Nocturnal Hypoglycemia and Physical Activity in Children With Diabetes: New Insights by Continuous Glucose Monitoring and Accelerometry

Bachmann, Sara; Hess, Melanie; Martin‐Diener, Eva; Denhaerynck, Kris; Zumsteg, Urs

doi:10.2337/dc16-0411

Cited by 35 publications

(22 citation statements)

References 6 publications

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“…An advantage of the approach presented in this work is the inclusion of features related with physical activity as input for the prediction models. It has already been shown that daytime physical activity is strongly related with NH [38][39][40]; however, previous investigations intended for NH prediction did not consider such information [28,41]. In our proposal, physical activity data were collected by the wristband.…”

Section: Discussionmentioning

confidence: 99%

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

Bertachi

Viñals

Biagi

et al. 2020

Sensors

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(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.

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Section: Discussionmentioning

confidence: 99%

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

Bertachi

Viñals

Biagi

et al. 2020

Sensors

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“…Children and adolescents using an isCGM should perform a scan at least twice during the nocturnal period (e.g. at 01:00 hours and 04:00 hours) due to the increased risk of nocturnal hypoglycaemia [101][102][103][104] (D), especially after exercise [81,[104][105][106] (D). Parents or other care providers can be alerted using the remote monitoring function within CGMs, which can support parents in their effort to avoid nocturnal hypoglycaemia in children [91] (D).…”

Section: Children and Adolescents With Type 1 Diabetesmentioning

confidence: 99%

Glucose management for exercise using continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems in type 1 diabetes: position statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) endorsed by JDRF and supported by the American Diabetes Association (ADA)

et al. 2020

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Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (i.e. before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes.

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“…Fear of hypoglycemia is the most common barrier to physical activity for children/adolescents and adults with T1D [43, 52–55], and several studies have demonstrated increased risk of hypoglycemia resulting from exercise [56–58]. Lack of time and work schedules for adults and parents are also barriers [53, 59].…”

Section: Physical Activity and Individuals With T1dmentioning

confidence: 99%

Biopsychosocial Aspects of Weight Management in Type 1 Diabetes: a Review and Next Steps

et al. 2017

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Purpose of Review This review aims to summarize the type 1 diabetes (T1D) and weight literature with an emphasis on barriers associated with weight management, the unique T1D-specific factors that impact weight loss success, maladaptive and adaptive strategies for weight loss, and interventions to promote weight loss. Recent Findings Weight gain is associated with intensive insulin therapy. Overweight and obese weight status in individuals with T1D is higher than the general population and prevalence is rising. A variety of demographic (e.g., female sex), clinical (e.g., greater insulin needs), environmental (e.g., skipping meals), and psychosocial (e.g., depression, stress) factors are associated with overweight/obese weight status in T1D. Fear of hypoglycemia is a significant barrier to engagement in physical activity. Studies evaluating adaptive weight loss strategies in people with T1D are limited. Summary There is a growing literature highlighting the prevalence and seriousness of overweight and obesity among both youth and adults with T1D. There is an urgent need to develop evidence-based weight management guidelines and interventions that address the unique concerns of individuals with T1D and that concurrently address glycemic control.

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Nocturnal Hypoglycemia and Physical Activity in Children With Diabetes: New Insights by Continuous Glucose Monitoring and Accelerometry

Abstract: Figure 1-Risk of nocturnal hypoglycemia correlated to bedtime glucose.

Cited by 35 publications

References 6 publications

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

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

Biopsychosocial Aspects of Weight Management in Type 1 Diabetes: a Review and Next Steps

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