and a greater prevalence of hypertension, hyperglycemia, hyperinsulinemia, and postprandial hypoglycemia. Finally, class four showed hyperglycemia, dysinsulinism, and hyperinsulinemia; this class had the worst cardiometabolic profile (a high proportion of males, greater age, hypertension, obesity, hypertriglyceridemia, and low HDL cholesterol, p < 0.001 vs. other classes).
Conclusions: The latent class analysis approach allows the identification of groups with an adverse cardiometabolic risk factor, and who might benefit from frequent follow-ups and timely multidisciplinary interventions.
Full text links
Related Resources
Trending Papers
Challenges in Septic Shock: From New Hemodynamics to Blood Purification Therapies.Journal of Personalized Medicine 2024 Februrary 4
Molecular Targets of Novel Therapeutics for Diabetic Kidney Disease: A New Era of Nephroprotection.International Journal of Molecular Sciences 2024 April 4
The 'Ten Commandments' for the 2023 European Society of Cardiology guidelines for the management of endocarditis.European Heart Journal 2024 April 18
A Guide to the Use of Vasopressors and Inotropes for Patients in Shock.Journal of Intensive Care Medicine 2024 April 14
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app