2016年1月18日 · We propose to model blood glucose during an OGTT using a compartmental dynamic model with a system of ODEs. Our model works well in describing most scenarios that occur during an OGTT considering only 4 parameters. Fitting the model to data is an inverse problem, which is suitable for Bayesian inference.

Diabetes testing provides population data to: 1) determine a national estimate of diabetes disease prevalence (diagnosed and undiagnosed), 2) identify the risk factors of diabetes disease; 3) permit a national cohort to be established for follow-up studies of this condition; and 4) provide critical information to clinicians and public health ...

These regression equations should be used when examining trends of oral glucose tolerance test (OGTT) data across 2015-2016 and 2007-2014 cycles, or combining 2015-2016 data with these previous cycles.

2003年4月1日 · RESEARCH DESIGN AND METHODS —OGTT data from 551 subjects (485 with normal glucose tolerance [NGT] and 66 with impaired glucose tolerance [IGT]) were analyzed. We distinguished between “monophasic,” “biphasic,” and unclassified glucose shapes.

Abstract . Most common methods for the analysis of the data on this test are wasteful of much of the information con ained therein. We propose to model blood glucose during an OGTT using a compartmental dynamic model with a ystem of ODEs. Our model works well in de-scribing most scenarios that occur during an OGTT

2025年2月4日 · Evidence for using continuous glucose monitoring (CGM) as an alternative to oral glucose tolerance tests (OGTTs) in presymptomatic type 1 diabetes is primarily cross-sectional. We used longitudinal data to compare the diagnostic performance of repeated CGM, HbA 1c, and OGTT metrics to predict progression to stage 3 type 1 diabetes.

2024年12月4日 · We propose to model blood glucose during an OGTT using a compartmental dynamic model with a system of Ordinary Differential Equations (ODEs). Our model works well in describing most scenarios that occur during an OGTT considering only four parameters. Fitting the model to data is an inverse problem, which is suitable for Bayesian inference.

This project propose an Ordinary Differential Equations System to model Glucose-Insulin dynamics during the Oral Glucose Tolerance Test. With the numerical Glucose curve, we solve a Bayesian inverse problem: Given five glucose observations, every thirty minutes, find a set of parameters that describe a patient status

2013年1月17日 · OGTTs with five glucose measurements over two hours were recorded for 974 healthy pregnant women in their first trimester. For each woman, the five measurements were transformed into smooth OGTT glucose curves by functional data analysis (FDA), a collection of statistical methods developed specifically to analyse curve data.

For over 100 years, the oral glucose tolerance test (OGTT) has been the cornerstone for detecting prediabetes and type 2 diabetes (T2DM). In recent decades, controversies have arisen identifying internationally acceptable cut points using fasting plasma glucose (FPG), 2-h post-load glucose (2-h PG), and/or HbA1c for defining intermediate ...