ArticleJournal of diabetes science and technology2008
Development of a clinical type 1 diabetes metabolic system model and in silico simulation tool.
Article in Journal of diabetes science and technology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- A controlled study of the effectiveness of an adaptive closed-loop algorithm to minimize corticosteroid-induced stress hyperglycemia in type 1 diabetes.Journal of diabetes science and technology · 2011Trial
- Blood glucose controller for neonatal intensive care: virtual trials development and first clinical trials.Journal of diabetes science and technology · 2009Trial
- Simulation Platform Development for Diabetes and Technology Self-Management.Journal of diabetes science and technology · 2022Article
- Validation of a novel method for determining the renal threshold for glucose excretion in untreated and canagliflozin-treated subjects with type 2 diabetes mellitus.The Journal of clinical endocrinology and metabolism · 2013Article
- Clinical detection and monitoring of acute pulmonary embolism: proof of concept of a computer-based method.Annals of intensive care · 2011Article
- The identification of insulin saturation effects during the dynamic insulin sensitivity test.The open medical informatics journal · 2010Article
- A benchmark data set for model-based glycemic control in critical care.Journal of diabetes science and technology · 2008Article
- In silico simulation of long-term type 1 diabetes glycemic control treatment outcomes.Journal of diabetes science and technology · 2008Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe goal of this study was to develop a system model of type 1 diabetes for the purpose of in silico simulation for the prediction of long-term glycemic control outcomes.
methodsThe system model was created and identified on a physiological cohort of virtual type 1 diabetes patients (n = 40). Integral-based identification was used to develop (n = 40) insulin sensitivity profiles.
resultsThe n = 40 insulin sensitivity profiles provide a driving input for virtual patient trials using the models developed. The identified models have a median (90% range) absolute percentage error of 1.33% (0.08-7.20%). The median (90% range) absolute error was 0.12 mmol/liter (0.01-0.56 mmol/liter). The model and integral-based identification of SI captured all patient dynamics with low error, which would lead to more physiological behavior simulation.
conclusionsA simulation tool incorporating n = 40 virtual patient data sets to predict long-term glycemic control outcomes from clinical interventions was developed based on a physiological type 1 diabetes metabolic system model. The overall goal is to utilize this model and insulin sensitivity profiles to develop and optimize self-monitoring blood glucose and multiple daily injection therapy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.