Comparing two treatment approaches for patients with type 1 diabetes during aerobic exercise: a randomised, crossover study

Abstract In a randomised, counterbalanced, crossover design, eight men with type 1 diabetes (T1D; mean ± SD age: 27.6 ± 11.4 years) reduced insulin (INS) by 50% of their normal dose or consumed carbohydrates equivalent to 1 g of carbohydrate/kg of their body weight without the usual insulin bolus (CARBS) over two sessions, held a week apart. Each session included standardised meals, a 45-minute treadmill-walk at 7.24 km.h-1 and a six-minute walk test (6MWT). Rate of perceived exertion (RPE), blood glucose, blood ketone and blood lactate measures were taken before, during and immediately after the aerobic exercise. The distance covered in metres and the predicted VO2 max (mL⋅kg−1⋅min−1) were also calculated for the 6MWT. Participants completing the INS intervention spent more time in normoglycaemia (242 ± 135 min vs 88 ± 132 min; P < 0.01) and less time in hyperglycaemia (41 ± 95 min vs 154 ± 125 min; P = 0.01) as compared to the CARBS intervention. Mild hypoglycaemia occurred in two participants during INS and no participants during CARBS. Furthermore, there was no significant difference for blood lactate, ketone, RPE, distance covered and predicted VO2 max between interventions. Based on this pilot study, INS intervention appears to be the best approach for maintaining blood glucose levels in those with T1D during aerobic exercise, though this does need evaluating in other groups, including women, children and those with sub-optimal glycaemic control. Trial registration: ACTRN12619001397101p. Registered 09 September 2019, http://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378264

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Comparing Two Treatment Approaches for Patients with Type 1 Diabetes During Aerobic Exercise: A Randomised, Crossover Study

10.21203/rs.3.rs-33528/v1 ◽

2020 ◽

Author(s):

Varun Vartak ◽

Lynne Chepulis ◽

Matthew Driller ◽

Ryan G. Paul

Keyword(s):

Type 1 Diabetes ◽

Blood Glucose ◽

Aerobic Exercise ◽

Blood Lactate ◽

Perceived Exertion ◽

Trial Registration ◽

Glucose Levels ◽

Significant Difference ◽

Mild Hypoglycaemia

Abstract In a randomised, counterbalanced, crossover design, eight men with type 1 diabetes (T1D; mean ± SD age: 27.6 ± 11.4 years) reduced insulin (INS) or consumed carbohydrates without the usual insulin bolus (CARBS) over two sessions, held a week apart. Each session included standardised meals, a 45-minute treadmill-walk at 7.24 km.h-1 and a six-minute walk test (6MWT). Rate of perceived exertion (RPE), blood glucose, blood ketone and blood lactate measures were taken before, during and immediately after the aerobic exercise. The distance covered and the predicted VO2 max were also calculated for the 6MWT. Participants completing the INS intervention spent more time in normoglycaemia (P < 0.01) and less time in hyperglycaemia (P = 0.01) as compared to the CARBS intervention. Mild hypoglycaemia occurred in two participants during INS and no participants during CARBS. Furthermore, there was no significant difference for blood lactate, ketone, RPE, distance covered and predicted VO2 max between interventions. Six of the eight participants felt that their performance was better during INS, with all six (including the two participants that experienced mild hypoglycaemia) indicating that they would prefer to use this strategy for management of glycaemic during exercise in the future. Based on this pilot study, INS intervention appears to be the best approach for maintaining blood glucose levels in those with T1D during aerobic exercise, though this does need evaluating in other groups, including women, children and those with sub-optimal glycaemic control.Trial registration: ACTRN12619001397101p. Registered 09 September 2019, http://anzctr.org.au/Trial/Registration/TrialReview.aspx?id=378264

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Comparing Two Treatment Approaches for Patients with Type 1 Diabetes During Aerobic Exercise: a Randomised, Crossover Study

Sports Medicine - Open ◽

10.1186/s40798-021-00319-5 ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Varun Vartak ◽

