Adaptive blood glucose control for intensive care applications

Authors:
Matteo Ottavian;Massimiliano Barolo;Howard Zisser;Eyal Dassau;Dale E. Seborg
Affiliations:
Dipartimento di Principi e Impianti di Ingegneria Chimica, Universití di Padova, via Marzolo 9, 35131 Padova PD, Italy;Dipartimento di Principi e Impianti di Ingegneria Chimica, Universití di Padova, via Marzolo 9, 35131 Padova PD, Italy;Sansum Diabetes Research Institute, 2219 Bath Street, Santa Barbara, CA 93105, United States and Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, United ...;Sansum Diabetes Research Institute, 2219 Bath Street, Santa Barbara, CA 93105, United States and Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, United ...;Department of Chemical Engineering, University of California, Santa Barbara, CA 93106-5080, United States and Sansum Diabetes Research Institute, 2219 Bath Street, Santa Barbara, CA 93105, United ...
Venue:
Computer Methods and Programs in Biomedicine
Year:
2013

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Abstract

Control of blood glucose concentration for patients in intensive care units (ICUs) has been demonstrated to be beneficial in reducing mortality and the incidence of serious complications, for both diabetic and non-diabetic patients. However, the high degree of variability and uncertainty characterizing the physiological conditions of critically ill subjects makes automated glucose control quite difficult; consequently, traditional, nurse-implemented protocols are widely employed. These protocols are based on infrequent glucose measurements, look-up tables to determine the appropriate insulin infusion rates, and bedside insulin administration. In this paper, a novel automatic adaptive control strategy based on frequent glucose measurements and a self-tuning control technique is validated based on a simulation study for 200 virtual patients. The adaptive control strategy is shown to be highly effective in controlling blood glucose concentration despite the large degree of variability in the blood glucose response exhibited by the 200 simulated patients.