Most information used to evaluate diabetic statuses is collected at a special time-point,such as taking fasting plasma glucose test and providing a limited view of individual’s health and disease risk.As a new parame...Most information used to evaluate diabetic statuses is collected at a special time-point,such as taking fasting plasma glucose test and providing a limited view of individual’s health and disease risk.As a new parameter for continuously evaluating personal clinical statuses,the newly developed technique“continuous glucose monitoring”(CGM)can characterize glucose dynamics.By calculating the complexity of glucose time series index(CGI)with refined composite multi-scale entropy analysis of the CGM data,the study showed for the first time that the complexity of glucose time series in subjects decreased gradually from normal glucose tolerance to impaired glucose regulation and then to type 2 diabetes(P for trend<0.01).Furthermore,CGI was significantly associated with various parameters such as insulin sensitivity/secretion(all P<0.01),and multiple linear stepwise regression showed that the disposition index,which reflectsβ-cell function after adjusting for insulin sensitivity,was the only independent factor correlated with CGI(P<0.01).Our findings indicate that the CGI derived from the CGM data may serve as a novel marker to evaluate glucose homeostasis.展开更多
基金the National Natural Science Foundation of China(Nos.81873646 and 61903071)the Shanghai United Developing Technology Project of Municipal Hospitals(Nos.SHDC12006101 and SHDC12010115)the Shanghai Municipal Education Commission Gaofeng Clinical Medicine grant support(Nos.20161430).
文摘Most information used to evaluate diabetic statuses is collected at a special time-point,such as taking fasting plasma glucose test and providing a limited view of individual’s health and disease risk.As a new parameter for continuously evaluating personal clinical statuses,the newly developed technique“continuous glucose monitoring”(CGM)can characterize glucose dynamics.By calculating the complexity of glucose time series index(CGI)with refined composite multi-scale entropy analysis of the CGM data,the study showed for the first time that the complexity of glucose time series in subjects decreased gradually from normal glucose tolerance to impaired glucose regulation and then to type 2 diabetes(P for trend<0.01).Furthermore,CGI was significantly associated with various parameters such as insulin sensitivity/secretion(all P<0.01),and multiple linear stepwise regression showed that the disposition index,which reflectsβ-cell function after adjusting for insulin sensitivity,was the only independent factor correlated with CGI(P<0.01).Our findings indicate that the CGI derived from the CGM data may serve as a novel marker to evaluate glucose homeostasis.
