Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
20 participants
INTERVENTIONAL
2016-05-31
2016-12-31
Brief Summary
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Detailed Description
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Artificial Pancreas System with Fault Detection Algorithms: Roche Accu-Check Spirit Combo Insulin Pump, Dexcom G4P System with Share, Diabetes Assistant (DiAs) on Android phone, DiAs Web Monitoring (DWM)
\- referred to as Remote Monitoring Server, MPC control algorithm, Health Monitoring System (HMS) algorithm. Sensor and infusion set fault detection algorithms will be applied offline with data obtained from server and notifications will be sent to the clinician.
Control Arm:
Sensor-augmented insulin pump therapy: Subject will use their personal insulin pump and Dexcom G4P System with Share.
Primary Objective:
To determine the efficacy of the fault detection algorithm. The primary outcome is based on the amount of time the sensor glucose is \>250 mg/dL in the 4 hours preceding detection of the infusion set failure during sensor augmented pump therapy vs. closed-loop control with fault detection alerts.
Secondary Objectives:
To determine the effectiveness of the sensor fault detection algorithm. To determine the efficacy of the Zone MPC controller by evaluating glycemic outcomes
Number of Subjects:
There will be 20 subjects recruited: 10 at Stanford and 10 at Denver (up to 36 subjects will be enrolled to reach 20 subjects completing the study)
Diagnosis and Main Inclusion Criteria:
Adult subjects between 18 and 55 years of age inclusive, diagnosed with type 1 diabetes.
Trial Design:
This outpatient study will be conducted over 6 weeks as shown in the figure below. The 6-week period will consist of two 2-week blocks of prolonged infusion set wear with a 1-week sensor run-in period preceding each block. In each block, subjects will wear an infusion set for up to 7 days. A new infusion set will be inserted at the start of each week in the block. Following enrollment procedures, subjects will be randomized at a ratio of 1:1 to either use the AP system with fault detection algorithms (intervention) or sensor-augmented pump therapy (control) in the first block.
Conditions
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Study Design
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RANDOMIZED
CROSSOVER
TREATMENT
NONE
Study Groups
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Sensor Augmented Pump (control)
Use sensor augmented pump (SAP) for 3 weeks.
No interventions assigned to this group
Artificial Pancreas (intervention)
Artificial pancreas system (Algorithm + CGM + pump)--use the AP system for 3 weeks which consists of: (1) Fault detection and Zone MPC algorithm housed on the DiAs platform + (2) Roche insulin pump + (3) Dexcom CGM
Artificial pancreas system (Algorithm + CGM + pump)
The AP system using fault detection algorithms will determine whether insulin infusion problems are occurring and may prevent severe hyperglycemia due to its predictive nature
Interventions
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Artificial pancreas system (Algorithm + CGM + pump)
The AP system using fault detection algorithms will determine whether insulin infusion problems are occurring and may prevent severe hyperglycemia due to its predictive nature
Eligibility Criteria
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Inclusion Criteria
2. Daily insulin therapy for at least 12 months
3. Age between 18.0 to 55.0 years of age
4. Use of an insulin pump for at least 3 months
5. Subject comprehends English
6. Females of childbearing potential must use an adequate method of contraception and have a negative pregnancy test
7. Total daily insulin requirement ≥ 0.3 units/kg/day
8. Subject has an adult companion, age \> 18 years, who lives with the subject, has access to where they sleep, is willing to be in the house when the subject is sleeping and willing to attend to the subject if there are safety concerns -
Exclusion Criteria
2. Hypoglycemic seizure or loss of consciousness in the past 6 months
3. Subjects requiring an intermediate or long-acting insulin (such as NPH, detemir or glargine)
4. Subjects using other anti-diabetic medications other than insulin (oral or injectable) at the time of enrollment. Any prior use of other anti-diabetic medications must be washed out for at least 8 weeks prior to enrollment.
5. Current use of other medications, which in the judgment of the investigator would be a contraindication to participation in the study
6. Subject has a medical disorder that in the judgment of the investigator will affect completion of any aspect of the protocol
7. Subject is currently participating in another investigational device or drug study within 30 days or 5-half-lives of the drug.
8. Subject has a history of any cardiac or vascular disorder including, but not limited to, myocardial infarction, unstable angina, coronary artery bypass surgery, coronary artery stenting, transient ischemic attack, cerebrovascular accident, angina, congestive heart failure, arrhythmia or thromboembolic disease
9. Subject has a history of hepatic disease
10. Subject has renal failure on dialysis
11. Systolic blood pressure \> 160 mmHg on screening visit
12. Diastolic blood pressure \> 90 mmHg on screening visit
13. Subjects with inadequately treated thyroid disease or celiac disease
14. Subject has a neurologic disorder that in the judgment of the investigator will affect completion of the protocol
15. Subject has received inpatient psychiatric treatment in the past 6 months
16. Subject consumes more than an average of 4 standard alcoholic drinks/day in the last 30 days
17. Subject has an active skin condition that would affect sensor placement
18. Subject is unable to avoid acetaminophen for the duration of the study
19. 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
20. Subject is currently on beta blocker medication -
18 Years
55 Years
ALL
No
Sponsors
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Stanford University
OTHER
University of Colorado, Denver
OTHER
Harvard University
OTHER
University of California, San Diego
OTHER
University of California, Santa Barbara
OTHER
Rensselaer Polytechnic Institute
OTHER
Responsible Party
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B. Wayne Bequette
Professor, Department of Chemical & Biological Engineering Associate Director of Process Technologies
Central Contacts
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References
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Howsmon DP, Baysal N, Buckingham BA, Forlenza GP, Ly TT, Maahs DM, Marcal T, Towers L, Mauritzen E, Deshpande S, Huyett LM, Pinsker JE, Gondhalekar R, Doyle FJ 3rd, Dassau E, Hahn J, Bequette BW. Real-Time Detection of Infusion Site Failures in a Closed-Loop Artificial Pancreas. J Diabetes Sci Technol. 2018 May;12(3):599-607. doi: 10.1177/1932296818755173. Epub 2018 Feb 1.
Forlenza GP, Deshpande S, Ly TT, Howsmon DP, Cameron F, Baysal N, Mauritzen E, Marcal T, Towers L, Bequette BW, Huyett LM, Pinsker JE, Gondhalekar R, Doyle FJ 3rd, Maahs DM, Buckingham BA, Dassau E. Application of Zone Model Predictive Control Artificial Pancreas During Extended Use of Infusion Set and Sensor: A Randomized Crossover-Controlled Home-Use Trial. Diabetes Care. 2017 Aug;40(8):1096-1102. doi: 10.2337/dc17-0500. Epub 2017 Jun 5.
Other Identifiers
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IDE G150122
Identifier Type: -
Identifier Source: org_study_id
NCT02506764
Identifier Type: -
Identifier Source: nct_alias
NCT02514785
Identifier Type: -
Identifier Source: nct_alias
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