Lynne Chepulis ◽

Matthew Driller ◽

Ryan G. Paul

Keyword(s):

Type 1 Diabetes ◽

Blood Glucose ◽

Aerobic Exercise ◽

Perceived Exertion ◽

Trial Registration ◽

Clinical Trial Registry ◽

Glucose Levels ◽

Significant Difference ◽

Mild Hypoglycaemia

Abstract Background In a randomised, counterbalanced, crossover design, eight men with type 1 diabetes (T1D; mean ± SD age, 27.6 ± 11.4 years) reduced insulin (INS) by 50% of their normal dose or consumed carbohydrates equivalent to 1 g of carbohydrate per kilogramme of their body weight without the usual insulin bolus (CARBS) over two sessions, held a week apart. Each session included standardised meals, a 45-min treadmill walk at 7.24 km h−1 and a 6-min walk test (6MWT). Rate of perceived exertion (RPE), blood glucose, ketone and lactate measures were taken before, during and immediately after the aerobic exercise. The distance covered in metres and the predicted VO2 max (mL kg−1 min−1) were also calculated for the 6MWT. Results Participants completing the INS intervention spent more time in normoglycaemia (242 ± 135 min vs 88 ± 132 min; P < 0.01) and less time in hyperglycaemia (41 ± 95 min vs 154 ± 125 min; P = 0.01) as compared to the CARBS intervention. Mild hypoglycaemia occurred in two participants during INS and no participants during CARBS. Furthermore, there was no significant difference for blood lactate, ketone, RPE, distance covered and predicted VO2 max between interventions. Conclusion Based on this pilot study, INS intervention appears to be the best approach for maintaining blood glucose levels in those with T1D during aerobic exercise, though this does need evaluation in other groups, including women, children and those with suboptimal glycaemic control. Trial Registration Australian New Zealand Clinical Trial Registry, ACTRN12619001397101p. Registered 09 September 2019.

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The value of blood glucose levels for the parameters of nocturnal sleep for patients with type 1 diabetes

Endocrine Abstracts ◽

10.1530/endoabs.49.ep541 ◽

2017 ◽

Author(s):

Ina Darashkevich ◽

Tatiana Mochort ◽

Lola Niconova ◽

Serhey Tishkovsky

Keyword(s):

Type 1 Diabetes ◽

Blood Glucose ◽

Nocturnal Sleep ◽

Glucose Levels ◽

Blood Glucose Levels

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776-P: Characteristics of Overnight Blood Glucose Levels Are Related to Sleep Quality in People with Type 1 Diabetes

Diabetes ◽

10.2337/db20-776-p ◽

2020 ◽

Vol 69 (Supplement 1) ◽

pp. 776-P

Author(s):

RACHEL BRANDT ◽

MINSUN PARK ◽

LAURIE T. QUINN ◽

MINSEUNG CHU ◽

YOUNGKWAN SONG ◽

...

Keyword(s):

Type 1 Diabetes ◽

Blood Glucose ◽

Sleep Quality ◽

Glucose Levels ◽

Blood Glucose Levels

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Deep learning and regression approaches to forecasting blood glucose levels for type 1 diabetes

Biomedical Signal Processing and Control ◽

10.1016/j.bspc.2021.102923 ◽

2021 ◽

Vol 69 ◽

pp. 102923

Author(s):

Meng Zhang ◽

Kevin B. Flores ◽

Hien T. Tran

Keyword(s):

Type 1 Diabetes ◽

Deep Learning ◽

Blood Glucose ◽

Glucose Levels ◽

Blood Glucose Levels

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The Effect of a Low-Glycemic Diet vs a Standard Diet on Blood Glucose Levels and Macronutrient Intake in Children with Type 1 Diabetes

Journal of the American Dietetic Association ◽

10.1016/j.jada.2008.10.047 ◽

2009 ◽

Vol 109 (2) ◽

pp. 303-307 ◽

Cited By ~ 30

Author(s):

