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Automatically accounting for physical activity in insulin dosing for type 1 diabetes.

作者信息

Ozaslan Basak, Patek Stephen D, Fabris Chiara, Breton Marc D

机构信息

University of Virginia, Charlottesville, VA, United States.

Dexcom, Inc., Charlottesville, VA, United States.

出版信息

Comput Methods Programs Biomed. 2020 Dec;197:105757. doi: 10.1016/j.cmpb.2020.105757. Epub 2020 Sep 21.

Abstract

BACKGROUND AND OBJECTIVE

Type 1 diabetes is a disease characterized by lifelong insulin administration to compensate for the autoimmune destruction of insulin-producing pancreatic beta-cells. Optimal insulin dosing presents a challenge for individuals with type 1 diabetes, as the amount of insulin needed for optimal blood glucose control depends on each subject's varying needs. In this context, physical activity represents one of the main factors altering insulin requirements and complicating treatment decisions. This work aims to develop and test in simulation a data-driven method to automatically incorporate physical activity into daily treatment decisions to optimize mealtime glycemic control in individuals with type 1 diabetes.

METHODS

We leveraged glucose, insulin, meal and physical activity data collected from twenty-three individuals to develop a method that (i) tracks and quantifies the accumulated glycemic impact from daily physical activity in real-time, (ii) extracts an individualized routine physical activity profile, and (iii) adjusts insulin doses according to the prolonged changes in insulin needs due to deviations in daily physical activity in a personalized manner. We used the data replay simulation framework developed at the University of Virginia to "re-simulate" the clinical data and estimate the performances of the new decision support system for physical activity informed insulin dosing against standard insulin dosing. The paired t-test is used to compare the performances of dosing methods with p < 0.05 as the significance threshold.

RESULTS

Simulation results show that, compared with standard dosing, the proposed physical-activity informed insulin dosing could result in significantly less time spent in hypoglycemia (15.3± 8% vs. 11.1± 4%, p = 0.007) and higher time spent in the target glycemic range (66.1± 11.7% vs. 69.6± 12.2%, p < 0.01) and no significant difference in the time spent above the target range(26.6± 1.4 vs. 27.4± 0.1, p = 0.5).

CONCLUSIONS

Integrating daily physical activity, as measured by the step count, into insulin dose calculations has the potential to improve blood glucose control in daily life with type 1 diabetes.

摘要

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Automatically accounting for physical activity in insulin dosing for type 1 diabetes.
Comput Methods Programs Biomed. 2020 Dec;197:105757. doi: 10.1016/j.cmpb.2020.105757. Epub 2020 Sep 21.

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Metrics for glycaemic control - from HbA to continuous glucose monitoring.血糖控制的指标——从 HbA 到连续血糖监测。
Nat Rev Endocrinol. 2017 Jul;13(7):425-436. doi: 10.1038/nrendo.2017.3. Epub 2017 Mar 17.
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Exercise management in type 1 diabetes: a consensus statement.1 型糖尿病的运动管理:共识声明。
Lancet Diabetes Endocrinol. 2017 May;5(5):377-390. doi: 10.1016/S2213-8587(17)30014-1. Epub 2017 Jan 24.

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