Literature DB >> 21827318

Prevention of hypoglycemia by using low glucose suspend function in sensor-augmented pump therapy.

Thomas Danne1, Olga Kordonouri, Martin Holder, Holger Haberland, Sven Golembowski, Kerstin Remus, Sara Bläsig, Tanja Wadien, Susanne Zierow, Reinhard Hartmann, Andreas Thomas.   

Abstract

BACKGROUND: Severe hypoglycemic episodes are a barrier for achieving optimal glycemic control. Sensor-augmented pump (SAP) therapy with insulin in combination with a novel mechanism of automatic insulin shutoff (low glucose suspend [LGS]) can be used to prevent and reduce hypoglycemia. In a prospective study, we investigated the effect of the LGS algorithm on the frequency of hypoglycemia in children and adolescents with type 1 diabetes under real-life conditions.
METHODS: Twenty-one patients with type 1 diabetes (10.8±3.8 years old, duration of diabetes 5.9±3.0 years, pump therapy for 3.7±1.7 years, glycated hemoglobin level 7.8±1.1%) from three pediatric centers used the Paradigm(®) Veo(™) system (Medtronic Minimed, Northridge, CA) during two subseqent time periods: SAP without LGS for 2 weeks and then SAP with LGS enabled for 6 weeks. The primary objective was to assess the frequency of hypoglycemic episodes when using the LGS feature with an insulin delivery shutoff of a maximum of 2 h at a sensor glucose level below 70 mg/dL (3.9 mmol/L).
RESULTS: In total, 1,298 LGS alerts occurred (853 shorter than 5 min). Forty-two percent of LGS activations (>5 min) lasted less than 30 min, whereas 24% had a duration of 2 h. The number of hypoglycemic excursions (average/day) was reduced during SAP+LGS (<70 mg/L, 1.27±0.75 vs. 0.95±0.49, P=0.010; ≤40 mg/dL, 0.28±0.18 vs. 0.13±0.14, P=0.005) as was the time spent in hypoglycemia (average minutes/day, 101±68 vs. 58±33, P=0.002) without significant difference in the mean glucose level (145±23 vs. 148±19 mg/dL). No episodes of severe hyperglycemia or diabetic ketoacidosis were observed following LGS activation.
CONCLUSIONS: The present investigation provides evidence that SAP with LGS reduces the frequency of hypoglycemia without compromising safety.

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Year:  2011        PMID: 21827318     DOI: 10.1089/dia.2011.0084

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  34 in total

Review 1.  Sensor-Augmented Insulin Pumps and Hypoglycemia Prevention in Type 1 Diabetes.

Authors:  Isabelle Steineck; Ajenthen Ranjan; Kirsten Nørgaard; Signe Schmidt
Journal:  J Diabetes Sci Technol       Date:  2016-10-06

2.  Putting brakes on insulin pump infusion to prevent hypoglycemia.

Authors:  Eda Cengiz
Journal:  J Diabetes Sci Technol       Date:  2011-09-01

Review 3.  Hypo- and Hyperglycemic Alarms: Devices and Algorithms.

Authors:  Daniel Howsmon; B Wayne Bequette
Journal:  J Diabetes Sci Technol       Date:  2015-04-30

4.  A Clinical Overview of Insulin Pump Therapy for the Management of Diabetes: Past, Present, and Future of Intensive Therapy.

Authors:  Cari Berget; Laurel H Messer; Gregory P Forlenza
Journal:  Diabetes Spectr       Date:  2019-08

5.  Routine sensor-augmented pump therapy in type 1 diabetes: the INTERPRET study.

Authors:  Kirsten Nørgaard; Andrea Scaramuzza; Natasa Bratina; Nebojsa M Lalić; Przemyslaw Jarosz-Chobot; Győző Kocsis; Edita Jasinskiene; Christophe De Block; Odile Carrette; Javier Castañeda; Ohad Cohen
Journal:  Diabetes Technol Ther       Date:  2013-02-25       Impact factor: 6.118

6.  Reimbursement for Continuous Glucose Monitoring.

Authors:  Lutz Heinemann; J Hans DeVries
Journal:  Diabetes Technol Ther       Date:  2016-02       Impact factor: 6.118

7.  Outpatient safety assessment of an in-home predictive low-glucose suspend system with type 1 diabetes subjects at elevated risk of nocturnal hypoglycemia.

Authors:  Bruce A Buckingham; Fraser Cameron; Peter Calhoun; David M Maahs; Darrell M Wilson; H Peter Chase; B Wayne Bequette; John Lum; Judy Sibayan; Roy W Beck; Craig Kollman
Journal:  Diabetes Technol Ther       Date:  2013-07-24       Impact factor: 6.118

8.  Effect of BGM Accuracy on the Clinical Performance of CGM: An In-Silico Study.

Authors:  Enrique Campos-Náñez; Marc D Breton
Journal:  J Diabetes Sci Technol       Date:  2017-05-31

Review 9.  Technology to optimize pediatric diabetes management and outcomes.

Authors:  Jessica T Markowitz; Kara R Harrington; Lori M B Laffel
Journal:  Curr Diab Rep       Date:  2013-12       Impact factor: 4.810

Review 10.  A review of artificial pancreas technologies with an emphasis on bi-hormonal therapy.

Authors:  P A Bakhtiani; L M Zhao; J El Youssef; J R Castle; W K Ward
Journal:  Diabetes Obes Metab       Date:  2013-04-21       Impact factor: 6.577

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