Introduction and application of non-parametric regression method in medical research / 复旦学报（医学版）

This article introduced the basic theory of non-parametric regression and its application in medical and public health research for methodological reference.We conducted Cox proportional hazard models with restricted cubic splines using chronic disease management data from a Center for Disease Control and Prevention.We aimed to explore the separate and combined effects of mean fasting blood glucose level and glucose variability on all-cause mortality among individuals with type 2 diabetes.A non-linear association was observed between glucose variability and the risk of all-cause mortality.The association between glucose variability and all-cause mortality was stronger at higher mean fasting blood glucose levels compared to lower levels.The non-parametric regression methods comprehensively explored dose-response relationships between continuous exposure and outcome,revealing the combined effects of continuous exposures,which provided recommendations for targeted interventions.The method showed promising application value in medical and public health research.

Association between blood glucose level derived using the oral glucose tolerance test and glycated hemoglobin level

BACKGROUND/AIMS: Glycated hemoglobin (HbA1c) is widely used as a marker of glycemic control. Translation of the HbA1c level to an average blood glucose level is useful because the latter figure is easily understood by patients. We studied the association between blood glucose levels revealed by the oral glucose tolerance test (OGTT) and HbA1c levels in a Korean population. METHODS: A total of 1,000 subjects aged 30 to 64 years from the Cardiovascular and Metabolic Diseases Etiology Research Center cohort were included. Fasting glucose levels, post-load glucose levels at 30, 60, and 120 minutes into the OGTT, and HbA1c levels were measured. RESULTS: Linear regression of HbA1c with mean blood glucose levels derived using the OGTT revealed a significant correlation between these measures (predicted mean glucose [mg/dL] = 49.4 × HbA1c [%] - 149.6; R2 = 0.54, p < 0.001). Our linear regression equation was quite different from that of the Alc-Derived Average Glucose (ADAG) study and Diabetes Control and Complications Trial (DCCT) cohort. CONCLUSIONS: Discrepancies between our results and those of the ADAG study and DCCT cohort may be attributable to differences in the test methods used and the extent of insulin secretion. More studies are needed to evaluate the association between HbA1c and self monitoring blood glucose levels.

Correlation of Blood Glucose Variability and TCM Syndromes in Type 2 Diabetic Patients / 中国中医药信息杂志

Objective To explore the correlation of blood glucose variability and TCM syndromes in type 2 diabetic patients. Methods A total of 64 type 2 diabetic patients from China-Japan Friendship Hospital during Jan. 2010 to Dec. 2013 with complete clinical data were measured by continuous glucose monitoring system (CGMs) for 3 days. Patients were divided into empirical group and deficiency group. The empirical group included heat excess and fluid deficiency syndrome, phlegm-dampness stagnation syndrome and blood stasis syndrome. The deficiency group included qi-yin deficiency syndrome and yin-yang deficiency syndrome. The mean blood glucose (MBG), and mean amplitude of glycemic excursions (MAGE) were compared between the groups and types in each group, and the correlation with TCM syndrome types were analyzed. Results There was no significant difference in MBG between two groups (P>0.05). MAGE in deficiency group was higher than that in empirical group (P0.05), but in deficiency group, MAGE in yin-yang deficiency syndrome was higher than that in qi-yin deficiency syndrome (P<0.05). Conclusion Blood glucose variability has no correlation with MBG in type 2 diabetic patients. Glucose showed significant variability in deficiency group, and the most serious glucose variability was found in type of yin-yang deficiency syndrome.