Relationship between glucose variability evaluated by continuous glucose monitoring and clinical factors, including glucagon-stimulated insulin secretion in patients with type 2 diabetes

Assessing the temporal within-day glycemic variability during hospitalization in patients with type 2 diabetes patients using continuous glucose monitoring: a retrospective observational study

AIMS

Frequent and extensive within-day glycemic variability (GV) in blood glucose levels may increase the risk of hypoglycemia and long-term mortality in hospitalized patients with diabetes. We aimed to assess the amplitude and frequency of within-day GV in inpatients with type 2 diabetes and to explore the factors influencing within-day GV.

METHODS

We conducted a single-center, retrospective observational study by analyzing hospital records and 10-day real-time continuous glucose monitoring data. Within-day GV was assessed using the coefficient of variation (%CV). The primary outcome was the amplitude and frequency of within-day GV. The frequency of within-day GV was assessed by the consecutive days (CD) of maintaining within the target %CV range after first reaching it (CD after first reaching the target) and the maximum consecutive days of maintaining within the target %CV range (Max-CD). The target %CV range was less than 24.4%. We evaluated the factors influencing within-day GV using COX regression and Poisson regression models.

RESULTS

A total of 1050 cases were analyzed, of whom 86.57% reduced the amplitude of within-day GV before the sixth day of hospitalization. Of the 1050 hospitalized patients, 66.57% stayed within the target %CV range for less than two days after first reaching the target and 69.71% experienced a Max-CD of fewer than four days. Reducing the average postprandial glucose excursion (hazard ratio [HR]: 0.81, 95% confidence interval [CI]: 0.77-0.85; incidence rate ratios [IRR]: 0.72, 95% CI: 0.69-0.74) and the use of α-glucosidase inhibitors (IRR: 1.1, 95% CI: 1.01-1.18) and glucagon-like peptide-1 agonist (IRR: 1.30, 95% CI: 1.02-1.65) contributed to reducing the amplitude and decreasing the frequency of within-day GV. However, the use of insulin (HR: 0.64, 95% CI: 0.55-0.75; IRR: 0.86, 95% CI: 0.79-0.93) and glinide (HR: 0.47, 95% CI: 0.31-0.73; IRR: 0.84, 95% CI: 0.73-0.97) may lead to an increased frequency of within-day GV.

CONCLUSIONS

An increasing frequency of within-day GV was observed during the hospitalization in patients with type 2 diabetes, despite the effective reduction in the amplitude of within-day GV. Using medications designed to lower postprandial blood glucose could contribute to minimize the risk of frequent within-day GV.

Clinical and Lifestyle Determinants of Continuous Glucose Monitoring Metrics in Insulin-Treated Patients with Type 2 Diabetes Mellitus

BACKGRUOUND

There was limited evidence to evaluate the association between lifestyle habits and continuous glucose monitoring (CGM) metrics. Thus, we aimed to depict the behavioral and metabolic determinants of CGM metrics in insulin-treated patients with type 2 diabetes mellitus (T2DM).

METHODS

This is a prospective observational study. We analyzed data from 122 insulin-treated patients with T2DM. Participants wore Dexcom G6 and Fitbit, and diet information was identified for 10 days. Multivariate-adjusted logistic regression analysis was performed for the simultaneous achievement of CGM-based targets, defined by the percentage of time in terms of hyper, hypoglycemia and glycemic variability (GV). Intake of macronutrients and fiber, step counts, sleep, postprandial C-peptide-to-glucose ratio (PCGR), information about glucose lowering medications and metabolic factors were added to the analyses. Additionally, we evaluated the impact of the distribution of energy and macronutrient during a day, and snack consumption on CGM metrics.

RESULTS

Logistic regression analysis revealed that female, participants with high PCGR, low glycosylated hemoglobin (HbA1c) and daytime step count had a higher probability of achieving all targets based on CGM (odds ratios [95% confidence intervals] which were 0.24 [0.09 to 0.65], 1.34 [1.03 to 1.25], 0.95 [0.9 to 0.99], and 1.15 [1.03 to 1.29], respectively). And participants who ate snacks showed a shorter period of hyperglycemia and less GV compared to those without.

CONCLUSION

We confirmed that residual insulin secretion, daytime step count, HbA1c, and women were the most relevant determinants of adequate glycemic control in insulin-treated patients with T2DM. In addition, individuals with snack consumption were exposed to lower times of hyperglycemia and GV.

