Automated insulin delivery (AID) systems have not been designed to account for psychological and physiological stress in individuals with type 1 diabetes (T1D). Prior studies have noted psychological stress can cause an increase in catecholamine and cortisol levels and can impair insulin sensitivity,1,2 with acute stress affecting postprandial glucose levels.3 We have reported that psychological stress can also cause changes in glucose variability, with potential increases in the number of low blood glucose readings and altered behavior, such as reduced carbohydrate intake.4 We enhanced our zone-model predictive control algorithm running on the Harvard University interoperable Artificial Pancreas System5 using a continuous function of glucose velocity and insulin-on-board to gradually increase insulin infusion under conditions of sustained hyperglycemia, while retaining the previous design to protect from controller-induced hypoglycemia, as a potential improvement for treatment of stress-induced hyperglycemia.
We piloted at-home use of the system in two adults with T1D (64-year-old male, A1c 5.3% and a 31-year-old female, A1c 6.0%) over a two-week period in a randomized crossover comparison to sensor-augmented pump (SAP) (NCT04142229) at Sansum Diabetes Research Institute in California and Mayo Clinic in Minnesota during March and April of 2020. Although neither subject was diagnosed with COVID-19, both subjects encountered multiple psychological stressors related to the pandemic, including job loss, closing of the study clinical centers, cancellation of the planned formal psychological and physiological stress induction sessions, challenges in purchasing food for themselves and their families, and adhering to strict isolation rules. Electrodermal activity (EDA) measurements were collected throughout each day using the Empatica E4 wristband (Empatica Srl, Milano, Italy) as a biomarker of stress.
Both subjects were randomized to the AID arm first. Comparing both arms, subjects had good glycemic control during SAP use, with Subject 1 having 90.3% sensor glucose time-in-range (TIR) 70-180 mg/dL overall and 87.1% overnight, and Subject 2 having 71.2% TIR overall and 71% overnight. This high TIR with SAP use also came at the cost of significant amount of hypoglycemia, in particular for Subject 1, who had 6.7% time <70 mg/dL overall, and 11% time <70 mg/dL overnight. During the two weeks of AID use, for Subject 1, TIR 70-180 mg/dL increased to 92% overall and to 89.4% overnight, with a decrease in time <70 mg/dL to 3.1% overall and to 1% overnight. For Subject 2, TIR 70-180 mg/dL increased to 84.6% overall and to 94% overnight, with a decrease in time <70 mg/dL to 0.5% overall and to 0.1% overnight (Figure 1).
Figure 1.
Paired comparison of 24 hours day and night sensor glucose time in range 70-180 mg/dL during the SAP and AID arms for each two-week period. The solid lines connect individual subjects, with the bubble size proportional to time in hypoglycemia below 70 mg/dL. Time in range improved for both subjects, while at the same time reducing hypoglycemia (time <70 mg/dL).
AID, automated insulin delivery; SAP, sensor-augmented pump.
Continuous decomposition analysis of EDA,6 defining a stress event as a response amplitude of at least 0.5 micro-Siemens, showed a greater number of events per day in the SAP arm for Subject 1 (median [interquartile range {IQR}]: 82.0 [167.0] vs 23.0 [20.0]) as well as for Subject 2 (median [IQR]: 122.5 [62.0] vs 56.0 [121.5]).
These results support the benefit of AID over SAP under stressful conditions. Our goal is to further explore improvements to AID technology to improve handling of stress-induced glucose variability.
Footnotes
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: JEP reports receiving grant support, provided to his institution, consulting fees, and speaker fees from Tandem Diabetes Care, Inc.; grant support, provided to his institution, and advisory board fees from Medtronic; grant support, provided to his institution, and consulting fees from Eli Lilly; grant support and supplies, provided to his institution, from Insulet; and supplies, provided to his institution, from Dexcom, Inc. FJD reports product support from Dexcom, Inc., and Tandem Diabetes Care, as well as patent royalties from Insulet Inc., Dexcom, Mode AGC, and Roche, and is a Scientific Advisor to Mode AGC. YCK has received product support from Dexcom and Roche Diabetes, and consulted for Novo Nordisk. ED is currently an employee of Eli Lilly and Company. The work presented in this paper was performed as part of ED’s academic appointment and is independent of his employment with Eli Lilly and Company. ED reports consulting fees from Eli Lilly, speaker bureau fees from Roche Diabetes Care, and product support from Dexcom, Inc. and Tandem Diabetes Care, as well as patent royalties from Insulet Inc., Dexcom, Mode AGC, and Roche. No conflicts of interest relevant to this project are reported for the rest of the authors.
Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was made possible through collaboration between the JDRF and The Leona M. and Harry B. Helmsley Charitable Trust (2-SRA-2017-503-M-B) and by grants from the National Institutes of Health (DP3DK104057 and DP3DK113511). Product support was provided by Dexcom Inc. (research discount on CGM sensors, with transmitters provided in-kind) (IIS-2019-017). Tandem t:AP insulin pumps were purchased from Tandem Diabetes Care, Inc. at full price. The funders and device manufacturers had no influence on the design or conduct of the trial and were not involved in data collection or analysis, the writing of the manuscript, or the decision to submit it for publication.
ORCID iDs: Jordan E. Pinsker 
https://orcid.org/0000-0003-4080-9034
Eyal Dassau
https://orcid.org/0000-0001-5333-6892
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