BACKGROUND:Predictive low glucose management (PLGM) may help prevent hypoglycemia by stopping insulin pump delivery based on predicted sensor glucose values. MATERIALS AND METHODS: Hypoglycemic challenges were simulated using the Food and Drug Administration-accepted glucose simulator with 100 virtual patients. PLGM was then tested with a system composed of a Paradigm(®) insulin pump (Medtronic, Northridge, CA), an Enlite™ glucose sensor (Medtronic), and a BlackBerry(®) (Waterloo, ON, Canada)-based controller. Subjects (n=22) on continuous subcutaneous insulin infusion (five females, 17 males; median [range] age, 15 [range, 14-20] years; median [range] diabetes duration, 7 [2-14] years; median [range] glycated hemoglobin, 8.0% [6.7-10.4%]) exercised until the PLGM system suspended insulin delivery or until the reference blood glucose value (HemoCue(®); HemoCue GmbH, Großostheim, Germany) reached the predictive suspension threshold setting. RESULTS:PLGM reduced hypoglycemia (<70 mg/dL) in silico by 26.7% compared with no insulin suspension, as opposed to a 5.3% reduction in hypoglycemia with use of low glucose suspend (LGS). The median duration of hypoglycemia (time spent <70 mg/dL) with PLGM was significantly less than with LGS (58 min vs. 101 min, respectively; P<0.001). In the clinical trial the hypoglycemic threshold during exercise was reached in 73% of the patients, and hypoglycemia was prevented in 80% of the successful experiments. The mean (±SD) sensor glucose at predictive suspension was 92±7 mg/dL, resulting in a postsuspension nadir (by HemoCue) of 77±22 mg/dL. The suspension lasted for 90±35 (range, 30-120) min, resulting in a sensor glucose level at insulin resumption of 97±19 mg/dL. CONCLUSIONS: In silico modeling and early feasibility data demonstrate that PLGM may further reduce the severity of hypoglycemia beyond that already established for algorithms that use a threshold-based suspension.
RCT Entities:
BACKGROUND: Predictive low glucose management (PLGM) may help prevent hypoglycemia by stopping insulin pump delivery based on predicted sensor glucose values. MATERIALS AND METHODS: Hypoglycemic challenges were simulated using the Food and Drug Administration-accepted glucose simulator with 100 virtual patients. PLGM was then tested with a system composed of a Paradigm(®) insulin pump (Medtronic, Northridge, CA), an Enlite™ glucose sensor (Medtronic), and a BlackBerry(®) (Waterloo, ON, Canada)-based controller. Subjects (n=22) on continuous subcutaneous insulin infusion (five females, 17 males; median [range] age, 15 [range, 14-20] years; median [range] diabetes duration, 7 [2-14] years; median [range] glycated hemoglobin, 8.0% [6.7-10.4%]) exercised until the PLGM system suspended insulin delivery or until the reference blood glucose value (HemoCue(®); HemoCue GmbH, Großostheim, Germany) reached the predictive suspension threshold setting. RESULTS:PLGM reduced hypoglycemia (<70 mg/dL) in silico by 26.7% compared with no insulin suspension, as opposed to a 5.3% reduction in hypoglycemia with use of low glucose suspend (LGS). The median duration of hypoglycemia (time spent <70 mg/dL) with PLGM was significantly less than with LGS (58 min vs. 101 min, respectively; P<0.001). In the clinical trial the hypoglycemic threshold during exercise was reached in 73% of the patients, and hypoglycemia was prevented in 80% of the successful experiments. The mean (±SD) sensor glucose at predictive suspension was 92±7 mg/dL, resulting in a postsuspension nadir (by HemoCue) of 77±22 mg/dL. The suspension lasted for 90±35 (range, 30-120) min, resulting in a sensor glucose level at insulin resumption of 97±19 mg/dL. CONCLUSIONS: In silico modeling and early feasibility data demonstrate that PLGM may further reduce the severity of hypoglycemia beyond that already established for algorithms that use a threshold-based suspension.
Authors: Marietta Stadler; Sandra Zlamal-Fortunat; Ingrid Schütz-Fuhrmann; Birgit Rami-Merhar; Elke Fröhlich-Reiterer; Sabine Hofer; Julia Mader; Michael Resl; Alexandra Kautzky-Willer; Raimund Weitgasser; Rudolf Prager; Martin Bischof Journal: Wien Klin Wochenschr Date: 2016-04 Impact factor: 1.704