Log-linear relationship between endogenous insulin secretion and glycemic variability in patients with type 2 diabetes on continuous glucose monitoring

The contribution of endogenous insulin secretion to glycemic variability (GV) may differ between patients with impaired insulin secretion and those with preserved secretion. Our objective was to determine the linearity of the relationship between fasting C-peptide (CPR) as a marker of endogenous insulin secretion and GV in type 2 diabetes (T2DM), regardless of the type of antidiabetic treatment. We conducted a prospective observational study using continuous glucose monitoring obtained from 284 Japanese outpatients with T2DM with various HbA1c values and antidiabetic treatment. We constructed a prediction curve of base-line CPR versus coefficient of variation (CV) and identified the clinical factors associated with CV using multiple regression analysis. Fasting CPR showed a significant negative log-linear relationship with CV (P < 0.0001), and the latter being strikingly high in the low-CPR group. The multiple regression analysis showed that low CPR was an independent predictor of high CV (P < 0.0001). The significant correlations were sustained in both patients with/without insulin treatment. The contribution of endogenous insulin secretion to GV depends on the extent of insulin secretion impairment. Fasting CPR may represent a useful indicator of GV instability in T2DM.

CGMS and Glycemic Variability, Relevance in Clinical Research to Evaluate Interventions in T2D, a Literature Review

Glycemic variability (GV) appears today as an integral component of glucose homeostasis for the management of type 2 diabetes (T2D). This review aims at investigating the use and relevance of GV parameters in interventional and observational studies for glucose control management in T2D. It will first focus on the relationships between GV parameters measured by continuous glucose monitoring system (CGMS) and glycemic control and T2D-associated complications markers. The second part will be dedicated to the analysis of GV parameters from CGMS as outcomes in interventional studies (pharmacological, nutritional, physical activity) aimed at improving glycemic control in patients with T2D. From 243 articles first identified, 63 articles were included (27 for the first part and 38 for the second part). For both analyses, the majority of the identified studies were pharmacological. Lifestyle studies (including nutritional and physical activity-based studies, N-AP) were poorly represented. Concerning the relationships of GV parameters with those for glycemic control and T2D related-complications, the standard deviation (SD), the coefficient of variation (CV), the mean blood glucose (MBG), and the mean amplitude of the glycemic excursions (MAGEs) were the most studied, showing strong relationships, in particular with HbA1c. Regarding the use and relevance of GV as an outcome in interventional studies, in pharmacological ones, SD, MAGE, MBG, and time in range (TIR) were the GV parameters used as main criteria in most studies, showing significant improvement after intervention, in parallel or not with glycemic control parameters' (HbA1c, FBG, and PPBG) improvement. In N-AP studies, the same results were observed for SD, MAGE, and TIR. Despite the small number of N-AP studies addressing both GV and glycemic control parameters compared to pharmacological ones, N-AP studies have shown promising results on GV parameters and would require more in-depth work. Evaluating CGMS-GV parameters as outcomes in interventional studies may provide a more integrative dimension of glucose control than the standard postprandial follow-up. GV appears to be a key component of T2D dysglycemia, and some parameters such as MAGE, SD, or TIR could be used routinely in addition to classical markers of glycemic control such as HbA1c, fasting, or postprandial glycemia.

Association of Glycated Albumin/Glycosylated Hemoglobin Ratio with Blood Glucose Fluctuation and Long-Term Blood Glucose Control in Patients with Type 2 Diabetes Mellitus

OBJECTIVE

This study aimed to investigate the association of the glycated albumin (GA)/glycosylated hemoglobin (HbA1c) ratio with the mean amplitude of glycemic excursion (MAGE) in type 2 diabetes mellitus (T2DM).

METHODS

A total of 102 patients with T2DM who were first treated in Jinjiang Hospital of Fujian Province were enrolled in this study. The patients' general clinical data, including HbA1c, GA, fasting blood glucose, and fasting and peak C-peptide values upon diagnosis and after one year of follow-up, were collected, and their MAGE was calculated.

RESULTS

With the increase of the GA/HbA1c ratio at baseline, the patients' fasting and peak C-peptide values decreased gradually from baseline to follow-up, while their MAGE, HbA1c, and fasting blood glucose increased gradually. A regression analysis demonstrated that the baseline MAGE was independently positively correlated with the GA/HbA1c ratio. A Cox regression analysis demonstrated that a baseline GA/HbA1c ratio of >2.78 was an independent risk factor for poor fasting blood glucose and HbA1c.

CONCLUSION

The GA/HbA1c ratio is closely related to the MAGE and islet function in patients with T2DM.

