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.
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.
Authors: Bruce Buckingham; Jen Block; Jonathan Burdick; Andrea Kalajian; Craig Kollman; Michael Choy; Darrell M Wilson; Peter Chase Journal: Diabetes Technol Ther Date: 2005-06 Impact factor: 6.118
Authors: Darrell M Wilson; Roy W Beck; William V Tamborlane; Mariya J Dontchev; Craig Kollman; Peter Chase; Larry A Fox; Katrina J Ruedy; Eva Tsalikian; Stuart A Weinzimer Journal: Diabetes Care Date: 2007-01 Impact factor: 19.112
Authors: Stuart A Weinzimer; Garry M Steil; Karena L Swan; Jim Dziura; Natalie Kurtz; William V Tamborlane Journal: Diabetes Care Date: 2008-02-05 Impact factor: 19.112
Authors: Fraser Cameron; Darrell M Wilson; Bruce A Buckingham; Hasmik Arzumanyan; Paula Clinton; H Peter Chase; John Lum; David M Maahs; Peter M Calhoun; B Wayne Bequette Journal: J Diabetes Sci Technol Date: 2012-09-01