Early Detection of Infusion Set Failure During Insulin Pump Therapy in Type 1 Diabetes.

Background: Insulin infusion set failure resulting in prolonged hyperglycemia or diabetic ketoacidosis can occur with pump therapy in type 1 diabetes. Set failures are frequently characterized by variable and unpredictable patterns of increasing glucose values despite increased insulin infusion. Early detection may minimize the risk of prolonged hyperglycemia, an important consideration for automated insulin delivery and closed-loop applications.
Methods: A novel algorithm designed to alert the patient to the onset of infusion set failure was developed based upon continuous glucose sensor values and insulin delivered from an insulin pump. The method was calibrated on 12 weeks of infusion set wear without failures recorded by 4 patients in ambulatory conditions and prospectively validated on 18 weeks of infusion set wear with and without failures belonging to 9 other subjects in ambulatory conditions.
Results: The algorithm, evaluated retrospectively, identified a failure 2.52 ± 1.91 days ahead of the actual event as recorded by the clinical team, corresponding to 50% sensitivity, 66% specificity and 55% accuracy. If set failure alarms had been activated in real time, the average time >180 mg/dl would be reduced from 82.7 ± 40.9 hours/week/subject (without alarm) to 58.8 ± 31.1 hours/week/subject (with alarm), corresponding to a potential 29% reduction in time spent >180mg/dl.
Conclusion: The proposed method for early detection of infusion set failure based on glucose sensor and insulin data demonstrated favorable results on retrospective data and may be implemented as an additional safeguard in a future fully automated closed-loop system.
Competing Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: MC: None. DJD: None. TTL: None. DMM: Insulet Corporation, Dexcom, Inc, Medtronic, Inc. LHM: Medtronic, Inc. BAB: Medtronic, Inc, Animas Corporation, BD Medical Diabetes Care, Tandem Diabetes Care, Inc, Sanofi US, Novo Nordisk Inc, Hylenex, Dexcom, Inc. FJD: Insulet Corporation. ED: Animas Corporation, Insulet Corporation.
(© 2016 Diabetes Technology Society.)