Real-Time Hypoglycemia Prediction Suite Using Continuous Glucose Monitoring: A safety net for the artificial pancreas

• Published in: Diabetes care Vol. 33; no. 6; pp. 1249 - 1254
• Main Authors: Dassau, Eyal, Cameron, Fraser, Lee, Hyunjin, Bequette, B. Wayne, Zisser, Howard, Jovanovič, Lois, Chase, H. Peter, Wilson, Darrell M, Buckingham, Bruce A, Doyle, Francis J. III
• Format: Journal Article
• Language: English
• Published: United States American Diabetes Association 01.06.2010
• Subjects: Adolescent; Algorithms; analysis; blood; blood glucose; Blood Glucose - analysis; Blood sugar monitoring; Child; Child, Preschool; children; data collection; Dextrose; Diabetes; Diabetes Mellitus, Type 1; Diabetes Mellitus, Type 1 - blood; Diabetes Mellitus, Type 1 - drug therapy; Diabetes therapy; drug therapy; Female; Glucose; Human powered aircraft; Humans; hypoglycemia; Hypoglycemia - blood; Hypoglycemia - drug therapy; insulin; Insulin Infusion Systems; insulin-dependent diabetes mellitus; Male; Medical research; Medicine, Experimental; monitoring; Navigation; Original Research; pancreas; Pancreas, Artificial; patients; prediction; Predictive Value of Tests
• ISSN: 0149-5992; 1935-5548; 1935-5548
• DOI: 10.2337/dc09-1487

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.