scholarly journals Continuous Glucose Monitoring and Exercise in Type 1 Diabetes: Past, Present and Future

Biosensors ◽  
2018 ◽  
Vol 8 (3) ◽  
pp. 73 ◽  
Author(s):  
Shaelyn Houlder ◽  
Jane Yardley
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Continuous Glucose Monitoring ◽  
Closed Loop ◽  
Artificial Pancreas ◽  
Glucose Monitoring ◽  
Post Exercise ◽  
Exercise Period ◽  
Academic Search

Prior to the widespread use of continuous glucose monitoring (CGM), knowledge of the effects of exercise in type 1 diabetes (T1D) was limited to the exercise period, with few studies having the budget or capacity to monitor participants overnight. Recently, CGM has become a staple of many exercise studies, allowing researchers to observe the otherwise elusive late post-exercise period. We performed a strategic search using PubMed and Academic Search Complete. Studies were included if they involved adults with T1D performing exercise or physical activity, had a sample size greater than 5, and involved the use of CGM. Upon completion of the search protocol, 26 articles were reviewed for inclusion. While outcomes have been variable, CGM use in exercise studies has allowed the assessment of post-exercise (especially nocturnal) trends for different exercise modalities in individuals with T1D. Sensor accuracy is currently considered adequate for exercise, which has been crucial to developing closed-loop and artificial pancreas systems. Until these systems are perfected, CGM continues to provide information about late post-exercise responses, to assist T1D patients in managing their glucose, and to be useful as a tool for teaching individuals with T1D about exercise.

scholarly journals Artificial Pancreas Systems and Physical Activity in Patients with Type 1 Diabetes: Challenges, Adopted Approaches, and Future Perspectives

2019 ◽  
Vol 13 (6) ◽  
pp. 1077-1090 ◽  
Author(s):  
Sémah Tagougui ◽  
Nadine Taleb ◽  
Joséphine Molvau ◽  
Élisabeth Nguyen ◽  
Marie Raffray ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Healthcare Professionals ◽  
Therapeutic Option ◽  
Artificial Pancreas ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Delivery Methods ◽  
Current State

Physical activity is important for patients living with type 1 diabetes (T1D) but limited by the challenges associated with physical activity induced glucose variability. Optimizing glycemic control without increasing the risk of hypoglycemia is still a hurdle despite many advances in insulin formulations, delivery methods, and continuous glucose monitoring systems. In this respect, the artificial pancreas (AP) system is a promising therapeutic option for a safer practice of physical activity in the context of T1D. It is important that healthcare professionals as well as patients acquire the necessary knowledge about how the AP system works, its limits, and how glucose control is regulated during physical activity. This review aims to examine the current state of knowledge on exercise-related glucose variations especially hypoglycemic risk in T1D and to discuss their effects on the use and development of AP systems. Though effective and highly promising, these systems warrant further research for an optimized use around exercise.

scholarly journals Prediction of Nocturnal Hypoglycemia in Adults with Type 1 Diabetes under Multiple Daily Injections Using Continuous Glucose Monitoring and Physical Activity Monitor

Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1705 ◽  
Author(s):  
Arthur Bertachi ◽  
Clara Viñals ◽  
Lyvia Biagi ◽  
Ivan Contreras ◽  
Josep Vehí ◽  
...  
Keyword(s):  
Physical Activity ◽  
Machine Learning ◽  
Type 1 Diabetes ◽  
Continuous Glucose Monitoring ◽  
Prediction Models ◽  
Glucose Monitoring ◽  
Supervised Machine Learning ◽  
Nocturnal Hypoglycemia ◽  
Activity Tracker

(1) Background: nocturnal hypoglycemia (NH) is one of the most challenging side effects of multiple doses of insulin (MDI) therapy in type 1 diabetes (T1D). This work aimed to investigate the feasibility of a machine-learning-based prediction model to anticipate NH in T1D patients on MDI. (2) Methods: ten T1D adults were studied during 12 weeks. Information regarding T1D management, continuous glucose monitoring (CGM), and from a physical activity tracker were obtained under free-living conditions at home. Supervised machine-learning algorithms were applied to the data, and prediction models were created to forecast the occurrence of NH. Individualized prediction models were generated using multilayer perceptron (MLP) and a support vector machine (SVM). (3) Results: population outcomes indicated that more than 70% of the NH may be avoided with the proposed methodology. The predictions performed by the SVM achieved the best population outcomes, with a sensitivity and specificity of 78.75% and 82.15%, respectively. (4) Conclusions: our study supports the feasibility of using ML techniques to address the prediction of nocturnal hypoglycemia in the daily life of patients with T1D on MDI, using CGM and a physical activity tracker.

Evaluation of the results obtained with flash continuous glucose monitoring in patients with type 1 diabetes after a structured training program

2020 ◽  
Author(s):  
Peris Begoña Pla ◽  
Leví Ana M Ramos ◽  
Vargas Marcos Lahera ◽  
Casieri Raffaele Carraro ◽  
Moreno Nerea Aguirre ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Training Program ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring

The impact of real-time continuous glucose monitoring on metabolic control in children with type 1 diabetes

2020 ◽  
Author(s):  
Ruxandra Calapod Ioana ◽  
Irina Bojoga ◽  
Duta Simona Gabriela ◽  
Ana-Maria Stancu ◽  
Amalia Arhire ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Real Time ◽  
Metabolic Control ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
The Impact

Increased Time-in-Range with Sotagliflozin as Adjunct Therapy to Insulin in Adults with Type 1 Diabetes as Demonstrated by 24-Week Continuous Glucose Monitoring (inTandem1, inTandem2)

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1179-P ◽  
Author(s):  
THOMAS DANNE ◽  
BERTRAND CARIOU ◽  
JOHN B. BUSE ◽  
SATISH K. GARG ◽  
JULIO ROSENSTOCK ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Adjunct Therapy ◽  
Time In Range

Adults with Type 1 Diabetes (T1D) Using Continuous Glucose Monitoring (CGM) Report Disease Has Little Impact on Daily Functioning—T1D Exchange

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 932-P
Author(s):  
LUDI FAN ◽  
COLLEEN GAREY ◽  
JINGWEN LIU ◽  
BETH MITCHELL ◽  
JEOFFREY BISPHAM ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Daily Functioning

955-P: Evaluating Early Initiation of Continuous Glucose Monitoring (CGM) among Youth Diagnosed with Type 1 Diabetes (T1D)

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 955-P
Author(s):  
JESSIE J. WONG ◽  
SUSAN MICHELLE CLAY ◽  
GREGORY P. FORLENZA ◽  
SARAH HANES ◽  
R. PAUL WADWA ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Early Initiation
Sign in / Sign up

Export Citation Format

Share Document