Please assess the completion status of the following clinical trial:

Trial Title: Outpatient Reduction of Nocturnal Hypoglycemia by Using Predictive Algorithms and Pump Suspension in Children

Study Design Characteristics:
- Allocation: RANDOMIZED
- Intervention Model: PARALLEL
- Observational Model: None
- Primary Purpose: PREVENTION
- Time Perspective: None
- Masking: NONE
- Phase: PHASE2
- Number of Arms: 2.0

Eligibility Criteria:
Inclusion Criteria:~* Clinical diagnosis of type 1 diabetes and using daily insulin therapy for at least one year and an insulin infusion pump for at least 6 months~* Age 3 to \<15 years~* HbA1c \<=8.5%~* Availability of internet access for periodic upload of study data~Exclusion Criteria:~* Diabetic ketoacidosis in the past 3 months~* Hypoglycemic seizure or loss of consciousness in past 6 months~* History of seizure disorder (except for hypoglycemic seizures)~* Cystic fibrosis~* Current use of oral/inhaled glucocorticoids, beta-blockers or other medications, which in the judgment of the investigator would be a contraindication to participation in the study~* History of ongoing renal disease (other than microalbuminuria), or liver disease (Creatinine is \> 1.5 mg/dL (132 µmol/L))~* Medical or psychiatric condition that in the judgment of the investigator might interfere with the completion of the protocol such as:~  * Inpatient psychiatric treatment in the past 6 months~ * Uncontrolled adrenal disorder~ * Abuse of alcohol~* Pregnancy~* Liver disease as defined by an Alanine Aminotransferase Test (ALT) greater than 3 times the upper limit of normal

- Gender: ALL
- Minimum Age: 3 Years
- Maximum Age: 14 Years
- Healthy Volunteers: f

Study Arms:
- Pump suspension algorithm (Type: ACTIVE_COMPARATOR): The pump suspension algorithm will be running actively on the study laptop during the night and suspend the pump if the algorithm predicts hypoglycemia.
- Standard of Care (Type: NO_INTERVENTION): The control algorithm will run passively and not suspend the patient's pump.

Based on this trial design, predict the completion outcome and termination type (if applicable).