The Effect and Safety of a Novel CGM-Based Titration Algorithm for Basal Insulin in T2DM Participants.
NCT ID: NCT06111508
Last Updated: 2024-10-08
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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COMPLETED
NA
30 participants
INTERVENTIONAL
2023-11-29
2024-09-16
Brief Summary
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
TREATMENT
NONE
Study Groups
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Continuous Glucose Monitoring (CGM) based Titration
The CGM-based titration algorithm will run on the Diabetes Assistant and Amazon Web Services (AWS) platform (DiAs-Cloud). DiAs-Cloud enables the seamless integration of a smart phone application and AWS server architecture to enable data capture, dose computation, review by the clinical team, and communication to study participants. For dose computation the algorithm is comprised of three components; titration glucose level, personalized target, and safety hypoglycemia feature.
Continuous Glucose Monitoring (CGM)-based titration algorithm implemented in DiAs
A Continuous Glucose Monitoring (CGM)-based once weekly titration algorithm of basal insulin as implemented in DiAs Cloud platform
Standard Self-Monitoring Blood Glucose (SMBG) Titration
The SMBG-based titration algorithm will run on the Diabetes Assistant and Amazon Web Services (AWS) platform (DiAs-Cloud). DiAs-Cloud enables the seamless integration of a smart phone application and AWS server architecture to enable data capture, dose computation, review by the clinical team, and communication to study participants. Participants in the standard SMBG based titration group will wear a blinded CGM during the whole study. The total daily basal insulin dose will be converted 1:1 to Degludec. Algorithm informed dose changes will be made once weekly and checked by study physician.
No interventions assigned to this group
Interventions
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Continuous Glucose Monitoring (CGM)-based titration algorithm implemented in DiAs
A Continuous Glucose Monitoring (CGM)-based once weekly titration algorithm of basal insulin as implemented in DiAs Cloud platform
Other Intervention Names
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Eligibility Criteria
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Inclusion Criteria
2. Diagnosis of Type 2 Diabetes minimum 180 days before the day of screening
3. Hemoglobin A1c between 7-9% and measured by local lab at screening
4. On daily basal insulin for at least 90 days before inclusion into the study
5. Stable dose of oral and injectable (other than insulin) antidiabetic medications for 90 days prior inclusion. Acceptable medications include:
1. Metformin
2. Sulfonylureas
3. Meglitinides (glinides)
4. Dipeptidyl peptidase 4 (DPP-4) inhibitors
5. Sodium glucose co-transporter 2 (SGLT2) inhibitors
6. Thiazolidinediones
7. Alpha-glucosidase inhibitors
8. Oral combination products (for the allowed individual oral anti-diabetic drugs)
9. Oral or injectable Glucagon-like peptide-1 (GLP-1) Receptor Agonists (RAs)
10. If on sulfonylureas or glinides, willingness to reduce dose by 50%
8. Known skin reactions to CGM adhesives
9. Current/prior use of CGM within 30 days of the screening visit
10. Any planned surgery or procedures where basal insulin would be decreased or held in anticipation
Exclusion Criteria
2. Use of an insulin pump
3. Use of a short-acting insulin
4. Participation or has participated in another trial within 90 days of the screening visit
5. Female who is pregnant or intends to become pregnant or is of child-bearing potential and not using an adequate contraceptive method
6. Any disorder, except for conditions associated with T2D, which in the investigator's opinion might jeopardize participant's safety or compliance with the protocol.
18 Years
ALL
No
Sponsors
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Novo Nordisk A/S
INDUSTRY
University of Virginia
OTHER
Responsible Party
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Marc Breton
Principal Investigator
Principal Investigators
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Ralf M Nass, MD
Role: STUDY_CHAIR
University of Virginia
Locations
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Icahn School of Medicine at Mount Sinai
New York, New York, United States
University of Virginia
Charlottesville, Virginia, United States
Countries
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Provided Documents
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Document Type: Informed Consent Form
Other Identifiers
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230357
Identifier Type: -
Identifier Source: org_study_id
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