Alisha J. Rovner ◽

Tonja R. Nansel ◽

Lauren Gellar

Keyword(s):

Type 1 Diabetes ◽

Blood Glucose ◽

Standard Diet ◽

Macronutrient Intake ◽

Glucose Levels ◽

Blood Glucose Levels

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T1D Hypoglycemia Prediction Algorithms: A Systematic Review (Preprint)

10.2196/preprints.34699 ◽

2021 ◽

Author(s):

Stella Tsichlaki ◽

Lefteris Koumakis ◽

Manolis Tsiknakis

Keyword(s):

Type 1 Diabetes ◽

Blood Glucose ◽

Digital Libraries ◽

Predictive Models ◽

Real Life ◽

Blood Glucose Monitoring ◽

Detection Techniques ◽

Glucose Levels ◽

Wide Range

BACKGROUND Diabetes is a chronic condition that necessitates regular monitoring and self-management of the patient's blood glucose levels. People with type 1 diabetes (T1D) can live a productive life if they receive proper diabetes care. Nonetheless, a loose glycemic control might increase the risk of developing hypoglycemia. This incident can occur due to a variety of causes, such as taking additional doses of insulin, skipping meals, or over-exercising. Mainly, the symptoms of hypoglycemia range from mild dysphoria to more severe conditions, if not detected in a timely manner. OBJECTIVE In this review, we report on innovative detection techniques and tactics for identifying and preventing hypoglycemic episodes, focusing on type 1 diabetes. METHODS A systematic literature search following the PRISMA guidelines was performed focusing on the “PUBMED”, “Google Scholar”, “IEEE Xplore” and “ACM” digital libraries to find articles about technologies related to hypoglycemia detection in type 1 diabetes patients. RESULTS The presented approaches have been utilized or devised to enhance blood glucose monitoring and boost its efficacy to forecast future glucose levels, which could aid the prediction of future episodes of hypoglycemia. We detected nineteen predictive models for hypoglycemia, specifically on type 1 diabetes, utilizing a wide range of algorithmic methodologies, spanning from statistics (10%) to machine learning (52%) and deep learning (38%). The algorithms employed most are the kalman filtering and classification models (SVM, KNN, random forests). The performance of the predictive models was found overall to be satisfactory, reaching accuracies between 70% and 99% which proves that such technologies are capable to facilitate the prediction of T1D hypoglycemia. CONCLUSIONS It is evident that CGM can improve the glucose control in diabetes but predictive models for hypo- and hyper- glycemia using only mainstream noninvasive sensors such as wristbands and smartwatches are foreseen to be the next step for mHealth in T1D. Prospective studies are required to demonstrate the value of such models in real-life mHealth interventions.

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A Review of Type 1 Diabetes (T1D)

Data Analytics in Medicine ◽

10.4018/978-1-7998-1204-3.ch002 ◽

2020 ◽

pp. 13-49

Author(s):

Eileen O'Donnell ◽

Liam O'Donnell

Keyword(s):

Type 1 Diabetes ◽

Blood Glucose ◽

Glucose Levels ◽

Blood Glucose Levels ◽

Acting Insulin ◽

Short Period ◽

Sporting Activities ◽

To Come

The diagnosis of Type 1 Diabetes (T1D) will come as an unwelcome surprise to most people. Within a short period of time, the person will have to come to understand and manage this chronic illness. The terminology associated with the T1D condition will also be totally new to the person: diabetes mellitus, pancreas, hyperglycaemia (hyper), hypoglycaemia (hypo), bolus (fast acting insulin), basal (slow acting insulin), ketones and blood glucose levels. The purpose of this article is to assist newly diagnosed patients' understanding of T1D, people who are already living with T1D, carers of people with T1D, partners and family members of someone with T1D, work colleagues, and friends who participate in the same sporting activities or go on holiday with a person who has T1D. In addition, this article reviews how people living with T1D can still enjoy exercise and maintain the best quality of life possible; whilst controlling the blood glucose levels in their body for the rest of their lives to prevent the onset of complications associated with diabetes.

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