Parameters of glucose dynamics recorded by the continuous glucose monitoring system (CGMS) could help the controlling of glycemic fluctuations that is important in diabetes management. Multiscale entropy (MSE) analysis has recently been developed to measure the complexity of physical and physiological time sequences. A reduced MSE complexity index indicates the increased repetition patterns of the time sequence, and thus a decreased complexity in this system. No study investigated the MSE analysis of glucose dynamics in diabetes. This study was designed to compare the complexity of glucose dynamics between the diabetic patients (n = 17) and the control subjects (n = 13) matched for sex, age and body mass index via MSE analysis using CGMS data. Compared with the control subjects, the diabetic patients revealed a significant increase (P < 0.001) in the mean (diabetic patients 166.0 ± 10.4 versus control subjects 93.3 ± 1.5 mg/dL), standard deviation (51.7 ± 4.3 versus 11.1 ± 0.5 mg/dL) and mean amplitude of glycemic excursions (127.0 ± 9.2 versus 27.7 ± 1.3 mg/dL) of the glucose levels; and a significant decrease (P < 0.001) in the MSE complexity index (5.09 ± 0.23 versus 7.38 ± 0.28). In conclusion, the complexity of glucose dynamics is decreased in diabetes. This finding implies the reactivity of glucoregualtion is impaired in the diabetic patients. Such impairment presenting as an increased regularity of glycemic fluctuating pattern could be detected by MSE analysis. Thus, the MSE complexity index could potentially be used as a biomarker in the monitoring of diabetes.