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Clinical Trial
. 2015 Jun 30;10(1):104-10.
doi: 10.1177/1932296815593292.

Sensitivity of the Predictive Hypoglycemia Minimizer System to the Algorithm Aggressiveness Factor

Daniel A Finan  1 , Eyal Dassau  2 , Marc D Breton  3 , Stephen D Patek  3 , Thomas W McCann Jr  4 , Boris P Kovatchev  3 , Francis J Doyle 3rd  2 , Brian L Levy  4 , Ramakrishna Venugopalan  4
Affiliations
Clinical Trial

Sensitivity of the Predictive Hypoglycemia Minimizer System to the Algorithm Aggressiveness Factor

Daniel A Finan et al. J Diabetes Sci Technol. .

Abstract

Background: The Predictive Hypoglycemia Minimizer System ("Hypo Minimizer"), consisting of a zone model predictive controller (the "controller") and a safety supervision module (the "safety module"), aims to mitigate hypoglycemia by preemptively modulating insulin delivery based on continuous glucose monitor (CGM) measurements. The "aggressiveness factor," a pivotal variable in the system, governs the speed and magnitude of the controller's insulin dosing characteristics in response to changes in CGM levels.

Methods: Twelve adults with type 1 diabetes were studied in closed-loop in a clinical research center for approximately 24 hours. This analysis focused primarily on the effect of the aggressiveness factor on the automated insulin-delivery characteristics of the controller, and secondarily on the glucose control results.

Results: As aggressiveness increased from "conservative" to "medium" to "aggressive," the controller recommended less insulin (-3.3% vs -14.4% vs -19.5% relative to basal) with a higher frequency (5.3% vs 14.4% vs 20.3%) during the critical times when the CGM was reading 90-120 mg/dl and decreasing. Blood glucose analyses indicated that the most aggressive setting resulted in the most desirable combination of the least time spent <70 mg/dl and the most time spent 70-180 mg/dl, particularly in the overnight period. Hyperglycemia, diabetic ketoacidosis, or severe hypoglycemia did not occur with any of the aggressiveness values.

Conclusion: The Hypo Minimizer's controller took preemptive action to prevent hypoglycemia based on predicted changes in CGM glucose levels. The most aggressive setting was quickest to take action to reduce insulin delivery below basal and achieved the best glucose metrics.

Trial registration: ClinicalTrials.gov NCT01919385.

Keywords: Aggressiveness factor; algorithm; artificial pancreas; closed-loop control; model predictive control; type 1 diabetes.

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Conflict of interest statement

Declaration of Conflicting Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: DAF, TWM, BLL, and RV are employees of Animas Corporation. ED has received product support from Animas, Dexcom, and Insulet. MDB has received research grants and product support from Animas, Insulet, Dexcom, Roche, Sanofi, Abbott, BD, Lilly, and Tandem Diabetes Care. SDP holds equity interest in TypeZero, LLC. BPK is on the advisory panel for Sanofi Aventis and AstraZeneca; has received research support from Animas, Dexcom, Insulet, Roche Diagnostic, and Tandem Diabetes Care; and receives patent royalties from Sanofi Aventis and J&J. The UCSB technology used in this study developed in part by ED and FJD has been licensed to Animas. The University of Virginia technology used in this study developed in part by BPK, MDB, and SDP has been licensed to Animas.

Figures

Figure 1.
Figure 1.
Median CGM tracing shown with the IQR for the entire cohort (N = 12). The shaded area is the approximately normoglycemic range of 70-180 mg/dl. CGM, continuous glucose monitor; IQR, interquartile range.
See this image and copyright information in PMC

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