Development of Algorithms for a Hypoglycemic Prevention Alarm: Closed Loop Study

Type 1 Diabetes Mellitus Clinical Trial

Official title:

Development of Algorithms for a Hypoglycemic Prevention Alarm

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT00884611
• Other study ID #: SU-10162008-1321
• Secondary ID: Stanford eprotoc
• Status: Completed
• Phase: N/A
• First received: April 17, 2009
• Last updated: January 29, 2018
• Start date: May 2007
• Est. completion date: August 2011

Study information

• Verified date: January 2018
• Source: Stanford University
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

This research study, Development of Algorithms for a Hypoglycemic Prevention Alarm, is being conducted at Stanford University Medical Center and the University of Colorado Barbara Davis Center. It is paid for by the Juvenile Diabetes Research Foundation.

The purpose of doing this research study is to understand the best way to stop an insulin infusion pump from delivering insulin to prevent a subject from having hypoglycemia. Nocturnal hypoglycemia is a common problem with type 1 diabetes. This is a pilot study to evaluate the safety of a system consisting of an insulin pump and continuous glucose monitor communicating wirelessly with a bedside computer running an algorithm that temporarily suspends insulin delivery when hypoglycemia is predicted in a home setting.

Description:

After the run-in phase, there is a 21-night trial in which each night is randomly assigned 2:1 to have either the predictive low-glucose suspend (PLGS) system active (intervention night) or inactive (control night).

Three predictive algorithm versions were studied sequentially during the study.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 20
• Est. completion date: August 2011
• Est. primary completion date: July 2011
• Accepts healthy volunteers: No
• Gender: All
• Age group: 12 Years to 46 Years

Eligibility

Inclusion Criteria:

1. Age 18 years or older,

2. Type 1 diabetes for at least 1 year

3. Current user of the MiniMed Paradigm Real-Time Revel system and Sof-sensor glucose sensor

4. Hemoglobin A1c level of < 8.0%,

5. Home computer with access to the Internet,

6. At least one CGMglucose value < 70 mg/dL during the most recent 15 nights of CGM glucose data.

7. Not pregnant or planning to become pregnant

Exclusion Criteria:

The exclusion criteria for this study is the following:

1. The presence of a significant medical disorder that in the judgment of the investigator will affect the wearing of the sensors or the completion of any aspect of the protocol

2. The presence of any of the following diseases:

• Asthma if treated with systemic or inhaled corticosteroids in the last 6 months

• Cystic fibrosis

• Angina (recurrent heart pain)

• Past heart attack or coronary artery (heart vessel) disease

• Past stroke or impairment of blood flow to the brain

• Other major illness that in the judgment of the investigator might interfere with the completion of the protocol Adequately treated thyroid disease and celiac disease do not exclude subjects from enrollment

3. Inpatient psychiatric treatment in the past 6 months for either the subject or the subject's primary care giver (i.e., parent or guardian)

4. Current use of oral/inhaled glucocorticoids or other medications, which in the judgment of the investigator would be a contraindication to participation in the study

5. Severe hypoglycemic event, as described as a seizure, loss of consciousness, severe neurological impairment, or neurological impairment suggestive of hypoglycemia and requiring an emergency department visit or hospitalization within 18 months of enrollment.

Related Conditions & MeSH terms

• Diabetes Mellitus
• Diabetes Mellitus, Type 1
• Type 1 Diabetes Mellitus

Intervention

Device:
• Predictive Low Glucose Suspend Algorithm ON
The algorithm uses a Kalman filter-based model to predict whether the sensor glucose level will fall below 80 mg/dL within a given time period and suspends the insulin pump if this event is predicted.
• Predictive Low Glucose Suspend Algorithm OFF

Locations

Country	Name	City	State
United States	Barbara Davis Center for Childhood Diabetes, University of Colorado	Aurora	Colorado
United States	Stanford University School of Medicine	Stanford	California

Sponsors (2)

Lead Sponsor	Collaborator
Stanford University	University of Colorado, Denver

Country where clinical trial is conducted

United States, 

References & Publications (1)

Buckingham BA, Cameron F, Calhoun P, Maahs DM, Wilson DM, Chase HP, Bequette BW, Lum J, Sibayan J, Beck RW, Kollman C. Outpatient safety assessment of an in-home predictive low-glucose suspend system with type 1 diabetes subjects at elevated risk of noctu — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Percentage of Nights With CGM (Continuous Glucose Monitor) Sensor Values < 60 mg/dL	Nights with CGM sensor values < 60 mg/dL were considered to be undesirable. A Kalman filter-based model algorithm predicted whether the sensor glucose level would fall below 80 mg/dL and would suspend insulin delivery as needed. Participants may have received treatment using one or more of the following algorithms: Algorithm 1 had a hypoglycaemic prediction horizon of 70 minutes; algorithm 2: 50 minutes; algorithm 3: 30 minutes.	21 days
Secondary	Percentage of Nights With CGM Values >180 mg/dL	Nights with CGM sensor values >180 mg/dL were considered to be undesirable. Participants may have received treatment using one or more of the following algorithms: Algorithm 1 had a hypoglycaemic prediction horizon of 70 minutes; algorithm 2: 50 minutes; algorithm 3: 30 minutes.	21 days
Secondary	Mean Morning Blood Glucose (BG)	Desirable glucose level was 70-180 mg/mL. Average of all morning BG data is presented. Participants may have received treatment using one or more of the following algorithms: Algorithm 1 had a hypoglycaemic prediction horizon of 70 minutes; algorithm 2: 50 minutes; algorithm 3: 30 minutes.	21 days