Design and Clinical Evaluation of a Novel Low-Glucose Prediction Algorithm with Mini-Dose Stable Glucagon Delivery in Post-Bariatric Hypoglycemia.

Autor:	Laguna Sanz AJ; 1 Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University , Cambridge, Massachusetts., Mulla CM; 2 Research Division, Joslin Diabetes Center , Boston, Massachusetts., Fowler KM; 2 Research Division, Joslin Diabetes Center , Boston, Massachusetts., Cloutier E; 2 Research Division, Joslin Diabetes Center , Boston, Massachusetts., Goldfine AB; 2 Research Division, Joslin Diabetes Center , Boston, Massachusetts., Newswanger B; 3 Research and Development Xeris Pharmaceuticals, Inc. , Austin, Texas., Cummins M; 3 Research and Development Xeris Pharmaceuticals, Inc. , Austin, Texas., Deshpande S; 1 Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University , Cambridge, Massachusetts., Prestrelski SJ; 3 Research and Development Xeris Pharmaceuticals, Inc. , Austin, Texas., Strange P; 3 Research and Development Xeris Pharmaceuticals, Inc. , Austin, Texas., Zisser H; 4 Department of Chemical Engineering, University of California , Santa Barbara, Santa Barbara, California., Doyle FJ 3rd; 1 Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University , Cambridge, Massachusetts., Dassau E; 1 Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University , Cambridge, Massachusetts.; 2 Research Division, Joslin Diabetes Center , Boston, Massachusetts., Patti ME; 2 Research Division, Joslin Diabetes Center , Boston, Massachusetts.
Jazyk:	angličtina
Zdroj:	Diabetes technology & therapeutics [Diabetes Technol Ther] 2018 Feb; Vol. 20 (2), pp. 127-139.
DOI:	10.1089/dia.2017.0298
Abstrakt:	Background: Postbariatric hypoglycemia (PBH) is a complication of bariatric surgery with limited therapeutic options. We developed an event-based system to predict and detect hypoglycemia based on continuous glucose monitor (CGM) data and recommend delivery of minidose liquid glucagon. Methods: We performed an iterative development clinical study employing a novel glucagon delivery system: a Dexcom CGM connected to a Windows tablet running a hypoglycemia prediction algorithm and an Omnipod pump filled with an investigational stable liquid glucagon formulation. Meal tolerance testing was performed in seven participants with PBH and history of neuroglycopenia. Glucagon was administered when hypoglycemia was predicted. Primary outcome measures included the safety and feasibility of this system to predict and prevent severe hypoglycemia. Secondary outcomes included hypoglycemia prediction by the prediction algorithm, minimization of time below hypoglycemia threshold using glucagon, and prevention of rebound hyperglycemia. Results: The hypoglycemia prediction algorithm alerted for impending hypoglycemia in the postmeal state, prompting delivery of glucagon (150 μg). After observations of initial incomplete efficacy to prevent hypoglycemia in the first two participants, system modifications were implemented: addition of PBH-specific detection algorithm, increased glucagon dose (300 μg), and a second glucagon dose if needed. These modifications, together with rescue carbohydrates provided to some participants, contributed to progressive improvements in glucose time above the hypoglycemia threshold (75 mg/dL). Conclusions: Preliminary results indicate that our event-based automatic monitoring algorithm successfully predicted likely hypoglycemia. Minidose glucagon therapy was well tolerated, without prolonged or severe hypoglycemia, and without rebound hyperglycemia.
Databáze:	MEDLINE
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