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| ID | Type | Description | Link |
|---|---|---|---|
| R01DK133148 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) | NIH |
| Tandem Diabetes Care, Inc. | INDUSTRY |
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Bolus Priming (BP) based on Artificial Intelligence (AI) learning of meal patterns, added to our established Automated insulin delivery as Adaptive Network (AIDANET) algorithm and running on iPhone Diabetes Assistant (iDiAs) phone wirelessly connected to Tandem Mobi insulin pump and Dexcom Continuous Glucose Monitor (CGM).
A randomized cross-over trial assessing glycemic control on AIDANET equipped with its standard bolus vs AIDANET AI. A secondary comparison of AIDANET AI vs a current commercial Hybrid Closed Loop (HCL) system is planned as well.
Following enrollment and screening, participants will be randomized 1:1 to two 8-week sequences: Group A participants will continue to use their home Hybrid closed loop (HCL) system for 2 weeks, then switch to AIDANET for two weeks, and the switch to AIDANET AI for another 4 weeks. Group B participants will begin with 4 weeks of AIDANET AI, then switch to AIDANET for 2 weeks and then revert to their home HCL systems for the last 2 weeks of the study (Figure 1). The last two weeks of the 4-week AIDANET AI session will be used for analysis, comparing standard Ambulatory Glucose Profile (AGP) metrics across AIDANET vs AIDANET AI, with primary outcome Time in Range (TIR) (70-180 mg/dL) during the day. Secondary analyses will compare AIDANET AI 2-week AGP to HCL AGP metrics. Both analyses use randomized crossover design.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| GROUP A: 2 weeks HCL, 2 weeks AIDANET, and 4 weeks AIDANET AI | Experimental | Group A participants will continue to use their home HCL system for 2 weeks, then switch to AIDANET for two weeks, and the switch to AIDANET AI for another 4 weeks. |
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| GROUP B: 4 weeks AIDANET AI, 2 weeks AIDANET, and 2 weeks HCL | Experimental | Group B participants will begin with 4 weeks of AIDANET AI, then switch to AIDANET for 2 weeks and then revert to their home HCL systems for the last 2 weeks of the study |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Hybrid Closed Loop (HCL) x 2 weeks | Device | During the HCL session, participants will be using their own HCL systems for 2-weeks. |
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| Measure | Description | Time Frame |
|---|---|---|
| Time in Range (TIR) 70-180 mg/dL for 2-week free-living at home periods on AIDANET vs AIDANET AI. | The last two weeks of the 4-week AIDANET AI session will be used for analysis, comparing standard Ambulatory Glucose Profile metrics across AIDANET vs AIDANET AI, with primary outcome TIR (70-180 mg/dL) during the day. | two weeks |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Carlene Alix | Contact | 434-249-8961 | UAX8YX@uvahealth.org | |
| Laura Kollar, RN | Contact | 434-982-6479 | LLK7M@uvahealth.org |
| Name | Affiliation | Role |
|---|---|---|
| Sue Brown, MD | University of Virginia Center for Diabetes Technology | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Virginia Center for Diabetes Technology | Charlottesville | Virginia | 22903 | United States |
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| AIDANET x 2 weeks | Device | Participant will use the AIDANET algorithm on the Mobi system with the standard Bolus Priming System (BPS) automated bolus that does not require announcement of meals. |
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| AIDANET AI x 4 weeks | Device | Participant will use the AIDANET algorithm with the addition of the Bolus Priming (BP) based on AI learning of meal patterns. |
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| ID | Term |
|---|---|
| D003922 | Diabetes Mellitus, Type 1 |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
| D004700 | Endocrine System Diseases |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |
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