BACKGROUND: This feasibility study investigated the insulin-delivery characteristics of the Hypoglycemia-Hyperglycemia Minimizer (HHM) System-an automated insulin delivery device-in participants with type 1 diabetes. METHODS: Thirteen adults with type 1 diabetes were enrolled in this nonrandomized, uncontrolled, clinical-research-center-based feasibility study. The HHM System comprised a continuous subcutaneous insulin infusion pump, a continuous glucose monitor (CGM), and a model predictive control algorithm with a safety module, run on a laptop platform. Closed-loop control lasted approximately 20 hours, including an overnight period and two meals. RESULTS: When attempting to minimize glucose excursions outside of a prespecified target zone, the predictive HHM System decreased insulin infusion rates below the participants' preset basal rates in advance of below-zone excursions (CGM < 90 mg/dl), and delivered 80.4% less insulin than basal during those excursions. Similarly, the HHM System increased infusion rates above basal during above-zone excursions (CGM > 140 mg/dl), delivering 39.9% more insulin than basal during those excursions. Based on YSI, participants spent a mean ± standard deviation (SD) of 0.2 ± 0.5% of the closed-loop control time at glucose levels < 70 mg/dl, including 0.3 ± 0.9% for the overnight period. The mean ± SD glucose based on YSI for all participants was 164.5 ± 23.5 mg/dl. There were nine instances of algorithm-recommended supplemental carbohydrate administrations, and there was no severe hypoglycemia or diabetic ketoacidosis. CONCLUSIONS: Results of this study indicate that the current HHM System is a feasible foundation for development of a closed-loop insulin delivery device.
BACKGROUND: This feasibility study investigated the insulin-delivery characteristics of the Hypoglycemia-Hyperglycemia Minimizer (HHM) System-an automated insulin delivery device-in participants with type 1 diabetes. METHODS: Thirteen adults with type 1 diabetes were enrolled in this nonrandomized, uncontrolled, clinical-research-center-based feasibility study. The HHM System comprised a continuous subcutaneous insulin infusion pump, a continuous glucose monitor (CGM), and a model predictive control algorithm with a safety module, run on a laptop platform. Closed-loop control lasted approximately 20 hours, including an overnight period and two meals. RESULTS: When attempting to minimize glucose excursions outside of a prespecified target zone, the predictive HHM System decreased insulin infusion rates below the participants' preset basal rates in advance of below-zone excursions (CGM < 90 mg/dl), and delivered 80.4% less insulin than basal during those excursions. Similarly, the HHM System increased infusion rates above basal during above-zone excursions (CGM > 140 mg/dl), delivering 39.9% more insulin than basal during those excursions. Based on YSI, participants spent a mean ± standard deviation (SD) of 0.2 ± 0.5% of the closed-loop control time at glucose levels < 70 mg/dl, including 0.3 ± 0.9% for the overnight period. The mean ± SD glucose based on YSI for all participants was 164.5 ± 23.5 mg/dl. There were nine instances of algorithm-recommended supplemental carbohydrate administrations, and there was no severe hypoglycemia or diabetic ketoacidosis. CONCLUSIONS: Results of this study indicate that the current HHM System is a feasible foundation for development of a closed-loop insulin delivery device.
Authors: Stephen D Patek; B Wayne Bequette; Marc Breton; Bruce A Buckingham; Eyal Dassau; Francis J Doyle; John Lum; Lalo Magni; Howard Zisser Journal: J Diabetes Sci Technol Date: 2009-03-01
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Authors: Daniel A Finan; Eyal Dassau; Marc D Breton; Stephen D Patek; Thomas W McCann; Boris P Kovatchev; Francis J Doyle; Brian L Levy; Ramakrishna Venugopalan Journal: J Diabetes Sci Technol Date: 2015-06-30
Authors: Daniel A Finan; Thomas W McCann; Kathleen Rhein; Eyal Dassau; Marc D Breton; Stephen D Patek; Henry Anhalt; Boris P Kovatchev; Francis J Doyle; Stacey M Anderson; Howard Zisser; Ramakrishna Venugopalan Journal: J Diabetes Sci Technol Date: 2014-05-18