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Type 1 diabetes mellitus (T1DM) is an autoimmune disease characterized by pancreatic beta cells destruction, resulting in insulin secretion deficit (1). Insulin therapy is essential in the therapeutical management of subjects with T1DM (1). The Diabetes Complications and Control Trial (DCCT) has showed that intensive insulin treatment was associated with a reduction in the onset of complications related to diabetes. In recent years, treatment of T1DM evolved rapidly because of the significant improvements in the use of technology (2). With the spread of continuous glucose monitoring (CGM) systems, standardized metrics, summarizing time spent within optimal glucose range (time in range - TIR), time below target glucose range (TBR) and time above target glucose range (TAR), have become commonly used metrics in clinical practice (3,4). Furthermore, glucose management indicator (GMI) estimates glycated haemoglobin from the average glucose level of CGM readings for 14 days and coefficient of variation (CV) evaluates the amplitude of glucose excursions.
Advanced hybrid closed loop (AHCL) systems combine insulin pump infusion and real time CGM (rtCGM) data through an algorithm: they suspend insulin infusion if hypoglycaemia is expected and can administer automatic corrective boluses in case of hyperglycaemia (6). Different algorithms, as Model Predictive Control (MPC) or Proportional-Integral-Derivative (PID), are used by different systems available on the market and are currently used in clinical practice. Overall, AHCL are associated with improvement of glycated hemoglobin (HbA1c) and TIR opening to the possibility to gain even tighter glycemic control.
The primary objective is therefore to evaluate the glycemic improvement expressed through adjunctive CGM metrics in subjects with T1DM 24 months after starting AHCL therapy
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Dario DFP Pitocco, Prof.
Data sourced from clinicaltrials.gov
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