Preventing Hypoglycemia Using Predictive Alarm Algorithms and Insulin Pump Suspension

Department of Pediatric Endocrinology, Stanford University, Stanford, California 94305-5208, USA.
Diabetes Technology &amp Therapeutics (Impact Factor: 2.11). 02/2009; 11(2):93-7. DOI: 10.1089/dia.2008.0032
Source: PubMed


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


Available from: Bruce Buckingham
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