AIMS: To evaluate the clinical factors affecting daily and day-to-day glucose variability by using continuous glucose monitoring. METHODS: We performed a cross-sectional analysis of patients with type 2 diabetes mellitus (T2DM) who underwent a glucagon stimulation test (GST) with 72 h of continuous glucose monitoring. Daily glucose variability was evaluated by mean amplitude of glycemic excursions [MAGE], percentage coefficient of variation for glucose (%CV), and day-to-day glucose variability (mean of daily differences [MODD]) by using continuous glucose monitoring. Correlations of clinical factors, including insulin secretion ability by the GST with MAGE, %CV, and MODD, were analyzed. RESULTS: In 83 T2DM with insulin therapy, age and hemoglobin A1c (HbA1c) correlated with MAGE and %CV, fasting plasma glucose with MAGE and MODD, and increment of C-peptide immunoreactivity (ΔCPR) by GST correlated inversely with MAGE, %CV, and MODD. In 126 T2DM without insulin therapy, age, diastolic blood pressure, and triglycerides correlated with MODD, HbA1c with MAGE and MODD, and ΔCPR inversely correlated with %CV. Use of α-glucosidase inhibitors inversely correlated with %CV, whereas that of sulfonylurea was associated with MAGE and %CV. CONCLUSIONS: These results suggest that ΔCPR correlated with stability of glycemic control, whereas poorly controlled diabetes is associated with increase in glucose variability. α-glucosidase inhibitors may be superior to sulfonylureas in reducing the glucose variability in T2DM.
AIMS: To evaluate the clinical factors affecting daily and day-to-day glucose variability by using continuous glucose monitoring. METHODS: We performed a cross-sectional analysis of patients with type 2 diabetes mellitus (T2DM) who underwent a glucagon stimulation test (GST) with 72 h of continuous glucose monitoring. Daily glucose variability was evaluated by mean amplitude of glycemic excursions [MAGE], percentage coefficient of variation for glucose (%CV), and day-to-day glucose variability (mean of daily differences [MODD]) by using continuous glucose monitoring. Correlations of clinical factors, including insulin secretion ability by the GST with MAGE, %CV, and MODD, were analyzed. RESULTS: In 83 T2DM with insulin therapy, age and hemoglobin A1c (HbA1c) correlated with MAGE and %CV, fasting plasma glucose with MAGE and MODD, and increment of C-peptide immunoreactivity (ΔCPR) by GST correlated inversely with MAGE, %CV, and MODD. In 126 T2DM without insulin therapy, age, diastolic blood pressure, and triglycerides correlated with MODD, HbA1c with MAGE and MODD, and ΔCPR inversely correlated with %CV. Use of α-glucosidase inhibitors inversely correlated with %CV, whereas that of sulfonylurea was associated with MAGE and %CV. CONCLUSIONS: These results suggest that ΔCPR correlated with stability of glycemic control, whereas poorly controlled diabetes is associated with increase in glucose variability. α-glucosidase inhibitors may be superior to sulfonylureas in reducing the glucose variability in T2DM.