349981 A Subcutaneous Insulin Absorption Model for Critically Ill Patients

Monday, November 4, 2013
Grand Ballroom B (Hilton)
Michael Vilkhovoy1, Ari Pritchard-Bell2, Robert S. Parker2 and Gilles Clermont3, (1)University of Massachusetts, Amherst, MA, (2)Chemical and Petroleum Engineering, University of Pittsburgh, Pittsburgh, PA, (3)Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA

Critically ill patients suffer from “stress hyperglycemia,” a diabetes-like condition of elevated glucose concentrations. Preventing these episodes may significantly reduce morbidity and mortality rates for patients [1]; while the NICE-SUGAR trial debates this result [2], these trials are often confounded by increased hypoglycemia. The current state is a conservative approach to glucose control in critical care where physicians maintain glucose levels via strategic administration of insulin, and the result is mild-to-moderate hyperglycemia for patients. We look to automate this insulin delivery process to improve glucose control, while mitigating hypoglycemia, using mathematical model-based tools. Key to clinical implementability and performance is a subcutaneous insulin delivery model. The proposed model is a reduction of an extended Wilinska model [3] that is able to capture the insulin plasma dynamics after a variety of insulin types, administration routes, and patients. Clinical data from type-1 diabetics and healthy patients administered different types of insulin by injection and infusion were fit to the model using nonlinear least-squares regression. Regular insulin was simultaneously fit across three doses by adjusting the transfer rates within the model. Fast acting insulin was simultaneously fit separately from the regular insulin, and similarities and differences between fast-acting insulin analogues were observed. The subcutaneous model, integrated with our whole body model [4] is able to accurately capture plasma glucose levels of patients published in the literature. We are currently coupling this model to a model-based control algorithm to facilitate clinical decision-making for glucose control and insulin delivery in critical care.

[1] G. Van den Berghe, P. Wouters, F. Weekers, C. Verwaest, F. Bruyninckx, M. Schetz, D. Vlasselaers, P. Ferdinande, P. Lauwers, and R. Bouillon.  “Intensive Insulin Therapy in Critically Ill Patients.”  NEJM 345, 1359-1367, 2001

[2] NICE-SUGAR Study Investigators, S. Finfer, D.R. Chittock, S.Y. Su, D. BlairD. Foster, V. Dhingra, R. Bellomo, D. Cook, P. Dodek, W.R. Henderson, P.C. Hebert, S. Heritier, D.K. Heyland, C. McArthur, E. McDonald, I. Mithcell, J.A. Myburgh, R. Norton, J. Potter, B.G. Robinson, and J.J. Ronco.  “Intentive versus Conventional Glucose Control in Critically Ill Patients.”  NEJM 360, 1283-97, 2009.

[3] M.E Willinska, L.J. Chassin, H.C. Schaller, L. Schaupp, T.R. Pieber and R. Hovorka. “Insulin Knetics in Type-1 Diabetes: Continyous and Bolus Delivery of Rapid Acting Insulin.” IEEE Trans Biomed Eng 52, 3-12, 2005.

[4] A. Roy and R.S. Parker.  “Dynamic Modeling of Free Fatty Acid, Glucose, and Insulin:  an Extended Minimal Model.”  Diabetes Technol Ther. 8, 617-26, 2006.

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