The Eindhoven Diabetes Education Simulator (e-DES) - incorporating different ...Natal van Riel
Background: Diabetes education is mainly based on one-on-one patient-health care provider contact. This is costly, time-consuming and gives the patient no room for practice. We want to address these issues by creating the Eindhoven Diabetes Education Simulator, which uses a physiology-based mathematical model to predict glucose and insulin concentrations for patients with diabetes type 1 and 2 over a 2-4 hour time period after intake of food and/or insulin. In our current model food is entered in the form of carbohydrate content. The goal of this study was to incorporate different food products and composite meals for healthy persons, since different food types will elicit different glucose responses.
Methods: A literature search was performed for datasets of different food products using (combinations of) the following search terms: healthy, mixed meal, glucose, insulin, glycemic response, glycemic index, and looking for cross-references. We included any dataset for which glucose ánd insulin concentrations were measured on at least 5 time points after food ingestion in healthy subjects. Healthy was defined as normal glucose tolerant, normal insulin sensitive, normotensive, normal HbA1c, non-obese (BMI< 30 kg/m2), no family history of diabetes, not pregnant, and free of apparent diseases and medication. Our model was fitted to the different datasets using a non-linear least squares algorithm.
Results: We have fitted our model to 57 separate datasets (from 18 publications including 220 subjects, references available on request). For 35 of these datasets we obtained a model fit that described the dataset well, of which five are shown in Figure 1. In the cases that we could not obtain a good fit, there usually were a limited number of data points available.
Conclusion: The Eindhoven Diabetes Education Simulator is able to simulate postprandial glucose and insulin concentrations for healthy persons for 35 different food products and composite meals.
ECR Europe Forum '05. Get the most out of communication standards upstreamECR Community
Get the most out of communication standards upstream:
EDI messages and bar codes have been great enablers for speeding up and improving the quality of supply chain processes between retailers and manufacturers. Now it is time to use them upstream. Learn how to apply these techniques with suppliers of raw materials and packaging.
Speakers:
Nicola Comiotto, Nestlé,
Regenald Kramer, GS1,
Miodrag Mitic, GS1,
Sarina Pielaat, GS1 Netherlands
Facilitated by
GS1 (formerly EAN International)
The Eindhoven Diabetes Education Simulator (e-DES) - incorporating different ...Natal van Riel
Background: Diabetes education is mainly based on one-on-one patient-health care provider contact. This is costly, time-consuming and gives the patient no room for practice. We want to address these issues by creating the Eindhoven Diabetes Education Simulator, which uses a physiology-based mathematical model to predict glucose and insulin concentrations for patients with diabetes type 1 and 2 over a 2-4 hour time period after intake of food and/or insulin. In our current model food is entered in the form of carbohydrate content. The goal of this study was to incorporate different food products and composite meals for healthy persons, since different food types will elicit different glucose responses.
Methods: A literature search was performed for datasets of different food products using (combinations of) the following search terms: healthy, mixed meal, glucose, insulin, glycemic response, glycemic index, and looking for cross-references. We included any dataset for which glucose ánd insulin concentrations were measured on at least 5 time points after food ingestion in healthy subjects. Healthy was defined as normal glucose tolerant, normal insulin sensitive, normotensive, normal HbA1c, non-obese (BMI< 30 kg/m2), no family history of diabetes, not pregnant, and free of apparent diseases and medication. Our model was fitted to the different datasets using a non-linear least squares algorithm.
Results: We have fitted our model to 57 separate datasets (from 18 publications including 220 subjects, references available on request). For 35 of these datasets we obtained a model fit that described the dataset well, of which five are shown in Figure 1. In the cases that we could not obtain a good fit, there usually were a limited number of data points available.
Conclusion: The Eindhoven Diabetes Education Simulator is able to simulate postprandial glucose and insulin concentrations for healthy persons for 35 different food products and composite meals.
ECR Europe Forum '05. Get the most out of communication standards upstreamECR Community
Get the most out of communication standards upstream:
EDI messages and bar codes have been great enablers for speeding up and improving the quality of supply chain processes between retailers and manufacturers. Now it is time to use them upstream. Learn how to apply these techniques with suppliers of raw materials and packaging.
Speakers:
Nicola Comiotto, Nestlé,
Regenald Kramer, GS1,
Miodrag Mitic, GS1,
Sarina Pielaat, GS1 Netherlands
Facilitated by
GS1 (formerly EAN International)
Project Management SKills Training Programme (Japanese)m_beresford
This series of Project Management skills training workshops is designed to help organizations manage projects more collaboratively and profitable across borders.
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