Effect of algorithm aggressiveness on the performance of the Hypoglycemia-Hyperglycemia Minimizer (HHM) system

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Abstract

The Hypoglycemia-Hyperglycemia Minimizer (HHM) System aims to mitigate glucose excursions by preemptively modulating insulin delivery based on continuous glucose monitor (CGM) measurements. The "aggressiveness factor" is a key parameter in the HHM System algorithm, affecting how readily the system adjusts insulin infusion in response to changing CGM levels. Twenty adults with type 1 diabetes were studied in closed-loop in a clinical research center for approximately 26 hours. This analysis focused on the effect of the aggressiveness factor on the insulin dosing characteristics of the algorithm and, to a lesser extent, on the glucose control results observed. As the aggressiveness factor increased from conservative to medium to aggressive: the maximum observed insulin dose delivered by the algorithm-which is designed to give doses that are corrective in nature every 5 minutes-increased (1.00 vs 1.15 vs 2.20 U, respectively); tendency to adhere to the subject's nominal basal dose decreased (61.9% vs 56.6% vs 53.4%); and readiness to decrease insulin below basal also increased (18.4% vs 19.4% vs 25.2%). Glucose analyses by both CGM and Yellow Springs Instruments (YSI) indicated that the aggressive setting of the algorithm resulted in the least time spent at levels >180 mg/dL, and the most time spent between 70-180 mg/dL. There was no severe hyperglycemia, diabetic ketoacidosis, or severe hypoglycemia for any of the aggressiveness values investigated. These analyses underscore the importance of investigating the sensitivity of the HHM System to its key parameters, such as the aggressiveness factor, to guide future development decisions. © 2014 Diabetes Technology Society.

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Finan, D. A., McCann, T. W., Rhein, K., Dassau, E., Breton, M. D., Patek, S. D., … Venugopalan, R. (2014). Effect of algorithm aggressiveness on the performance of the Hypoglycemia-Hyperglycemia Minimizer (HHM) system. Journal of Diabetes Science and Technology, 8(4), 685–690. https://doi.org/10.1177/1932296814534589

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