A Century of Diabetes Technology: Signals, Models, and Artificial Pancreas Control.

Arguably, diabetes mellitus is one of the best-quantified human conditions: elaborate in silico models describe the action of the human metabolic system; real-time signals such as continuous glucose monitoring are readily available; insulin delivery is being automated; and control algorithms are capable of optimizing blood glucose fluctuation in patients' natural environments. The transition of the artificial pancreas (AP) to everyday clinical use is happening now, and is contingent upon seamless concerted work of devices encompassing the patient in a digital treatment ecosystem. This review recounts briefly the story of diabetes technology, which began a century ago with the discovery of insulin, progressed through glucose monitoring and subcutaneous insulin delivery, and is now rapidly advancing towards fully automated clinically viable AP systems.

Glycemic Variability: Risk Factors, Assessment, and Control.

Glycemic variability (GV) a well-established risk factor for hypoglycemia and a suspected risk factor for diabetes complications. GV is also a marker of the instability of a person's metabolic system, expressed as frequent high and low glucose excursions and overall volatile glycemic control. In this review, the author discusses topics related to the assessment, quantification, and optimal control of diabetes, including (1) the notion that optimal control of diabetes, that is, lowering of HbA1c-the commonly accepted gold-standard outcome-can be achieved only if accompanied by simultaneous reduction of GV; (2) assessment and visualization of the two principal dimensions of GV, amplitude and time, which is now possible via continuous glucose monitoring (CGM) and various metrics quantifying GV and the risks associated with hypo- and hyperglycemic excursions; and (3) the evolution of diabetes science and technology beyond quantifying GV and into the realm of GV control via pharmacological agents, for example, GLP-1 receptor agonists and DPP-4 inhibitors, which have pronounced variability-reducing effect, or real-time automated closed-loop systems commonly referred to as the "artificial pancreas.

Evaluation of a Predictive Low-Glucose Management System In-Clinic.

Background: Predictions based on continuous glucose monitoring (CGM) data are the basis for automatic suspension and resumption of insulin delivery by a predictive low-glucose management feature termed "suspend before low," which is part of the Medtronic MiniMed 640G combined insulin pump and CGM system. This study assessed the safety and performance characteristics of the system in an in-clinic setting at eight sites.

Materials And Methods: In-clinic standardized increases in basal insulin delivery rates were used to induce nocturnal hypoglycemia in subjects (14-75 years) with type 1 diabetes wearing the MiniMed 640G system.