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

Exclusion Criteria

• •1. Known allergy/hypersensitivity to medical grade adhesives and/or to physical activity tracker material
• •2. Known severe nickel allergies
• •3. History of frequent catheter abscesses associated with pump therapy
• •4. Treatment with \> 1000 mg of acetaminophen every 6 hours
• •5. Treatment with hydroxyurea
• •6. Serious acute or chronic disease besides diabetes mellitus or an anamnesis which might, in the opinion of the investigator, pose a risk to the subject, e.g. seizure disorder, adrenal disorder, dialysis for renal failure, cystic fibrosis, active infection
• •7. Severe late complications of diabetes mellitus, e.g. severe macro- and/or micro-angiopathy (as determined by the investigator)
• •8. Known hypoglycaemia unawareness
• •9. Occurrence of self-reported severe hypoglycaemia event requiring third-party assistance within the last 6 months prior to study start
• •10. Occurrence of self-reported diabetic ketoacidosis requiring healthcare assistance within the last 6 months prior to study start
• •11. Participation in another investigation with an investigational drug or a pre-market medical device within the 30 days preceding and during the present investigation
• •12. Female subjects: pregnancy, lactation period, lack of a negative urine pregnancy test (except in case of menopause, sterilization or hysterectomy), or unwilling to use a contraception during the study (for sexually active subjects of childbearing potential)
• •13. Dependency from the sponsor or the clinical investigator
• •14. Inability to follow the procedures of the investigation, e.g. due to language problems, psychological disorders, dementia, etc. of the subject