Type 1 Diabetes MellitusNCT00884611
Development of Algorithms for a Hypoglycemic Prevention Alarm: Closed Loop Study
A study testing Predictive Low Glucose Suspend Algorithm ON and Predictive Low Glucose Suspend Algorithm OFF in people with Type 1 Diabetes Mellitus, run by Stanford University at 2 sites in United States.
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. Read more about this study
- Who is it for?
- Ages 12 to 46 years
- Conditions the study is for
- Type 1 Diabetes Mellitus
- What is being tested?
- Predictive Low Glucose Suspend Algorithm ON and Predictive Low Glucose Suspend Algorithm OFF
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 20 participants
- Where
- 2 sitesUnited States
- Study dates
- May 2007to Aug 2011
- Phase
- Interventional
- Are there results?
- Yes, posted in the registrySummary in the doctors' view
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 12 to 46 years
- All sexes
- No healthy volunteers
- Child, Adult
Who may be able to join
- 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
Who cannot join
- 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)
Show all 12Show fewer
- 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.
Trial locations and contacts
2 sites in 1 country.
United States2 sites
Barbara Davis Center for Childhood Diabetes, University of Colorado
Aurora, Colorado, 80045
Stanford University School of Medicine
Stanford, California, 94305
About this study
Official title: Development of Algorithms for a Hypoglycemic Prevention Alarm
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.
Read the 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.
- Conditions
- Type 1 Diabetes Mellitus
- Being tested
- Predictive Low Glucose Suspend Algorithm ON, Predictive Low Glucose Suspend Algorithm OFF
- Medical subject headings
- Diabetes Mellitus, Type 1
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Predictive Low Glucose Suspend Algorithm ONDevice
Also called Intervention Night
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 OFFDevice
Also called Control Night
| Study group | Role | What they receive |
|---|---|---|
| Predictive Low Glucose Suspend | Experimental | 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. Receives: Device: Predictive Low Glucose Suspend Algorithm ON; Device: Predictive Low Glucose Suspend Algorithm OFF |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 21 days
Secondary outcomes (2)
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.
Measured: 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.
Measured: 21 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted21 Apr 2009 (estimated)
- Study startMay 2007
- Primary completionJul 2011
- Study completionAug 2011
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Posted resultsParticipant flow, outcome measures and adverse events reported by the sponsor.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Type 1 Diabetes MellitusStudies of the same condition, open and under way.
- More trials run by Stanford UniversityThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Treatment
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 20 participants (actual)
Sponsor and investigators
- Lead sponsor
- Stanford University
- Sponsor type
- University, hospital or other
- Collaborators
- University of Colorado, Denver
- Responsible party
- Principal investigator, Bruce A. Buckingham, Stanford University
- Investigators
- Bruce A. Buckingham, Principal investigator, Stanford University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT00884611
- Sponsor's protocol ID
- SU-10162008-1321
- Other IDs
- Stanford eprotocol # 6789
- Status last verified
- Jan 2018
- First submitted
- 17 Apr 2009
- Last updated
- 28 Feb 2018
- Results posted
- Yes, on ClinicalTrials.gov
- Data monitoring committee
- No
Publications
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.
PubMed 23883408
Study at a glance
From the registry record, last updated by the sponsor on 28 Feb 2018. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of Algorithms for a Hypoglycemic Prevention Alarm
- ClinicalTrials.gov ID
- NCT00884611
- Acronym / sponsor ID
- SU-10162008-1321
- Conditions
- Type 1 Diabetes Mellitus
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 20 participants (actual)
- Lead sponsor
- Stanford UniversityUniversity, hospital or other
- Collaborators
- University of Colorado, Denver
- Study start
- May 2007
- Primary completion
- Jul 2011 (actual)
- Study completion
- Aug 2011 (actual)
- First posted
- 21 Apr 2009 (estimated)
- Results
- Posted 28 Feb 2018
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Treatment
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Predictive Low Glucose Suspend | Experimental | Device: Predictive Low Glucose Suspend Algorithm ON, Device: Predictive Low Glucose Suspend Algorithm OFFThe 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. |
Who may qualify
- Ages
- 12 to 46 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult
Key inclusion criteria (7 listed)
- 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,
Key exclusion criteria (12 listed)
- 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:
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Predictive Low Glucose Suspend Algorithm ONAlso: Intervention NightThe 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. | Device | Predictive Low Glucose Suspend |
| Predictive Low Glucose Suspend Algorithm OFFAlso: Control Night | Device | Predictive Low Glucose Suspend |
Primary outcome
Percentage of Nights With CGM (Continuous Glucose Monitor) Sensor Values < 60 mg/dL
Time frame: 21 days
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.
2 secondary outcomes
Percentage of Nights With CGM Values >180 mg/dL
Time frame: 21 days
Mean Morning Blood Glucose (BG)
Time frame: 21 days
Results and safety
Loading the posted results from ClinicalTrials.gov…
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 28 Feb 2018.
- Posted resultsParticipant flow, baseline, all outcome measures and adverse events.
- Results publication: PubMed 23883408Buckingham 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Bruce A. Buckingham principal investigator
Stanford University
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Predictive Low Glucose Suspend Algorithm ON and Predictive Low Glucose Suspend Algorithm OFF in people with Type 1 Diabetes Mellitus, run by Stanford University at 2 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 12 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 28 Feb 2018. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Yes. Results are posted in the registry (first posted 28 Feb 2018). A summary is in the For doctors view, and the full results are on ClinicalTrials.gov.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Percentage of Nights With CGM (Continuous Glucose Monitor) Sensor Values < 60 mg/dL (time frame: 21 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT00884611, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 28 Feb 2018.