Using Wearable Sensors To Understand Low Blood Sugar in Type 1 Diabetes

This is a single-site study using wearable sensor technology (CGM and smartwatch) to better explain low blood sugars in patients living with type 1 diabetes.

Up to 20 participants with T1D will wear a continuous glucose monitor (CGM) and a smartwatch to collect information about hypoglycemia (low blood sugar), heart rate variability (HRV), and sleep for 4 weeks. The main goal is to create a hypoglycemia risk score using wearable sensor metrics that can be easily applied to all patients with T1D to identify those at greater risk of hypoglycemia.

This is a single-site study using wearable sensor technology (continuous glucose monitor \[CGM\] and smartwatch actigraphy) to stratify hypoglycemia and cardiovascular risk in patients living with type 1 diabetes.

To carry out this research, 20 local participants with Type 1 Diabetes (T1D) will wear CGM and smartwatches to quantify hypoglycemia, heart rate variability (HRV), and sleep actigraphy for 4 weeks. These data will be correlated with counterregulatory hormone levels collected during hyperinsulinemic-hypoglycemic (HHC) clamp. The goal is to create a hypoglycemia risk score using wearable sensor metrics that can be easily applied to all patients with T1D to identify those with impaired counter-regulation in the clinical setting (Aim 1). How hypoglycemia exposure impacts cardiometabolic health in T1D will also be explored.

Participants will complete ambulatory blood pressure monitoring (ABPM), flow mediated dilation (FMD), reactive hyperemia-peripheral artery tonometry (RH-PAT), HRV assessment via wearable smartwatch, and serum inflammatory and coagulation evaluation before and after hyperinsulinemic-hypoglycemic clamp to investigate the effect of hypoglycemia on these cardiovascular (CV) risk factors (Aim 2,3). Subjects will be monitored for 4 weeks prior, and 1 week after hypoglycemic clamp.

Eligibility Criteria:
Inclusion Criteria:

1. Men and women between the ages of 18 and 75 years old, inclusive, at the time of screening;
2. Females of non-childbearing potential must be ≥ 1 year post-menopausal or documented as being surgically sterile. Females of childbearing potential must agree to use two methods of contraception during the entire study;
3. Diagnosed with Type 1 diabetes \>2-year duration based on clinical history or as defined by the current American Diabetes Association (ADA) criteria;
4. Using hybrid closed loop, standard pump, or multiple daily injections;
5. Able to use a Continuous Glucose Monitoring (CGM) device;
6. A1c \> 7% and ≤ 10%:
7. eGFR ≥ 60 mL/min/1.73m²;
8. BMI 18.5-35.0 kg/m2 ;
9. Able to provide written informed consent approved by an Institutional Review Board (IRB).

Exclusion Criteria:

1. History or evidence of clinically significant disorder or condition that, in the opinion of the Investigator, would pose a risk to subject safety or interfere with the study evaluation, procedures, or completion;
2. History of pancreatitis, medullary thyroid carcinoma or liver disease:
3. Clinically significant diagnosis of anemia (Hemoglobin \< 9 g/dl at screening);
4. Body Mass Index (BMI) \< 18.5 kg/m2 and/or weight \<50kg;
5. Body Mass Index (BMI) \> 35 kg/m2;
6. Whole blood donation of 1 pint (500 mL) within 8 weeks prior to Screening. Donations of plasma, packed RBCs, platelets or quantities less than 500 mL are allowed at investigator discretion;
7. Current or recent (within 1 month of screening) use of diabetes medications other than insulin; (examples include GLP-1, RA, SGLT-2i, Pramlintide, Metformin);
8. Women who are pregnant or lactating/breastfeeding;
9. Unable or unwilling to follow the study protocol or who are non-compliant with screening appointments or study visits;
10. Any other condition(s) that might reduce the chance of obtaining study data, or that might cause safety concerns, or that might compromise the ability to give truly informed consent;
11. Severe hypoglycemic events or DKA within 3 months;
12. Currently using beta-blockers;
13. Adrenal insufficiency diagnosis.