Prediction and Prevention of Nocturnal Hypoglycemia in Persons With Type 1 Diabetes Using Machine Learning Techniques

Hospital Clinic of Barcelona

Status: Completed

Conditions: Hypoglycemia; Type1diabetes

Treatments: Device: Physical exercise tracker; Device: isCGM (intermittently scanned Continuous Glucose Monitoring)

Study type: Interventional

Funder types: Other

Identifiers

NCT03711656

Nocturnal Hypoglycemia

Details and patient eligibility

About

The objective is to develop a novel system to predict and prevent nocturnal hypoglycemia in type 1 diabetic (T1D) patients, focused in patients with multiple daily injections (MDI) therapy. The general idea is to make use of previous-day information in the moment when patients go to sleep, and then predict if in the next following hours any hypoglycemic event will occur. If the system will have predicted any hypoglycemic event in that moment, it is expected that it will be able to warn the patient to take some action: such as reduce basal insulin dose or to consume a snack before sleep.

10 patients with T1D for more than five years will be included.

It is a longitudinal, prospective, interventional study in which every patient will use intermittently scanned Continuous Glucose Monitoring (isCGM) and a physical activity tracker during 12 weeks. Moreover, during this period, patients will store in a mobile application (Freestyle LibreLink) or in a reader information regarding their diabetes management activities, such as insulin delivery doses and meal consumption.

Enrollment: 10 patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Patients > 18 years with Type 1 Diabetes:

  • > 4 hypoglycemia / week (< 70 mg/dl, including day and night), last 2 weeks and / or
  • One severe hypoglycemia during the last year and / or
  • Hypoglycemia unawareness (Clarke Test >3)

• Disease duration > 5 years

• On multiple doses of insulin (MDI) therapy using a rapid acting insulin analogue as prandial insulin (lispro, aspart or glulisine) and any basal analogue as basal insulin.

• A1c 6.5 - 9.5 %

• Able to use an intermittently scanned continuous glucose monitoring (isCGM) system.

• Performing >4 self-monitoring blood glucose (SMBG) per day

• Using carb-counting

• Providing an informed consent

• No CGM user previously (during the last 3 months).

Exclusion criteria

• Patients with a previous Diabetic Ketoacidosis (DKA) episode in the previous 6 months.
• Patients with a severe hypoglycemia in the previous 6 months.
• Severe diabetic complications or comorbidities: eye, renal, cardiovascular...from the clinicians point of view.
• Pregnancy and breastfeeding.
• History of drug or alcohol abuse.
• Scheduled surgery during the study period.
• Mental conditions that prevent the subject to understand the nature, purpose and possible consequences of the study.
• Subjects those are unlikely to meet the clinical study protocol, eg uncooperative attitude, inability to return for follow-up visits, or poor probability of completing the study.
• Using an experimental drug or device during the past 30 days.

Trial design

Primary purpose: Other

Allocation: N/A

Interventional model: Single Group Assignment

Masking: None (Open label)

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10 participants in 1 patient group

isCGM and Physical exercise tracker

Experimental group

Description:

Participants will perform CGM during 12 weeks using an isCGM (intermittently scanned Continuous Glucose Monitoring), Freestyle Libre, (Abbott Diabetes Care, Witney, Oxon, UK). Insulin dose (rapid-acting and long acting), carbohydrates and Self-monitoring blood glucose (SMBG) per day will be recorded by the patient in the reader or in the App (LibreLink, Abbott Diabetes Care, Witney, Oxon, UK). Moreover, participants will be instructed to collect data about moderate or high intensity exercise, illness and other disturbances occurring during the study period at home. Patients will wear a physical exercise tracker (Fitbit Alta HR® wristband (Fitbit, Inc., San Francisco, California, USA)) to track physiological variables such as heart rate, steps, activity level and sleep quality.

Treatment:

Device: isCGM (intermittently scanned Continuous Glucose Monitoring)

Device: Physical exercise tracker