search
Back to results

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

Primary Purpose

Type 1 Diabetes Mellitus

Status
Completed
Phase
Not Applicable
Locations
United States
Study Type
Interventional
Intervention
Predictive Low Glucose Suspend Algorithm ON
Predictive Low Glucose Suspend Algorithm OFF
Sponsored by
Stanford University
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional treatment trial for Type 1 Diabetes Mellitus

Eligibility Criteria

12 Years - 46 Years (Child, Adult)All SexesDoes not accept healthy volunteers

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.

Sites / Locations

  • Stanford University School of Medicine
  • Barbara Davis Center for Childhood Diabetes, University of Colorado

Arms of the Study

Arm 1

Arm Type

Experimental

Arm Label

Predictive Low Glucose Suspend

Arm Description

The pump suspension system consists of the Revel CGM device communicating with a laptop computer that contains the hypoglycemia prediction algorithm. During the 21 night study period, the laptop is placed at the bedside and turned on by the participant at bedtime and off on arising in the morning.The laptop contains a randomization schedule (2:1) that indicats whether the hypoglycemia prediction algorithm will be in operation that night (Predictive Low Glucose Suspend Algorithm ON) or will not be activated (Predictive Low Glucose Suspend Algorithm OFF), to which the participant is blinded.

Outcomes

Primary Outcome Measures

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.

Secondary Outcome Measures

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.
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.

Full Information

First Posted
April 17, 2009
Last Updated
January 29, 2018
Sponsor
Stanford University
Collaborators
University of Colorado, Denver
search

1. Study Identification

Unique Protocol Identification Number
NCT00884611
Brief Title
Development of Algorithms for a Hypoglycemic Prevention Alarm: Closed Loop Study
Official Title
Development of Algorithms for a Hypoglycemic Prevention Alarm
Study Type
Interventional

2. Study Status

Record Verification Date
January 2018
Overall Recruitment Status
Completed
Study Start Date
May 2007 (undefined)
Primary Completion Date
July 2011 (Actual)
Study Completion Date
August 2011 (Actual)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Principal Investigator
Name of the Sponsor
Stanford University
Collaborators
University of Colorado, Denver

4. Oversight

Data Monitoring Committee
No

5. Study Description

Brief 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.
Detailed 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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Type 1 Diabetes Mellitus

7. Study Design

Primary Purpose
Treatment
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
20 (Actual)

8. Arms, Groups, and Interventions

Arm Title
Predictive Low Glucose Suspend
Arm Type
Experimental
Arm Description
The pump suspension system consists of the Revel CGM device communicating with a laptop computer that contains the hypoglycemia prediction algorithm. During the 21 night study period, the laptop is placed at the bedside and turned on by the participant at bedtime and off on arising in the morning.The laptop contains a randomization schedule (2:1) that indicats whether the hypoglycemia prediction algorithm will be in operation that night (Predictive Low Glucose Suspend Algorithm ON) or will not be activated (Predictive Low Glucose Suspend Algorithm OFF), to which the participant is blinded.
Intervention Type
Device
Intervention Name(s)
Predictive Low Glucose Suspend Algorithm ON
Other Intervention Name(s)
Intervention Night
Intervention Description
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.
Intervention Type
Device
Intervention Name(s)
Predictive Low Glucose Suspend Algorithm OFF
Other Intervention Name(s)
Control Night
Primary Outcome Measure Information:
Title
Percentage of Nights With CGM (Continuous Glucose Monitor) Sensor Values < 60 mg/dL
Description
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.
Time Frame
21 days
Secondary Outcome Measure Information:
Title
Percentage of Nights With CGM Values >180 mg/dL
Description
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.
Time Frame
21 days
Title
Mean Morning Blood Glucose (BG)
Description
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.
Time Frame
21 days

10. Eligibility

Sex
All
Minimum Age & Unit of Time
12 Years
Maximum Age & Unit of Time
46 Years
Accepts Healthy Volunteers
No
Eligibility Criteria
Inclusion Criteria: Age 18 years or older, Type 1 diabetes for at least 1 year Current user of the MiniMed Paradigm Real-Time Revel system and Sof-sensor glucose sensor Hemoglobin A1c level of < 8.0%, Home computer with access to the Internet, At least one CGMglucose value < 70 mg/dL during the most recent 15 nights of CGM glucose data. Not pregnant or planning to become pregnant Exclusion Criteria: The exclusion criteria for this study is the following: 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 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 Inpatient psychiatric treatment in the past 6 months for either the subject or the subject's primary care giver (i.e., parent or guardian) 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 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.
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Bruce A. Buckingham
Organizational Affiliation
Stanford University
Official's Role
Principal Investigator
Facility Information:
Facility Name
Stanford University School of Medicine
City
Stanford
State/Province
California
ZIP/Postal Code
94305
Country
United States
Facility Name
Barbara Davis Center for Childhood Diabetes, University of Colorado
City
Aurora
State/Province
Colorado
ZIP/Postal Code
80045
Country
United States

12. IPD Sharing Statement

Citations:
PubMed Identifier
23883408
Citation
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 nocturnal hypoglycemia. Diabetes Technol Ther. 2013 Aug;15(8):622-7. doi: 10.1089/dia.2013.0040. Epub 2013 Jul 24.
Results Reference
result

Learn more about this trial

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

We'll reach out to this number within 24 hrs