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      Enhancing Automatic Closed-Loop Glucose Control in Type 1 Diabetes with an Adaptive Meal Bolus Calculator – In Silico Evaluation under Intra-Day Variability

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          Abstract

          Background and Objective

          Current prototypes of closed-loop systems for glucose control in type 1 diabetes mellitus, also referred to as artificial pancreas systems, require a pre-meal insulin bolus to compensate for delays in subcutaneous insulin absorption in order to avoid initial post-prandial hyperglycemia. Computing such a meal bolus is a challenging task due to the high intra-subject variability of insulin requirements. Most closed-loop systems compute this pre-meal insulin dose by a standard bolus calculation, as is commonly found in insulin pumps. However, the performance of these calculators is limited due to a lack of adaptiveness in front of dynamic changes in insulin requirements. Despite some initial attempts to include adaptation within these calculators, challenges remain.

          Methods

          In this paper we present a new technique to automatically adapt the meal-priming bolus within an artificial pancreas. The technique consists of using a novel adaptive bolus calculator based on Case-Based Reasoning and Run-To-Run control, within a closed-loop controller. Coordination between the adaptive bolus calculator and the controller was required to achieve the desired performance. For testing purposes, the clinically validated Imperial College Artificial Pancreas controller was employed.

          The proposed system was evaluated against itself but without bolus adaptation. The UVa-Padova T1DM v3.2 system was used to carry out a three-month in silico study on 11 adult and 11 adolescent virtual subjects taking into account inter-and intra-subject variability of insulin requirements and uncertainty on carbohydrate intake.

          Results

          Overall, the closed-loop controller enhanced by an adaptive bolus calculator improves glycemic control when compared to its non-adaptive counterpart. In particular, the following statistically significant improvements were found (non-adaptive vs. adaptive). Adults: mean glucose 142.2±9.4 vs. 131.8±4.2 mg/dl; percentage time in target [70, 180] mg/dl, 82.0±7.0 vs. 89.5±4.2; percentage time above target 17.7±7.0 vs. 10.2±4.1. Adolescents: mean glucose 158.2±21.4 vs. 140.5±13.0 mg/dl; percentage time in target, 65.9±12.9 vs. 77.5±12.2; percentage time above target, 31.7±13.1 vs. 19.8±10.2. Note that no increase in percentage time in hypoglycemia was observed.

          Conclusion

          Using an adaptive meal bolus calculator within a closed-loop control system has the potential to improve glycemic control in type 1 diabetes when compared to its non-adaptive counterpart.

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          Author and article information

          Journal
          8506513
          Comput Methods Programs Biomed
          Comput Methods Programs Biomed
          Computer methods and programs in biomedicine
          0169-2607
          1872-7565
          1 July 2017
          1 June 2017
          17 May 2019
          : 146
          : 125-131
          Affiliations
          [1 ]Centre for Bio-Inspired Technology, Institute of Biomedical Engineering, Imperial College London, London, United Kingdom
          [2 ]Institut Universitari d'Automàtica i Informàtica Industrial, Universitat Politècnica de València, València, Spain
          [3 ]Charing Cross Hospital, Imperial College Healthcare NHS Trust, London, United Kingdom
          Article
          PMC6522376 PMC6522376 6522376 ems82887
          10.1016/j.cmpb.2017.05.010
          6522376
          28688482
          0089c845-aff4-431a-a3fd-c056bf1c1f71
          History
          Categories
          Article

          case-based reasoning,diabetes,artificial pancreas,run-to-run control

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