Real-Time Hypoglycemia Prediction Suite Using Continuous Glucose Monitoring
A safety net for the artificial pancreas
- Eyal Dassau, PHD1,2⇓,
- Fraser Cameron, MS3,
- Hyunjin Lee, PHD4,
- B. Wayne Bequette, PHD4,
- Howard Zisser, MD1,2,
- Lois Jovanovič, MD1,2,
- H. Peter Chase, MD5,
- Darrell M. Wilson, MD6,
- Bruce A. Buckingham, MD6 and
- Francis J. Doyle III, PHD1,2
- 1Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California;
- 2Sansum Diabetes Research Institute, Santa Barbara, California;
- 3Department of Aeronautics and Astronautics, Stanford University, Palo Alto, California;
- 4Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, New York;
- 5Barbara Davis Center for Childhood Diabetes, University of Colorado Health Sciences Center, Aurora, Colorado;
- 6Department of Pediatrics, Division of Pediatric Endocrinology, Stanford Medical Center, Palo Alto, California.
- Corresponding author: Eyal Dassau, .
OBJECTIVE The purpose of this study was to develop an advanced algorithm that detects pending hypoglycemia and then suspends basal insulin delivery. This approach can provide a solution to the problem of nocturnal hypoglycemia, a major concern of patients with diabetes.
RESEARCH DESIGN AND METHODS This real-time hypoglycemia prediction algorithm (HPA) combines five individual algorithms, all based on continuous glucose monitoring 1-min data. A predictive alarm is issued by a voting algorithm when a hypoglycemic event is predicted to occur in the next 35 min. The HPA system was developed using data derived from 21 Navigator studies that assessed Navigator function over 24 h in children with type 1 diabetes. We confirmed the function of the HPA using a separate dataset from 22 admissions of type 1 diabetic subjects. During these admissions, hypoglycemia was induced by gradual increases in the basal insulin infusion rate up to 180% from the subject's own baseline infusion rate.
RESULTS Using a prediction horizon of 35 min, a glucose threshold of 80 mg/dl, and a voting threshold of three of five algorithms to predict hypoglycemia (defined as a FreeStyle plasma glucose readings <60 mg/dl), the HPA predicted 91% of the hypoglycemic events. When four of five algorithms were required to be positive, then 82% of the events were predicted.
CONCLUSIONS The HPA will enable automated insulin-pump suspension in response to a pending event that has been detected prior to severe immediate complications.
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- Received August 10, 2009.
- Accepted January 18, 2010.
- © 2010 by the American Diabetes Association.
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