Predictive Low-Glucose Suspend Reduces Hypoglycemia in Adults, Adolescents, and Children With Type 1 Diabetes in an At-Home Randomized Crossover Study: Results of the PROLOG Trial

OBJECTIVE This study evaluated a new insulin delivery system designed to reduce insulin delivery when trends in continuous glucose monitoring (CGM) glucose concentrations predict future hypoglycemia. RESEARCH DESIGN AND METHODS Individuals with type 1 diabetes (n = 103, age 6–72 years, mean HbA1c 7.3% [56 mmol/mol]) participated in a 6-week randomized crossover trial to evaluate the efficacy and safety of a Tandem Diabetes Care t:slim X2 pump with Basal-IQ integrated with a Dexcom G5 sensor and a predictive low-glucose suspend algorithm (PLGS) compared with sensor-augmented pump (SAP) therapy. The primary outcome was CGM-measured time <70 mg/dL. RESULTS Both study periods were completed by 99% of participants; median CGM usage exceeded 90% in both arms. Median time <70 mg/dL was reduced from 3.6% at baseline to 2.6% during the 3-week period in the PLGS arm compared with 3.2% in the SAP arm (difference [PLGS − SAP] = −0.8%, 95% CI −1.1 to −0.5, P < 0.001). The corresponding mean values were 4.4%, 3.1%, and 4.5%, respectively, represent-ing a 31% reduction in the time <70 mg/dL with PLGS. There was no increase in mean glucose concentration (159 vs. 159 mg/dL, P = 0.40) or percentage of time spent >180 mg/dL (32% vs. 33%, P = 0.12). One severe hypoglycemic event occurred in the SAP arm and none in the PLGS arm. Mean pump suspension time was 104 min/day. CONCLUSIONS The Tandem Diabetes Care Basal-IQ PLGS system significantly reduced hypoglycemia without rebound hyperglycemia, indicating that the system can benefit adults and youth with type 1 diabetes in improving glycemic control.

[1]  T. Jones,et al.  Reducing Rates of Severe Hypoglycemia in a Population-Based Cohort of Children and Adolescents With Type 1 Diabetes Over the Decade 2000–2009 , 2011, Diabetes Care.

[2]  Darrell M. Wilson,et al.  Outpatient safety assessment of an in-home predictive low-glucose suspend system with type 1 diabetes subjects at elevated risk of nocturnal hypoglycemia. , 2013, Diabetes technology & therapeutics.

[3]  P. Cryer Hypoglycemia in type 1 diabetes mellitus. , 2010, Endocrinology and metabolism clinics of North America.

[4]  John B. Welsh,et al.  Effectiveness of Automated Insulin Management Features of the MiniMed® 640G Sensor-Augmented Insulin Pump , 2016, Diabetes technology & therapeutics.

[5]  Darrell M. Wilson,et al.  A Randomized Trial of a Home System to Reduce Nocturnal Hypoglycemia in Type 1 Diabetes , 2014, Diabetes Care.

[6]  D. Klonoff,et al.  Threshold-based insulin-pump interruption for reduction of hypoglycemia. , 2013, The New England journal of medicine.

[7]  B. Perkins,et al.  Effect of artificial pancreas systems on glycaemic control in patients with type 1 diabetes: a systematic review and meta-analysis of outpatient randomised controlled trials. , 2017, The lancet. Diabetes & endocrinology.

[8]  B. Olsen,et al.  Hypoglycemia Prevention and User Acceptance of an Insulin Pump System with Predictive Low Glucose Management , 2016, Diabetes technology & therapeutics.

[9]  Tadej Battelino,et al.  Prevention of Hypoglycemia With Predictive Low Glucose Insulin Suspension in Children With Type 1 Diabetes: A Randomized Controlled Trial , 2017, Diabetes Care.

[10]  David M Maahs,et al.  Current State of Type 1 Diabetes Treatment in the U.S.: Updated Data From the T1D Exchange Clinic Registry , 2015, Diabetes Care.

[11]  Gregory P. Forlenza,et al.  Predictive hyperglycemia and hypoglycemia minimization: In‐home double‐blind randomized controlled evaluation in children and young adolescents , 2018, Pediatric diabetes.

