scholarly journals Use of apps for physical activity in type 1 diabetes: current status and requirements for future development

2019 ◽  
Vol 10 ◽  
pp. 204201881983929 ◽  
Author(s):  
Olga Kordonouri ◽  
Michael C. Riddell
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Caloric Intake ◽  
Glucose Monitoring ◽  
Current Status ◽  
Treatment Modalities ◽  
Activity Levels ◽  
Smartphone Apps ◽  
Physical Activity Monitoring

Smartphone technologies, and the applications (apps) that they host, are developing rapidly mainly with regard to communication, information processing, design, features and connectivity with other devices. Technologies used in modern treatment modalities and monitoring of type 1 diabetes are also rapidly evolving and can communicate with smartphones and apps. Therefore, numerous web-based and smartphone apps aim to provide information and various patient data metrics (e.g. caloric intake, activity levels, glucose monitoring) that can be accessed and processed for decision support by smartphone apps. In this narrative review, we highlight current information about the effectiveness of interventions through smartphone apps with a focus on apps designed to give guidance to patients with type 1 diabetes on physical activity monitoring and glucose control during and after structured exercise sessions, as these patients are experiencing huge therapeutic challenges during exercise. Furthermore, we propose a number of critical elements for future apps designed for people with type 1 diabetes.

scholarly journals Effects of Flash Glucose Monitoring on Dietary Variety, Physical Activity, and Self-Care Behaviors in Patients with Diabetes

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Satoshi Ida ◽  
Ryutaro Kaneko ◽  
Kanako Imataka ◽  
Kaoru Okubo ◽  
Yoshitaka Shirakura ◽  
...  
Keyword(s):  
Physical Activity ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Type 1 Diabetes Mellitus ◽  
Glucose Monitoring ◽  
Flash Glucose Monitoring

The aim of this study was to evaluate the effects of flash glucose monitoring on dietary variety, physical activity, and self-care behavior in patients with diabetes. This study included outpatients with diabetes using insulin who presented at the Department of Diabetes and Metabolism of the Ise Red Cross Hospital. Before initiating flash glucose monitoring and 12 weeks after its initiation, blood glucose-related parameters were assessed and self-administered questionnaires were completed (Dietary Variety Score (DVS), the International Physical Activity Questionnaire (IPAQ), the Summary of Diabetes Self-Care Activities Measure (SDSCA), and the Diabetes Treatment Satisfaction Questionnaire (DTSQ)) and compared between the two time points. We analyzed 42 patients with type 1 diabetes mellitus and 48 patients with type 2 diabetes mellitus. In patients with type 2 diabetes mellitus, but not type 1 diabetes mellitus, there was an increase in moderate/high category scores for IPAQ (P<0.001) and for treatment satisfaction reported via DTSQ. Furthermore, in patients with type 2 diabetes mellitus, the glycemic excursion index improved significantly and HbA1c decreased significantly (from 7.7 (1.2) to 7.4 (0.8), P=0.025). Results showed that standard deviation and mean amplitude of glycemic excursions significantly decreased in patients with type 1 diabetes mellitus (from 71.2 (20.4) to 66.2 (17.5), P=0.033 and from 124.6 (31.9) to 108.1 (28.4), P<0.001, respectively). Flash glucose monitoring is a useful tool to improve physical activity in patients with type 2 diabetes.

scholarly journals Patient and disease characteristics of adult patients with type 1 diabetes in Germany: an analysis of the DPV and DIVE databases

2019 ◽  
Vol 10 ◽  
pp. 204201881983086 ◽  
Author(s):  
Gesine van Mark ◽  
Stefanie Lanzinger ◽  
Ralf Barion ◽  
Michael Degenhardt ◽  
Simone Badis ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycosylated Hemoglobin ◽  
Glucose Monitoring ◽  
Severe Hypoglycemia ◽  
Current Status ◽  
Metabolic Pattern ◽  
Oral Antidiabetic ◽  
Hba1c Control ◽  
Long Acting

Background: An understanding of the current status of patients with type 1 diabetes mellitus (T1DM) can help to provide appropriate treatment. Methods: This was a retrospective analysis of the DIabetes Versorgungs-Evaluation (DIVE) and the Diabetes-Patienten-Verlaufsdokumentation (DPV) databases for Germany. Results: The analysis included 56,250 people with T1DM (54.2% male), a median age of 36.8 years, and a median diabetes duration of 12.4 years. 15.3% were obese (body mass index ≥ 30kg/m2). Long-acting insulin analogs were used by 53.3%, short-acting analogs by 72.1%, and oral antidiabetic drugs by 4.7%. Patients had a median glycosylated hemoglobin (HbA1c) of 7.8%. There was a drop in HbA1c and an increase in the rate of hypertension, oral antidiabetic drug use, and in the rate of severe hypoglycemia (all p < 0.01) with age. Flash glucose monitoring (FGM) showed the best glucose values with fewer complications compared to other monitoring systems. HbA1c and FBG were lower in patients using a pump versus multiple daily injections (MDIs; 7.7 versus 7.9% and 7.8 versus 8.7 mmol/l; all adjusted p < 0.01). Patients had a lower risk of at least one severe hypoglycemic or DKA episode during the most recent treatment year with pump treatment compared to MDI (9.4% versus 10.5% and 4.7% versus 6.1%, both adjusted p < 0.01). Conclusion: The data demonstrated less-than-optimal glycemic control in the young, an increasing metabolic pattern in T1DM with increasing age, a benefit of FGM to improve HbA1c control and adverse effects, as well as benefits of pump treatment over MDIs.

