In silico comparison of control strategies of insulin therapy for type 1 diabetes during physical activity using the extended sorensen glucoregulatory model

2019 ◽  
Author(s):  
B. Romanski ◽  
C. Benner ◽  
B. Glasmacher ◽  
S. Leonhardt ◽  
M. Walter
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Insulin Therapy ◽  
In Silico ◽  
Control Strategies

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

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5386 ◽  
Author(s):  
Chiara Fabris ◽  
Basak Ozaslan ◽  
Marc D. Breton
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
In Silico ◽  
University Of Virginia ◽  
Percent Time ◽  
Activity Trackers ◽  
Continuous Glucose Monitors ◽  
The University

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’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 “smart” 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.

scholarly journals The Effect of Lockdown and Physical Activity on Glycemic Control in Italian Children and Young Patients With Type 1 Diabetes

2021 ◽  
Vol 12 ◽  
Author(s):  
Nicola Minuto ◽  
Marta Bassi ◽  
Carolina Montobbio ◽  
Francesco Vinci ◽  
Claudia Mercuri ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Insulin Therapy ◽  
Young Patients ◽  
Lifestyle Changes ◽  
Reduced Physical Activity ◽  
Italian Children ◽  
The Impact

AimsThe purpose of the study was to evaluate the impact of the lockdown established by the Italian government to limit the spread of Coronavirus disease (COVID-19) on glycemic control in a large sample of patients with type 1 diabetes (T1D) based on age, type of insulin therapy, number of telemedicine visits and physical activity.Material and MethodsWe retrospectively evaluated glycemic control in young T1D patients using the DexcomG6® system before the Italian lockdown (February 10–23, 2020—Time 0) and during lockdown (April 17–30, 2020—Time 1). Data on age, type of insulin therapy, number of telemedicine visits and physical activity of 202 patients with T1D and a median age of 18.2 years (range: 6–39) were collected.ResultsData showed a significant improvement of TIR from 54.58% at T0 to 59.09% at T1 (p ≤0.0001). Glycemic control improved significantly in patients ≥14 years old, showing the best outcome in the “university students and young adults” group (55.40% at T0 and 61.37% at T1, p ≤0.001). All patients reduced physical activity during lockdown; in the 56 patients of “intense physical activity” group both at T0 and T1 TIR increased from ±56.91 to 64.11% (p ≤0.0001).ConclusionsOverall, the lockdown led to an unexpected improvement in glycemic control of young patients with T1D. A healthier and stressless lifestyle changes in association with the maintenance of physical activity resulted in a significant age-proportional improvement in glycemic control.

1129-P: Effect of Sotagliflozin Added to Insulin Therapy on Beta-Hydroxybutyrate in Patients with Type 1 Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1129-P
Author(s):  
ANNE L. PETERS ◽  
THOMAS DANNE ◽  
SANGEETA SAWHNEY ◽  
PHILLIP L. BANKS ◽  
MICHAEL J. DAVIES ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Insulin Therapy ◽  
Beta Hydroxybutyrate

89-LB: The Effect of GIP on Plasma Glucose in a Setting of Prandial Insulin Overdose and Physical Activity after Meal Intake in Patients with Type 1 Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 89-LB ◽  
Author(s):  
BJØRN HOE ◽  
SEBASTIAN M. NGUYEN HEIMBÜRGER ◽  
LÆRKE S. GASBJERG ◽  
MADS B. LYNGGAARD ◽  
BOLETTE HARTMANN ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Plasma Glucose ◽  
Prandial Insulin ◽  
Meal Intake ◽  
Insulin Overdose
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