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Diabetes Care. 2010 Jun;33(6):1249-54. doi: 10.2337/dc09-1487.

Real-Time hypoglycemia prediction suite using continuous glucose monitoring: a safety net for the artificial pancreas.

Author information

  • 1Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California, USA. dassau@engineering.ucsb.edu

Abstract

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.

PMID:
20508231
[PubMed - indexed for MEDLINE]
PMCID:
PMC2875433
Free PMC Article
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