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



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.



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.



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.
Department Chemical Engineering & Institute for Collaborative Biotechnologies, University of California, Santa Barbara, Santa Barbara, CA, USA.
Marzia
M
Cescon
Pediatric Diabetes and Endocrinology, Baylor College of Medicine, Texas Children's Hospital, Houston, TX, USA.
Daniel J
DJ
DeSalvo
Division of Pediatric Endocrinology, Stanford School of Medicine, Stanford, CA, USA.
Trang T
TT
Ly
Barbara Davis Center for Diabetes, University of Colorado Denver, Aurora, CO, USA.
David M
DM
Maahs
Barbara Davis Center for Diabetes, University of Colorado Denver, Aurora, CO, USA.
Laurel H
LH
Messer
Division of Pediatric Endocrinology, Stanford School of Medicine, Stanford, CA, USA.
Bruce A
BA
Buckingham
Department Chemical Engineering & Institute for Collaborative Biotechnologies, University of California, Santa Barbara, Santa Barbara, CA, USA.|Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
Francis J
FJ
Doyle
Department Chemical Engineering & Institute for Collaborative Biotechnologies, University of California, Santa Barbara, Santa Barbara, CA, USA dassau@seas.harvard.edu.|Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
Eyal
E
Dassau
D000465:Algorithms; D001786:Blood Glucose / Q000032:analysis; D015190:Blood Glucose Self-Monitoring / Q000295:instrumentation; D056902:Clinical Alarms; D003922:Diabetes Mellitus, Type 1 / Q000188:drug therapy*; D004868:Equipment Failure; D005260:Female; D006801:Humans; D006943:Hyperglycemia / Q000139:chemically induced / Q000517:prevention & control*; D007004:Hypoglycemic Agents / Q000008:administration & dosage / Q000009:adverse effects; D007328:Insulin / Q000008:administration & dosage / Q000009:adverse effects; D007332:Insulin Infusion Systems / Q000009:adverse effects*; D008297:Male; D012680:Sensitivity and Specificity
D001786:Blood Glucose; D007004:Hypoglycemic Agents; D007328:Insulin
artificial pancreas; infusion set failures