Continuous Glucose Monitors and Activity Trackers to Inform Insulin Dosing in Type 1 Diabetes: The University of Virginia Contribution

التفاصيل البيبلوغرافية
العنوان: Continuous Glucose Monitors and Activity Trackers to Inform Insulin Dosing in Type 1 Diabetes: The University of Virginia Contribution
المؤلفون: Basak Ozaslan, Chiara Fabris, Marc D. Breton
المصدر: Sensors (Basel, Switzerland)
Sensors
Volume 19
Issue 24
بيانات النشر: MDPI, 2019.
سنة النشر: 2019
مصطلحات موضوعية: Research design, Blood Glucose, medicine.medical_specialty, endocrine system diseases, type 1 diabetes, medicine.medical_treatment, 030209 endocrinology & metabolism, Hypoglycemia, Biochemistry, Article, Analytical Chemistry, 03 medical and health sciences, 0302 clinical medicine, Bolus (medicine), Insulin Infusion Systems, medicine, Humans, Hypoglycemic Agents, Insulin, 030212 general & internal medicine, Dosing, Electrical and Electronic Engineering, Instrumentation, Exercise, Glycemic, smart insulin dosing, Type 1 diabetes, business.industry, Blood Glucose Self-Monitoring, nutritional and metabolic diseases, medicine.disease, Atomic and Molecular Physics, and Optics, Postprandial, Diabetes Mellitus, Type 1, Emergency medicine, continuous glucose monitors, activity trackers, business
الوصف: Objective: Suboptimal insulin dosing in type 1 diabetes (T1D) is frequently associated with time-varying insulin requirements driven by various psycho-behavioral and physiological factors influencing insulin sensitivity (IS). Among these, physical activity has been widely recognized as a trigger of altered IS both during and following the exercise effort, but limited indication is available for the management of structured and (even more) unstructured activity in T1D. In this work, we present two methods to inform insulin dosing with biosignals from wearable sensors to improve glycemic control in individuals with T1D. Research Design and Methods: Continuous glucose monitors (CGM) and activity trackers are leveraged by the methods. The first method uses CGM records to estimate IS in real time and adjust the insulin dose according to a person&rsquo
s insulin needs
the second method uses step count data to inform the bolus calculation with the residual glucose-lowering effects of recently performed (structured or unstructured) physical activity. The methods were tested in silico within the University of Virginia/Padova T1D Simulator. A standard bolus calculator and the proposed &ldquo
smart&rdquo
systems were deployed in the control of one meal in presence of increased/decreased IS (Study 1) and following a 1-hour exercise bout (Study 2). Postprandial glycemic control was assessed in terms of time spent in different glycemic ranges and low/high blood glucose indices (LBGI/HBGI), and compared between the dosing strategies. Results: In Study 1, the CGM-informed system allowed to reduce exposure to hypoglycemia in presence of increased IS (percent time <
70 mg/dL: 6.1% versus 9.9%
LBGI: 1.9 versus 3.2) and exposure to hyperglycemia in presence of decreased IS (percent time >
180 mg/dL: 14.6% versus 18.3%
HBGI: 3.0 versus 3.9), tending toward optimal control. In Study 2, the step count-informed system allowed to reduce hypoglycemia (percent time <
70 mg/dL: 3.9% versus 13.4%
LBGI: 1.7 versus 3.2) at the cost of a minor increase in exposure to hyperglycemia (percent time >
180 mg/dL: 11.9% versus 7.5%
HBGI: 2.4 versus 1.5). Conclusions: We presented and validated in silico two methods for the smart dosing of prandial insulin in T1D. If seen within an ensemble, the two algorithms provide alternatives to individuals with T1D for improving insulin dosing accommodating a large variety of treatment options. Future work will be devoted to test the safety and efficacy of the methods in free-living conditions.
وصف الملف: application/pdf
اللغة: English
تدمد: 1424-8220
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b713a6c9e804474eb085a0f29c00bd9Test
http://europepmc.org/articles/PMC6961036Test
حقوق: OPEN
رقم الانضمام: edsair.doi.dedup.....3b713a6c9e804474eb085a0f29c00bd9
قاعدة البيانات: OpenAIRE