[12]  R. Beck,et al.  Severe hypoglycemia and diabetic ketoacidosis in adults with type 1 diabetes: results from the T1D Exchange clinic registry. , 2013, The Journal of clinical endocrinology and metabolism.

[13]  Thomas Danne,et al.  The PILGRIM study: in silico modeling of a predictive low glucose management system and feasibility in youth with type 1 diabetes during exercise. , 2014, Diabetes technology & therapeutics.

[14]  Benyamin Grosman,et al.  Glucose Outcomes with the In-Home Use of a Hybrid Closed-Loop Insulin Delivery System in Adolescents and Adults with Type 1 Diabetes , 2017, Diabetes technology & therapeutics.

[15]  Simon R. Heller,et al.  Hypoglycemia and diabetes: a report of a workgroup of the American Diabetes Association and the Endocrine Society. , 2013, The Journal of clinical endocrinology and metabolism.

[16]  B. Wayne Bequette,et al.  Predictive Low-Glucose Insulin Suspension Reduces Duration of Nocturnal Hypoglycemia in Children Without Increasing Ketosis , 2015, Diabetes Care.

[17]  J. L. Hodges,et al.  Estimates of Location Based on Rank Tests , 1963 .

[18]  Gregory P. Forlenza,et al.  Optimizing Hybrid Closed-Loop Therapy in Adolescents and Emerging Adults Using the MiniMed 670G System , 2018, Diabetes Care.

[19]  F. Chiarelli,et al.  The Effect of Recurrent Severe Hypoglycemia on Cognitive Performance in Children With Type 1 Diabetes , 2011, Journal of child neurology.

[20]  Bruce R King,et al.  Reduction in Hypoglycemia With the Predictive Low-Glucose Management System: A Long-term Randomized Controlled Trial in Adolescents With Type 1 Diabetes , 2017, Diabetes Care.

[21]  Marc D. Breton,et al.  Closed-Loop Control During Intense Prolonged Outdoor Exercise in Adolescents With Type 1 Diabetes: The Artificial Pancreas Ski Study , 2017, Diabetes Care.

[22]  B. Wayne Bequette,et al.  Predictive Hyperglycemia and Hypoglycemia Minimization: In-Home Evaluation of Safety, Feasibility, and Efficacy in Overnight Glucose Control in Type 1 Diabetes , 2017, Diabetes Care.

[23]  Eyal Dassau,et al.  International Consensus on Use of Continuous Glucose Monitoring , 2017, Diabetes Care.

[24]  Y. Benjamini,et al.  Adaptive linear step-up procedures that control the false discovery rate , 2006 .

[25]  Martin Holder,et al.  “Let the Algorithm Do the Work”: Reduction of Hypoglycemia Using Sensor-Augmented Pump Therapy with Predictive Insulin Suspension (SmartGuard) in Pediatric Type 1 Diabetes Patients , 2017, Diabetes technology & therapeutics.

[26]  Stacie L. Warren,et al.  Frequency and timing of severe hypoglycemia affects spatial memory in children with type 1 diabetes. , 2005, Diabetes care.

[27]  Hypoglycemia does not change the threshold for arousal from sleep in adolescents with type 1 diabetes. , 2012, Diabetes technology & therapeutics.

[28]  Bruce W Bode,et al.  Safety of a Hybrid Closed-Loop Insulin Delivery System in Patients With Type 1 Diabetes. , 2016, JAMA.

[29]  Philip T. Kortum,et al.  Determining what individual SUS scores mean: adding an adjective rating scale , 2009 .

[30]  T. Jones,et al.  Impaired Awareness of Hypoglycemia in a Population-Based Sample of Children and Adolescents With Type 1 Diabetes , 2009, Diabetes Care.

[31]  William L Clarke,et al.  Quantifying temporal glucose variability in diabetes via continuous glucose monitoring: mathematical methods and clinical application. , 2005, Diabetes technology & therapeutics.

[32]  D. Maahs,et al.  Frequency of Morning Ketosis After Overnight Insulin Suspension Using an Automated Nocturnal Predictive Low Glucose Suspend System , 2014, Diabetes Care.