Strengths and Challenges of Closed-Loop Insulin Delivery During Exercise in People With Type 1 Diabetes: Potential Future Directions

Abstract

Exercise has many physical and psychological benefits and is recommended for people with type 1 diabetes; however, there are many barriers to exercise, including glycemic instability and fear of hypoglycemia. Closed-loop (CL) systems have shown benefit in the overall glycemic management of type 1 diabetes, including improving HbA1c levels and reducing the incidence of nocturnal hypoglycemia; however, these systems are challenged by the rapidly changing insulin needs with exercise. This commentary focuses on the principles, strengths, and challenges of CL in the management of exercise, and discusses potential approaches, including the use of additional physiological signals, to address their shortcomings in the pursuit of fully automated CL systems.

Taking a Walk in Their Shoes: The Lived Experiences of Emerging Adults with Type 1 Diabetes

“…Some of these newer systems ask that the user identify the size of the meal rather than the actual amount of carbohydrates being ingested, or have technology to account for inaccurate carbohydrate counting and/or the occasional missed food bolus, and at least one (Beta Bionic's iLet) does not require notification of food intake at all. [27][28][29] Managing blood sugars during exercise continues to be a challenge, 30 but working with these AID systems may also help decrease the exercise-related frustrations felt by emerging adults with type 1 diabetes. Studies need to be done to see how the newer AID systems affect diabetes management in emerging adults with type 1 diabetes, including if there is less or added mental burden and/or psychological distress, especially in specific populations, with increased use of AID systems.…”

Multivariable Automated Insulin Delivery System for Handling Planned and Spontaneous Physical Activities

“…An important feature of the safety module is the ability to predict in advance hypoglycemia and hyperglycemia for their early detection of potential occurrence, suspension of insulin delivery, or avoiding insulin overdosing. 43,44 In addition, predicting potential hypoglycemia and hyperglycemia can be used to adjust the conservativeness or aggressiveness of the controller. Mamdani fuzzy logic systems were used to predict hypoglycemia and hyperglycemia as they are easy to incorporate human knowledge and leverage the glucose information extracted from the T1Ds.…”

Advancements and future directions in the teamwork, targets, technology, and tight control—the 4T study: improving clinical outcomes in newly diagnosed pediatric type 1 diabetes

“…With increasing adoption of CGM use, patients can use the detailed information (e.g., trend arrows, patterns) to learn how different factors may impact glycemia around physical activity and exercise [40]. In addition, with advancements in automated insulin delivery (AID) systems, improvements in overnight glycemia are apparent [45]; but exercise and glycemic management remain a challenge [46,47]. In study 2, we will encourage patients to initiate the use of an insulin pump or AID system during the first 3-month period post-diagnosis and continue to offer exercise education to increase the knowledge and confidence around safe exercise.…”