CONTEXT: A challenge for automated glycemic control in type 1 diabetes (T1D) is the large variation in insulin needs between individuals and within individuals at different times in their lives. OBJECTIVES: The objectives of the study was to test the ability of a third-generation bihormonal bionic pancreas algorithm, initialized with only subject weight; to adapt automatically to the different insulin needs of adults and adolescents; and to evaluate the impact of optional, automatically adaptive meal-priming boluses. DESIGN: This was a randomized controlled trial. SETTING: The study was conducted at an inpatient clinical research center. PATIENTS: Twelve adults and 12 adolescents with T1D participated in the study. INTERVENTIONS: Subjects in each age group were randomized to automated glycemic control for 48 hours with or without automatically adaptive meal-priming boluses. MAIN OUTCOME MEASURES: Mean plasma glucose (PG), time with PG less than 60 mg/dL, and insulin total daily dose were measured. RESULTS: The 48-hour mean PG values with and without adaptive meal-priming boluses were 132 ± 9 vs 146 ± 9 mg/dL (P = .03) in adults and 162 ± 6 vs 175 ± 9 mg/dL (P = .01) in adolescents. Adaptive meal-priming boluses improved mean PG without increasing time spent with PG less than 60 mg/dL: 1.4% vs 2.3% (P = .6) in adults and 0.1% vs 0.1% (P = 1.0) in adolescents. Large increases in adaptive meal-priming boluses and shifts in the timing and size of automatic insulin doses occurred in adolescents. Much less adaptation occurred in adults. There was nearly a 4-fold variation in the total daily insulin dose across all cohorts (0.36-1.41 U/kg · d). CONCLUSIONS: A single control algorithm, initialized only with subject weight, can quickly adapt to regulate glycemia in patients with TID and highly variable insulin requirements.
RCT Entities:
CONTEXT: A challenge for automated glycemic control in type 1 diabetes (T1D) is the large variation in insulin needs between individuals and within individuals at different times in their lives. OBJECTIVES: The objectives of the study was to test the ability of a third-generation bihormonal bionic pancreas algorithm, initialized with only subject weight; to adapt automatically to the different insulin needs of adults and adolescents; and to evaluate the impact of optional, automatically adaptive meal-priming boluses. DESIGN: This was a randomized controlled trial. SETTING: The study was conducted at an inpatient clinical research center. PATIENTS: Twelve adults and 12 adolescents with T1D participated in the study. INTERVENTIONS: Subjects in each age group were randomized to automated glycemic control for 48 hours with or without automatically adaptive meal-priming boluses. MAIN OUTCOME MEASURES: Mean plasma glucose (PG), time with PG less than 60 mg/dL, and insulin total daily dose were measured. RESULTS: The 48-hour mean PG values with and without adaptive meal-priming boluses were 132 ± 9 vs 146 ± 9 mg/dL (P = .03) in adults and 162 ± 6 vs 175 ± 9 mg/dL (P = .01) in adolescents. Adaptive meal-priming boluses improved mean PG without increasing time spent with PG less than 60 mg/dL: 1.4% vs 2.3% (P = .6) in adults and 0.1% vs 0.1% (P = 1.0) in adolescents. Large increases in adaptive meal-priming boluses and shifts in the timing and size of automatic insulin doses occurred in adolescents. Much less adaptation occurred in adults. There was nearly a 4-fold variation in the total daily insulin dose across all cohorts (0.36-1.41 U/kg · d). CONCLUSIONS: A single control algorithm, initialized only with subject weight, can quickly adapt to regulate glycemia in patients with TID and highly variable insulin requirements.
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Authors: Daniela Elleri; Janet M Allen; Marianna Nodale; Malgorzata E Wilinska; Jasdip S Mangat; Anne Mette F Larsen; Carlo L Acerini; David B Dunger; Roman Hovorka Journal: Diabetes Technol Ther Date: 2011-02-28 Impact factor: 6.118
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Authors: Jordan S Sherwood; Rabab Z Jafri; Courtney A Balliro; Hui Zheng; Firas H El-Khatib; Edward R Damiano; Steven J Russell; Melissa S Putman Journal: J Cyst Fibros Date: 2019-08-13 Impact factor: 5.482
Authors: Steven J Russell; Firas H El-Khatib; Manasi Sinha; Kendra L Magyar; Katherine McKeon; Laura G Goergen; Courtney Balliro; Mallory A Hillard; David M Nathan; Edward R Damiano Journal: N Engl J Med Date: 2014-06-15 Impact factor: 91.245