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This study will be conducted in a Clinical Research Center (CRC) setting and recruiting type 1 diabetes that are currently using an insulin pump.
This study is a non-randomized, uncontrolled feasibility study that looks to enroll people with type 1 diabetes who are currently using an insulin pump. During the subject's participation, the study staff will closely monitor the study subject in a clinical research center environment for approximately 30 hours, while controller algorithm determined insulin doses are delivered by an insulin pump, and utilizing continuous glucose monitoring results.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| type 1 diabetes | Experimental | Predictive Low Glucose Minimizer (PLGM) System |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Predictive Low Glucose Minimizer | Device | This study is a non-randomized feasibility study enrolling type 1 diabetics who are currently using an insulin pump. Participating Investigators will closely monitor the study subject in a clinical research center environment for approximately 30 hours, while controller algorithm determined insulin doses are delivered by an insulin pump, and utilizing continuous glucose monitoring results. |
| Measure | Description | Time Frame |
|---|---|---|
| Evaluate the performance of the System while the subject is under close medical supervision in the Clinical Research Center (CRC) setting | Evaluating the ability of the system to predict a fall or rise in glucose values below or above a low glucose threshold, and take the corresponding appropriate action of reducing or suspending insulin delivery in order to keep the subject's glucose above this threshold, or resuming insulin delivery at the current basal rate upon the increase of glucose above this threshold. Ability of the system to issue timely and accurate warnings. | 1 week after subject is enrolled in the study |
| Measure | Description | Time Frame |
|---|---|---|
| Capturing the number of Adverse Events as a measure of assessing subject safety | Understand the System's ability to safely keep the subject glucose levels within designated threshold. The subject and the device will be continuously monitored by the Principle Investigator and Algorithm Engineer to ensure proper function of the device and subject safety. All Adverse Events will be captured on the CRF. |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Howard Zisser, MD | Samsum Diabetes Reserach Inst. | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Samsum Diabetes Reserach Inst. | Santa Barbara | California | 93105 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 26134834 | Derived | Finan DA, Dassau E, Breton MD, Patek SD, McCann TW Jr, Kovatchev BP, Doyle FJ 3rd, Levy BL, Venugopalan R. Sensitivity of the Predictive Hypoglycemia Minimizer System to the Algorithm Aggressiveness Factor. J Diabetes Sci Technol. 2015 Jun 30;10(1):104-10. doi: 10.1177/1932296815593292. |
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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 |
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| 1 week after subject is enrolled in the study |
| D004700 | Endocrine System Diseases |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |