Type 1 Diabetes Mellitus
Conditions
Keywords
type 1 diabetes, pediatric diabetes, sport, physical activity, automated insulin delivery
Brief summary
We hypothesize that the use of the Control-IQ system positively influences glycemic control in teenagers with type 1 diabetes during physical activity. To test this hypothesis, we will evaluate the glucose profiles (based on CGM metrics) of adolescents engaging in different types, intensities, and durations of physical activity over a 14-day period, in real-life conditions. We will compare glucose control on exercise days with that on sedentary days. As a secondary objective, we will investigate the influence of factors such as anthropometric characteristics, type and duration of exercise, the use of the exercise mode and other management strategies used for physical activity, on glycemic outcomes. Regarding the safety, we will report any episodes of severe hypoglycemia or diabetic ketoacidosis (DKA). This is an observational, open-label, non-randomized, real-world study. Each participant will be provided with a diary to record detailed information about physical activity sessions over a 14-day period, including type, intensity, and duration of exercise, and timing and composition of pre-exercise meals. Clear instructions on how to complete the diary will be provided. CGM metrics will be analyzed throughout the 14-day observation period, including time in range, time in tight range, time above range, time below range, mean glucose level, and coefficient of variation. A daily comparison will be performed between metrics recorded on days of physical activity and sedentary days, assessing the entire day as well as daytime (07:00-23:00) and nighttime (23:00-07:00) periods. The influence of factors such as anthropometrics, type of physical activity, the use of the exercise mode and other specific management strategies, type and duration of exercise, and pre-exercise meals on CGM metrics will be evaluated. The frequency of severe hypoglycemia and DKA episodes, as defined by international guidelines, will be assessed.
Interventions
Control-IQ is one of the second-generation AID technologies currently available worldwide and is approved for people \> 6 years. Control-IQ can predict glucose levels 30 minutes in advance and automatically adjust basal insulin delivery, providing corrective boluses if needed. The system can prevent hypoglycemia by suspending insulin delivery if glucose is predicted to drop below 70 mg/dl (8). Additionally, the device offers specific settings for circumstances such as sleep or exercise. When the exercise mode is activated, the system temporarily raises the minimum glucose target from 112.5 to 140 mg/dl to minimize the risk of hypoglycemia, a common effect of physical activity.
Sponsors
University of Messina
University of Verona, Italy
Bruno Bombaci
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
No minimum to 20 Years
Healthy volunteers
No
Inclusion criteria
* Diagnosis of type 1 diabetes according to International Society for Pediatric and Adolescent Diabetes (ISPAD) guidelines * Duration of diabetes \> 12 months * Age \< 20 years * Pubertal development completed according to the Tanner stage * Use of Control-IQ technology for at least 3 months * Automatic mode use for at least 70% of the time during the 2 weeks preceding enrollment * CGM use for at least 70% of the time during the 2 weeks preceding enrollment * Regular physical activity (at least 2 sessions per week, each lasting at least 45 minutes)
Exclusion criteria
* Uncontrolled celiac disease or thyroid disease * Presence of other chronic illnesses * Psychiatric or neurological conditions, including eating disorders, that may interfere with the study * Chronic use of medications (other than insulin) that may affect glucose control * Chronic use of substances or drugs that could impact CGM accuracy
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Mean sensor glucose (mg/dl or mmol/L) | 14 days | — |
| Time above range level 1 (%) | 14 days | Time spent with sensor glucose between 180 and 250 mg/dl (10.1 and 13.9 mmol/L) |
| Time above range level 2 (%) | 14 days | Time spent with sensor glucose \> 250 mg/dl (13.9 mmol/L) |
| Time below range level 1 (%) | 14 days | Time spent with sensor glucose between 54 and 70 mg/dl (3.0 and 3.8 mmol/L) |
| Time below range level 2 (%) | 14 days | Time spent with sensor glucose \< 54 mg/dl (3.0 mmol/L) |
| Coefficient of variation (%) | 14 days | — |
| Time in range (%) | 14 days | Time spent with sensor glucose between 70 and 180 mg/dl (3.9 and 10 mmol/L) |
| Time in tight range (%) | 14 days | Time spent with sensor glucose between 70 and 140 mg/dl (3.9 and 7.8 mmol/L) |
Secondary
| Measure | Time frame |
|---|---|
| Daytime (h 07.00-23.00) Time in Range (%) | 14 days |
| Nighttime (h 23.00 - 07.00) Time in Range (%) | 14 days |
Other
| Measure | Time frame | Description |
|---|---|---|
| Severe hypoglycemia episodes | 14 days | (safety) |
| Diabetic ketoacidosis episodes | 14 days | (safety) |
Countries
Italy
Contacts
Primary ContactBruno Bombaci, MD
Backup ContactGiuseppina Salzano, PhD MD
Outcome results
None listed