Computer assisted diabetes care: a 6-year retrospective.
Over the past 6 years we have designed a number of computer-based prototypes for the provision of therapeutic advice and the generation of glycaemic predictions in insulin-dependent (type 1) diabetic patients. In this paper we provide an overview of some of this work, and describe our experiences in trying to develop such methods for clinical use. We review, as an example, a model of the glucoregulatory system which has been developed for patient and medical staff education about type 1 diabetes mellitus, as well as possibly for therapeutic use. Using individualised parameter values the predictions of the model can be applied to generate 24-h simulations of patient blood glucose profiles. Previous preliminary retrospective validation work performed with this model has revealed a mean predictive accuracy for blood glucose simulations of approximately 2 mmol/l. Conceptual limitations of such modelling approaches are considered. We comment that such "mechanistic' models may lack the necessary sophistication and flexibility to represent the complexity of the human glucoregulatory system and the challenges it has to face. Although such methodologies may therefore not be suitable for safe and effective application in routine clinical practice, we conclude that the evolution of such a system for demonstration/educational purposes could have widespread clinical utility as an interactive teaching tool.
Lehmann
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Academic Department of Radiology, St. Bartholomew's Hospital, London, UK.
Deutsch
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D001185:Artificial Intelligence; D001786:Blood Glucose / Q000032:analysis; D003920:Diabetes Mellitus / Q000628:therapy*; D006801:Humans; D007328:Insulin / Q000008:administration & dosage; D008954:Models, Biological; D010353:Patient Education as Topic; D012189:Retrospective Studies; D013813:Therapy, Computer-Assisted
D001786:Blood Glucose; D007328:Insulin