Identification of Main Factors Explaining Glucose Dynamics During and Immediately After Moderate Exercise in Patients With Type 1 Diabetes.
BACKGROUND
Physical activity is recommended for patients with type 1 diabetes (T1D). However, without proper management, it can lead to higher risk for hypoglycemia and impaired glycemic control. In this work, we identify the main factors explaining the blood glucose dynamics during exercise in T1D. We then propose a prediction model to quantify the glycemic drop induced by a mild to moderate physical activity.


METHODS
A meta-data analysis was conducted over 59 T1D patients from 4 different studies in the United States and France (37 men and 22 women; 47 adults; weight, 71.4 ± 10.6 kg; age, 42 ± 10 years; 12 adolescents: weight, 60.7 ± 12.5 kg; age, 14.0 ± 1.4 years). All participants had physical activity between 3 and 5 pm at a mild to moderate intensity for approximately 30 to 45 min. A multiple linear regression analysis was applied to the data to identify the main parameters explaining the glucose dynamics during such physical activity.


RESULTS
The blood glucose at the beginning of exercise ([Formula: see text]), the ratio of insulin on board over total daily insulin ([Formula: see text]) and the age as a categorical variable (1 for adult, 0 for adolescents) were significant factors involved in glucose evolution at exercise (all P < .05). The multiple linear regression model has an R-squared of .6.


CONCLUSIONS
The main factors explaining glucose dynamics in the presence of mild-to-moderate exercise in T1D have been identified. The clinical parameters are formally quantified using real data collected during clinical trials. The multiple linear regression model used to predict blood glucose during exercise can be applied in closed-loop control algorithms developed for artificial pancreas.
Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA Department of Endocrinology, Diabetes, Nutrition and Clinical Investigation Center INSERM 1411, Montpellier University Hospital and Institute of Functional Genomics, CNRS 5203/INSERM U1191/University of Montpellier, Montpellier, France.
Najib
N
Ben Brahim
Department of Endocrinology, Diabetes, Nutrition and Clinical Investigation Center INSERM 1411, Montpellier University Hospital and Institute of Functional Genomics, CNRS 5203/INSERM U1191/University of Montpellier, Montpellier, France.
Jerome
J
Place
Department of Endocrinology, Diabetes, Nutrition and Clinical Investigation Center INSERM 1411, Montpellier University Hospital and Institute of Functional Genomics, CNRS 5203/INSERM U1191/University of Montpellier, Montpellier, France.
Eric
E
Renard
Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA Department of Endocrinology, Diabetes, Nutrition and Clinical Investigation Center INSERM 1411, Montpellier University Hospital and Institute of Functional Genomics, CNRS 5203/INSERM U1191/University of Montpellier, Montpellier, France mb6nt@eservices.virginia.edu.
Marc D
MD
Breton
D000293:Adolescent; D000328:Adult; D000465:Algorithms; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000187:drug effects / Q000378:metabolism*; D003922:Diabetes Mellitus, Type 1 / Q000097:blood* / Q000175:diagnosis / Q000188:drug therapy / Q000503:physiopathology; D004867:Equipment Design; D015444:Exercise; D005260:Female; D006801:Humans; D007004:Hypoglycemic Agents / Q000008:administration & dosage; D007328:Insulin / Q000008:administration & dosage; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D019397:Pancreas, Artificial; D016032:Randomized Controlled Trials as Topic; D013997:Time Factors
D015415:Biomarkers; D001786:Blood Glucose; D007004:Hypoglycemic Agents; D007328:Insulin
T1DM; artificial pancreas; exercise; hypoglycemia; physical activity