Journal article

Effectiveness of a Predictive Algorithm in the Prevention of Exercise-Induced Hypoglycemia in Type 1 Diabetes

Mary B Abraham, Raymond Davey, Michael J O'Grady, Trang T Ly, Nirubasini Paramalingam, Paul A Fournier, Anirban Roy, Benyamin Grosman, Natalie Kurtz, Janice M Fairchild, Bruce R King, Geoffrey R Ambler, Fergus Cameron, Timothy W Jones, Elizabeth A Davis



BACKGROUND: Sensor-augmented pump therapy (SAPT) with a predictive algorithm to suspend insulin delivery has the potential to reduce hypoglycemia, a known obstacle in improving physical activity in patients with type 1 diabetes. The predictive low glucose management (PLGM) system employs a predictive algorithm that suspends basal insulin when hypoglycemia is predicted. The aim of this study was to determine the efficacy of this algorithm in the prevention of exercise-induced hypoglycemia under in-clinic conditions. METHODS: This was a randomized, controlled cross-over study in which 25 participants performed 2 consecutive sessions of 30 min of moderate-intensity exercise while on basal conti..

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Funding Acknowledgements

This study was funded by the Juvenile Diabetes Research Foundation funded Australian Type 1 Diabetes Clinical Research Network. The Jaeb Centre contributed toward the review of study progress, as part of the JDRF Artificial Pancreas Consortium Network. M.B.A. is the recipient of the Channel 7 Telethon Research Fellowship 2014. Insulin pumps, glucose sensors, and the Blackberry phones were provided by Medtronic via an unrestricted grant. Medtronic had no role in the design and conduct of the study; data collection, analysis, and interpretation of the data; the preparation, review, or approval of the article; and the decision to submit the article for publication.