Biochemical analyses and you can data collection
Ambulatory CGM (using a FreeStyle Libre Pro sensor; Abbott Diabetes Care, Alameda, CA, USA) was performed for 14 consecutive days. The CGM data remained blinded for patients and physicians because the CGM system used was a professional version that permitted blinded CGM. Thus, patients were not able to access any real time information on their GV that might have influenced their lifestyle behaviors, including their dietary choices, during the study. After the monitoring period, we excluded data collected during the first and last days of wearing the device, considering possible inaccuracies relating to its attachment and removal 15 . We analyzed the CGM data for the remaining period using GlyCulator2 software 16 . Because an international consensus statement recommends the coefficient of variation (CV) as the primary measure of GV 17 , we analyzed the CV as an index of GV using the following formula: 100 ? [SD of glucose]/[mean glucose]. The standard deviation (SD) glucose concentration, the mean amplitude of glycemic excursions (MAGE) 18 , and the mean glucose concentration were also analyzed as secondary indices of GV. The low blood glucose index (LBGI) and high blood glucose index (HBGI), which increase with the frequency and extent of hypoglycemia and hyperglycemia, respectively, were also analyzed 19 . Furthermore, we calculated three key CGM-related indices: the percentage of readings and time per day within the target glucose range (TIR: 3.9–10.0 mmol/L), time below target glucose range (TBR: < 3.9 mmol/L), and time above the target glucose range (TAR: > 10.0 mmol/L), as recommended by the international consensus statement 20 .