Insulinoma induces a hyperinsulinemia-mediated decrease of GLUT2 and GLP1 receptor in normal pancreatic β-cells

There have been several clinical reports of transient postoperative hyperglycemia in patients with insulinoma, but the effect of insulinoma on normal β-cells has not been investigated. We examined the glucose transporter 2 (GLUT2) and glucagon-like peptide 1 receptor (GLP1R) expression in normal pancreatic β-cells of five patients with insulinoma and five patients with normal glucose tolerance (NGT) as controls. The positive rate of GLUT2-or GLP1R-positive islets in the nontumor area was calculated by the ratio with the analyzed islets. For functional in vitro analyses, q-PCR and Western blotting were performed after insulin loading on MIN6 cells. The expression rates of both GLUT2 and GLP1R were significantly lower in nontumor area islets of insulinoma patients than in patients with NGT (GLUT2: 31.6 ± 15.3% vs 95.9 ± 6.7%, p < 0.01, GLP1R: 66.8 ± 15.0% vs 96.7 ± 5.0%, p < 0.01). Exposure of MIN6 cells to high concentrations of insulin resulted in a significant decrease in GLUT2 protein for 12 h and GLP1R protein for 24 h (GLUT2; 1.00 ± 0.079 vs 0.81 ± 0.04. p = 0.02, GLP1R; 1.00 ± 0.10 vs 0.50 ± 0.24, p = 0.03) but not in those mRNAs. Our findings show that insulinoma is associated with the downregulation of GLUT2 and GLP1R expression in nontumor area islets. These phenomena may be caused by high levels of insulin.

A Dipeptidyl Peptidase-4 Inhibitor Inhibits Foam Cell Formation of Macrophages in Type 1 Diabetes via Suppression of CD36 and ACAT-1 Expression

Dipeptidyl peptidase-4 (DPP-4) inhibitors have been reported to play a protective role against atherosclerosis in both animal models and patients with type 2 diabetes (T2D). However, since T2D is associated with dyslipidemia, hypertension and insulin resistance, part of which are ameliorated by DPP-4 inhibitors, it remains unclear whether DPP-4 inhibitors could have anti-atherosclerotic properties directly by attenuating the harmful effects of hyperglycemia. Therefore, we examined whether a DPP-4 inhibitor, teneligliptin, could suppress oxidized low-density lipoprotein (ox-LDL) uptake, foam cell formation, CD36 and acyl-coenzyme A: cholesterol acyltransferase-1 (ACAT-1) gene expression of macrophages isolated from streptozotocin-induced type 1 diabetes (T1D) mice and T1D patients as well as advanced glycation end product (AGE)-exposed mouse peritoneal macrophages and THP-1 cells. Foam cell formation, CD36 and ACAT-1 gene expression of macrophages derived from T1D mice or patients increased compared with those from non-diabetic controls, all of which were inhibited by 10 nmol/L teneligliptin. AGEs mimicked the effects of T1D; teneligliptin attenuated all the deleterious effects of AGEs in mouse macrophages and THP-1 cells. Our present findings suggest that teneligliptin may inhibit foam cell formation of macrophages in T1D via suppression of CD36 and ACAT-1 gene expression partly by attenuating the harmful effects of AGEs.

Association between 1,5-Anhydroglucitol and Acute C Peptide Response to Arginine among Patients with Type 2 Diabetes

OBJECTIVE

The aim of this study was to explore the association of 1,5-anhydroglucitol with acute C peptide response (ACPR) to arginine among patients with type 2 diabetes.

METHODS

Patients with type 2 diabetes were enrolled from the Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital. ACPR was assessed using arginine stimulation test. Decreased β-cell function was defined as ACPR < 2.1. Multivariable logistic regression models were used to demonstrate the association between 1,5-anhydroglucitol and decreased β-cell function.

RESULTS

Finally, 623 patients with type 2 diabetes were enrolled into the analysis. Multivariable-adjusted odds ratios for decreased β-cell function across quartiles of 1,5-anhydroglucitol were 1.00, 0.47 (95% confidence interval (CI) 0.23-0.99), 0.41 (95% CI 0.20-0.84), and 0.27 (95% CI 0.13-0.57) (P _trend = 0.042), respectively. When 1,5-anhydroglucitol was considered as a continuous variable after logarithm, the corresponding odds ratio was 0.40 (95% CI 0.23-0.71).

CONCLUSIONS

We demonstrated a dose-response linear association between 1,5-anhydroglucitol and ACPR. 1,5-Anhydroglucitol was likely to be associated with β-cell function. Further analysis with large sample size and prospective study design is warranted to validate our findings.