Current diabetes education methods are costly, time-consuming, and do not actively engage the patient. Here, we describe the development and verification of the physiological model for healthy subjects that forms the basis of the Eindhoven Diabetes Education Simulator (E-DES). E-DES shall provide diabetes patients with an individualized virtual practice environment incorporating the main factors that influence glycemic control: food, exercise, and medication. The physiological model consists of 4 compartments for which the inflow and outflow of glucose and insulin are calculated using 6 nonlinear coupled differential equations and 14 parameters. These parameters are estimated on 12 sets of oral glucose tolerance test (OGTT) data (226 healthy subjects) obtained from literature. The resulting parameter set is verified on 8 separate literature OGTT data sets (229 subjects). The model is considered verified if 95% of the glucose data points lie within an acceptance range of ±20% of the corresponding model value. All glucose data points of the verification data sets lie within the predefined acceptance range. Physiological processes represented in the model include insulin resistance and β-cell function. Adjusting the corresponding parameters allows to describe heterogeneity in the data and shows the capabilities of this model for individualization. We have verified the physiological model of the E-DES for healthy subjects. Heterogeneity of the data has successfully been modeled by adjusting the 4 parameters describing insulin resistance and β-cell function. Our model will form the basis of a simulator providing individualized education on glucose control.
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http://dx.doi.org/10.1177/1932296814562607 | DOI Listing |
Curr Cardiol Rep
January 2025
John Ochsner Heart and Vascular Institute, Ochsner Clinical School University of Queensland School of Medicine, New Orleans, LA, USA.
Purpose Of Review: To provide a narrative overview of trends and disparities in the cardiometabolic profiles of U.S. adults by synthesizing findings from nationally representative studies conducted between 1999 and 2020.
View Article and Find Full Text PDFCurr Diab Rep
January 2025
Sections of Adult and Pediatric Endocrinology, University of Chicago Medicine, Outpatient CDCES, Chicago, USA.
Purpose Of Review: Evidence over the past few decades have proven the benefits and cost savings of diabetes self-management education and support (DSMES) and medical nutrition therapy (MNT). Yet, the benefits continue to be underutilized. Little evidence is available to definitively assess insurance coverage for both services.
View Article and Find Full Text PDFTransl Behav Med
January 2025
University of Pittsburgh School of Public Health, Department of Epidemiology, Pittsburgh, PA, USA.
Background: In previous efforts, health-related quality of life (HRQoL) improved for individuals at high risk of type 2 diabetes and cardiovascular disease after participation in community-based lifestyle interventions (LI) with a moderate-to-vigorous physical activity (MVPA) movement goal.
Purpose: It is unknown whether HRQoL improves with LI when the primary movement goal is to reduce sedentary behavior. HRQoL changes were examined among adults with overweight and prediabetes and/or metabolic syndrome randomized to a 12-month Diabetes Prevention Program-based Group Lifestyle Balance (DPP-GLB) community LI work with goals of weight-loss and either increasing MVPA (DPP-GLB) or reducing sedentary time (GLB-SED).
Angew Chem Int Ed Engl
January 2025
Shanghai Jiaotong University, 800 Dongchuan Road, Minhang District, Shanghai, CHINA.
Diabetes significantly increases the risk of serious health issues, including prolonged skin inflammation and delayed wound healing, owing to inferior glucose control and suppression of the immune system. Although traditional hydrogen (H2) therapy is slightly effective, its ability to tailor the release of H2 on the skin is limited. Accordingly, this study proposed a novel strategy for electrocatalytic H2 release under neutral conditions to promote wound healing in diabetic mice and rabbit.
View Article and Find Full Text PDFMed Decis Making
January 2025
Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
Our commentary proposes the application of directed acyclic graphs (DAGs) in the design of decision-analytic models, offering researchers a valuable and structured tool to enhance transparency and accuracy by bridging the gap between causal inference and model design in medical decision making.The practical examples in this article showcase the transformative effect DAGs can have on model structure, parameter selection, and the resulting conclusions on effectiveness and cost-effectiveness.This methodological article invites a broader conversation on decision-modeling choices grounded in causal assumptions.
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