[Analyze of the correlation and corresponding value of serum C-peptide and insulin in adult population]

Objective: To investigate the correlation between serum C-peptide and in adult population, and establish the corresponding insulin values of serum C-peptide levels. Methods: Cross-sectional study. The clinical data of the adults who underwent physical examination in the Second Medical Center of PLA General Hospital from January 2017 to December 2021 were retrospectively included. The participants were divided into type 2 diabetes group, prediabetes group and normal plasma glucose group according to the diagnostic criteria for diabetes. The correlation between serum C-peptide and insulin was explored by Pearson correlation analysis, linear regression analysis, and nonlinear regression analysis, and the corresponding insulin values of serum C-peptide were established. Results: A total of 48 008 adults were enrolled, including 31 633 males (65.9%) and 16 375 females (34.1%), aged (50.1±9.9) years (18-89 years). There were 8 160 subjects (17.0%) with type 2 diabetes, 13 263 subjects (27.6%) with prediabetes, and 26 585 subjects (55.4%) with normal plasma glucose. The serum fasting C-peptide (FCP, M(Q₁, Q₃)] of the three groups were 2.76(2.18, 3.47), 2.54(1.99, 3.21) and 2.18(1.71, 2.79)μg/L, respectively. The fasting insulin [FINS, M(Q₁,Q₃)] of the three groups were 10.98(7.57, 16.09), 10.06(6.95, 14.47) and 8.43(5.86,12.12)mU/L, respectively. FCP was positively correlated with FINS (r=0.82), and 2 h postprandial C-peptide (2 h CP) was positively correlated with 2 h postprandial insulin (2 h INS) (r=0.84) (both P<0.001). FCP was linearly associated with FINS (R²=0.68), and 2 h CP was linearly associated with 2 h INS (R²=0.71) (both P<0.001). There was a power function correlation between FCP and FINS (R²=0.74), and 2 h CP and 2 h INS (R²=0.78) (both P<0.001). The results of the statistical analysis were similar in various glucose metabolism subgroups. Since the fitting degree of the power function model was higher than that of the linear model, the power function model was the best model. The power function equation was FINS=2.96×FCP^1.32, and 2 h INS=1.64×(2 h CP)^1.60, respectively. Multivariate linear regression analysis demonstrated that FCP was a related factor of FINS (R²=0.70, P<0.001) and 2 h CP was a related factor of 2 h INS (R²=0.73, P<0.001), after adjusting for related confounders. Conclusions: There was a power function correlation between FCP and FINS, 2 h CP and 2 h INS in adult population. The insulin values corresponding to C-peptide levels were established in the study.

[Relationship between hemoglobin and serum uric acid in adults with various glucose metabolism status]

Objective: To investigate the relationship between hemoglobin and serum uric acid in adults with various glucose metabolism status. Methods: The demographic data and biochemical indicators of the adult population who had received physical examination in the Second Medical Center of the PLA General Hospital from January 2018 to December 2021 were collected. The subjects were divided into two groups according to the level of serum uric acid: the normal uric acid group and the hyperuricemia group. The relationship between hemoglobin (stratified into four levels of Q₁ to Q₄ by the quartile) and serum uric acid was quantified by using Pearson correlation and logistic regression analysis. The effects of age and glucose metabolism status on the relationship between hemoglobin and serum uric acid were analyzed. Results: A total of 33 183 adults were enrolled with age (50.6±10.0) years. The level of hemoglobin in the normal uric acid group (142.61±14.24) g/L was significantly lower than that in the hyperuricemia group [(151.79±11.24) g/L, P<0.001]. Univariate Pearson correlation analysis showed that hemoglobin was positively associated with serum uric acid (r=0.444, P<0.001). After adjusting for related confounding factors, multivariate logistic regression analysis showed that hemoglobin was associated with serum uric acid, and the OR values (95%CI) of hemoglobin Q₂ to Q₄ group were 1.29 (1.13-1.48), 1.42 (1.24-1.62) and 1.51 (1.32-1.72), respectively (P_trend<0.001) when compared with hemoglobin Q₁ group. Subgroup analysis and hierarchical interaction analysis suggested that with the increase of hemoglobin, the serum uric acid in the age<60 years subgroup, normal glucose subgroup and prediabetes subgroup increased gradually (P_trend<0.05 and P_interaction<0.001). Conclusion: The association between hemoglobin and serum uric acid in adults is affected by age and glucose metabolism status.

