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

Study Overview
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Brief Summary
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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
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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.

Official Title
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Development of Algorithms for a Hypoglycemic Prevention Alarm

Conditions
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Type 1 Diabetes Mellitus

Intervention / Treatment
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* Device: Predictive Low Glucose Suspend Algorithm ON
* Device: Predictive Low Glucose Suspend Algorithm OFF


Participation Criteria
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Eligibility Criteria
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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.

Ages Eligible for Study
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Minimum Age: 12 Years
Maximum Age: 46 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Treatment
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Predictive Low Glucose Suspend<br>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. | Device: Predictive Low Glucose Suspend Algorithm ON<br>* 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.<br>* Other names: Intervention Night;Device: Predictive Low Glucose Suspend Algorithm OFF<br> <br> * Other names: Control Night;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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 Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| 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 | 
| 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 |