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

M.B. Abraham, Ray Davey, Martin J. O'Grady, Trang T. Ly, N. Paramalingam, Paul A. Fournier, A. Roy, B. Grosman, N. Kurtz, J.M. Fairchild, B.R. King, G.R. Ambler, F. Cameron, Timothy W. Jones, Elizabeth A. Davis

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)


© Copyright 2016, Mary Ann Liebert, Inc. 2016.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 continuous subcutaneous insulin infusion on 2 study days: a control day with SAPT alone and an intervention day with SAPT and PLGM. The predictive algorithm suspended basal insulin when sensor glucose was predicted to be below the preset hypoglycemic threshold in 30 min. We tested preset hypoglycemic thresholds of 70 and 80 mg/dL. The primary outcome was the requirement for hypoglycemia treatment (symptomatic hypoglycemia with plasma glucose
Original languageEnglish
Pages (from-to)543-550
Number of pages8
JournalDiabetes Technology and Therapeutics
Issue number9
Publication statusPublished - 1 Sep 2016


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