Trials / Completed
CompletedNCT05096325
YpsoPump Occlusion Detection Algorithm: Collection of Real-world Data for In-silico Evaluation of a New Software Algorithm to Refine Occlusion Detection in Subjects With Type 1 Diabetes Using Continuous Subcutaneous Insulin Infusion
- Status
- Completed
- Phase
- —
- Study type
- Observational
- Enrollment
- 40 (actual)
- Sponsor
- mylife Diabetes Care AG · Industry
- Sex
- All
- Age
- 18 Years
- Healthy volunteers
- Not accepted
Summary
A common difficulty related to the insulin pumps are occlusions of the insulin infusion set (IIS). This study aims to evaluate the performance of a new software algorithm to detect catheter-occlusion in silico in order to refine the current automated occlusion detection algorithm of the mylife™ YpsoPump®.
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| DEVICE | YpsoPump® insulin pump system | The subjects will receive a CE-certified mylife™ YpsoPump® insulin pump system that allows detailed logging of pressure data. Data will then be analysed in silico comparing the new occlusion detection algorithm with the common occlusion detection algorithm. |
Timeline
- Start date
- 2022-01-03
- Primary completion
- 2022-03-01
- Completion
- 2022-03-01
- First posted
- 2021-10-27
- Last updated
- 2022-03-22
Locations
2 sites across 2 countries: Germany, Switzerland
Source: ClinicalTrials.gov record NCT05096325. Inclusion in this directory is not an endorsement.