scholarly journals Physical Activity Levels of Adolescents with Type 1 Diabetes Physical Activity in T1D

2017 ◽  
Vol 29 (2) ◽  
pp. 213-219 ◽  
Author(s):  
Valderi Abreu de Lima ◽  
Luis Paulo Gomes Mascarenhas ◽  
Juliana Pereira Decimo ◽  
William Cordeiro de Souza ◽  
Anna Louise Stellfeld Monteiro ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Cardiorespiratory Fitness ◽  
Vigorous Physical Activity ◽  
Inverse Correlation ◽  
Activity Levels ◽  
Z Score ◽  
Intensity Physical Activity ◽  
Vigorous Intensity

The aim of this study was to evaluate the level of physical activity and cardiorespiratory fitness in teenagers with type 1 diabetes mellitus (T1D) in comparison with healthy scholar participants. Total of 154 teenagers (T1D = 45 and CON = 109). Height, weight, cardiorespiratory fitness (VO2max), and the level of physical activity by the Bouchard’s Physical Activity Record were measured, and glycated hemoglobin (HbA1c) in T1D. The VO2max was lower in the T1D (38.38 ± 7.54) in comparison with the CON (42.44 ± 4.65; p < .05). The VO2max had correlation with the amount of time of moderate-to-vigorous physical activity (r = .63; p = .0001) and an inverse correlation with sedentary activities (r= -0.46; p = .006). In the T1D the levels of HbA1c had an inverse correlation with the amount of time of moderate-to-vigorous physical activity (r= -0.34; p = .041) and correlation with the BMI z-score (r = .43; p = .017). Only 37,8% of the participants in the T1D reached the adequate amount of daily moderate-to-vigorous intensity physical activity, in the CON 81,7% reached the WHO’s recommendation. Conclusion: T1D had less cardiorespiratory capacity then healthy controls, the teenagers of T1D with lower BMI z-score and that dedicated a greater time in moderate-to-vigorous intensity physical activity demonstrated a better glycemic control.

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 Blood Glucose Level Forecasting on Type-1-Diabetes Subjects during Physical Activity: A Comparative Analysis of Different Learning Techniques

2021 ◽  
Vol 8 (6) ◽  
pp. 72
Author(s):  
Benedetta De Paoli ◽  
Federico D’Antoni ◽  
Mario Merone ◽  
Silvia Pieralice ◽  
Vincenzo Piemonte ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Mean Squared Error ◽  
Glucose Monitoring ◽  
Online Training ◽  
Machine Learning Algorithms ◽  
Glucose Levels ◽  
Blood Glucose Levels

Background: Type 1 Diabetes Mellitus (T1DM) is a widespread chronic disease in industrialized countries. Preventing blood glucose levels from exceeding the euglycaemic range would reduce the incidence of diabetes-related complications and improve the quality of life of subjects with T1DM. As a consequence, in the last decade, many Machine Learning algorithms aiming to forecast future blood glucose levels have been proposed. Despite the excellent performance they obtained, the prediction of abrupt changes in blood glucose values produced during physical activity (PA) is still one of the main challenges. Methods: A Jump Neural Network was developed in order to overcome the issue of predicting blood glucose values during PA. Three learning configurations were developed and tested: offline training, online training, and online training with reinforcement. All configurations were tested on six subjects suffering from T1DM that held regular PA (three aerobic and three anaerobic) and exploited Continuous Glucose Monitoring (CGM). Results: The forecasting performance was evaluated in terms of the Root-Mean-Squared-Error (RMSE), according to a paradigm of Precision Medicine. Conclusions: The online learning configurations performed better than the offline configuration in total days but not on the only CGM associated with the PA; thus, the results do not justify the increased computational burden because the improvement was not significant.

scholarly journals Physical Activity in Adolescent Females with Type 1 Diabetes

2010 ◽  
Vol 2010 ◽  
pp. 1-6 ◽  
Author(s):  
Bahareh Schweiger ◽  
Georgeanna Klingensmith ◽  
Janet K. Snell-Bergeon
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Vigorous Physical Activity ◽  
Linear Regression Analysis ◽  
Adolescent Females ◽  
Self Report ◽  
Activity Levels ◽  
Physically Active

Objective. We sought to identify amount of physical activity and relationship of physical activity to glycemic control among adolescent females 11 to 19 years of age with type 1 diabetes mellitus (T1DM). We also sought to evaluate associations of age and ethnicity with physical activity levels.Research Design and Methods. Adolescent females ages 11–19 years (n=203) were recruited during their outpatient diabetes appointment. Physical activity was obtained by self-report and was categorized as the number of days subjects had accumulated 60 minutes of moderate-to-vigorous physical activity during the past 7 days and for a typical week.Results. Girls reported being physically active for at least 60 minutes per day on2.7±2.3days in the last week, and on3.1±2.2days in a typical week. A greater number of physically active days in a typical week were associated with lower A1c (P=.049) in linear regression analysis.Conclusion. Adolescent females with T1DM report exercising for at least 60 minutes about 3 days per week, which does not meet the international recommendations of 60 minutes of moderate-to-vigorous activity per day. It is particularly important that adolescent girls with T1DM be encouraged to exercise since a greater number of physically active days per week is associated with better glycemic control.

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