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. 2009 Feb;11(2):93-7.
doi: 10.1089/dia.2008.0032.

Preventing hypoglycemia using predictive alarm algorithms and insulin pump suspension

Bruce Buckingham  1 , Erin Cobry, Paula Clinton, Victoria Gage, Kimberly Caswell, Elizabeth Kunselman, Fraser Cameron, H Peter Chase
Affiliations

Preventing hypoglycemia using predictive alarm algorithms and insulin pump suspension

Bruce Buckingham et al. Diabetes Technol Ther. 2009 Feb.

Abstract

Background: Nocturnal hypoglycemia is a significant problem. From 50% to 75% of hypoglycemia seizures occur at night. Despite the development of real-time glucose sensors (real-time continuous glucose monitor [CGM]) with hypoglycemic alarms, many patients sleep through these alarms. The goal of this pilot study was to assess the feasibility using a real-time CGM to discontinue insulin pump therapy when hypoglycemia was predicted.

Methods: Twenty-two subjects with type 1 diabetes had two daytime admissions to a clinical research center. On the first admission their basal insulin was increased until their blood glucose level was <60 mg/dL. On the second admission hypoglycemic prediction algorithms were tested to determine if hypoglycemia was prevented by a 90-min pump shutoff and to determine if the pump shutoff resulted in rebound hyperglycemia.

Results: Using a statistical prediction algorithm with an 80 mg/dL threshold and a 30-min projection horizon, hypoglycemia was prevented 60% of the time. Using a linear prediction algorithm with an 80 mg/dL threshold and a 45-min prediction horizon, hypoglycemia was prevented 80% of the time. There was no rebound hyperglycemia following pump suspension.

Conclusions: Further development of algorithms is needed to prevent all episodes of hypoglycemia from occurring.

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Figures

FIG. 1.
FIG. 1.
Graph of results from a first admission.
FIG. 2.
FIG. 2.
Second admission with pump shutoff on projected alarm.
FIG. 3.
FIG. 3.
Rate of change of glucose levels following pump shutoff.
See this image and copyright information in PMC

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