[Correlation between glycemic variability and glycosylated hemoglobin level during follow-up in elderly male patients with type 2 diabetes in Beijing]

Objective: To investigate the relationship between glycemic variability and glycosylated hemoglobin (HbA1c) level during follow-up in elderly male patients with type 2 diabetes. Methods: Retrospective cohort study. A total of 200 elderly male patients who received continuous glucose monitoring from January 2007 to January 2011 were recruited in the Second Medical Center of PLA General Hospital. The subjects were divided into two groups according to baseline mean amplitude of glycaemic excursion (MAGE) level, including MAGE <3.9 mmol/L group (n=114) and MAGE ≥3.9 mmol/L group (n=86). The correlation between baseline MAGE and mean HbA1c during follow-up were evaluated by univariate Pearson correlation analysis and multivariate linear regression analysis. Results: Baseline characteristics including age, body mass index, waist circumference, smoking, drinking, fasting blood glucose, blood lipid and blood pressure were comparable between MAGE <3.9 mmol/L group and MAGE ≥3.9 mmol/L group. The average follow-up period was 12.5 years. The mean HbA1c during follow-up in MAGE ≥3.9 mmol/L group was significantly higher than that in MAGE <3.9 mmol/L group (7.23%±0.72% vs. 6.91%±0.77%, t=-2.94, P=0.004). The proportion of mean HbA1c <7.0% during follow-up in MAGE ≥3.9 mmol/L group was 44.2% (38/86), which was significantly lower than that in MAGE <3.9 mmol/L group [60.5% (69/114), χ²=5.26, P=0.022]. In univariate analysis, MAGE at baseline was correlated with the mean HbA1c during follow-up (r=0.306, P<0.001). Multivariate linear regression analysis suggested that the baseline MAGE remained an independent influential factor of mean HbA1c (β=0.09, 95%CI: 0.03 to 0.15, P=0.006, R²=0.31) after several confounding factors were adjusted. Conclusions: With the increased glycemic variability at baseline, mean HbA1c level during follow-up is accordingly elevated. The glycemic variability at baseline is independently related to mean HbA1c level during follow-up in elderly male patients with type 2 diabetes.

A comparative meta-analysis of the efficacy of statin-ezetimibe co-therapy versus statin monotherapy in reducing cardiovascular and cerebrovascular adverse events in patients with type 2 diabetes mellitus

OBJECTIVE

This study evaluates the efficacy of statin-ezetimibe co-therapy compared to statin monotherapy in reducing cardiovascular and/or cerebrovascular disease (CVD) prevalence in diabetes and non-diabetes patients.

PATIENTS AND METHODS

Literature search was conducted in electronic databases and study selection was based on pre-determined eligibility criteria. Random-effects metanalyses were performed to examine the risk of CVD incidence between statin-ezetimibe co-therapy and statin monotherapy and subgroups were performed to examine the significance of differences between diabetic and non-diabetic individuals. A pooled analysis of hazard ratios of statin-ezetimibe combination versus statin monotherapy in the prevalence of CVD reported by the individual studies was also performed.

RESULTS

8 studies (136893 individuals; 80790 diabetics, 85555 non-diabetics; age 63.5 years [95% confidence interval (CI) 61.2, 65.8]; 61.5% [95% CI 55.2, 67.8] males) were included. Follow-up duration was 45 months [95% CI 27.5, 62.5]. Risk of CVD prevalence was significantly less with ezetimibe-statin than with statin alone in both diabetes (RR 0.69 [95% CI 0.67, 0.73]; p<0.00001) and in non-diabetes (RR 0.68 [95% CI 0.52, 0.90]; p=0.006) subjects (subgroup difference: chi2=0.00; p=0.97). Risk of prevalence of stroke was significantly less with ezetimibe-statin than with statin monotherapy in diabetes (RR 0.74 [95% CI 0.56, 0.98]; p=0.03) but non-significantly less in non-diabetes patients (RR 0.74 [95% CI 0.39, 1.41]; p=0.39) and this sub-group difference was also not statistically significant (chi2=0.00; p=0.99).

CONCLUSIONS

Statin-ezetimibe co-therapy is found more efficacious than statin monotherapy in reducing the incidence of CVD with no significant difference between diabetic and non-diabetic individuals.