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

Associations between time in range and insulin secretory capacity in Japanese patients with type 2 diabetes

Impaired insulin secretory capacity is associated with high glycemic variability in patients with type 2 diabetes (T2DM). However, there are no existing reports on the association between insulin secretory capacity and time in range (TIR). This retrospective study involved 330 T2DM admitted for diabetes education who underwent intermittently scanned continuous glucose monitoring (isCGM) and had their fasting serum C-peptide immunoreactivity (S-CPR) measured within 5 days of admission. The baseline characteristics were as follows: age, 60.2 years; glycated hemoglobin (HbA1c), 9.2%; S-CPR, 2.2 ng/mL; S-CPR index (S-CPR [ng/mL]/fasting plasma glucose [mg/dL] × 100), 1.6; and TIR, 60.3%. TIR correlated significantly with the S-CPR index, which was confirmed by multivariate analysis that included various factors such as HbA1c. Receiver operating characteristic (ROC) analysis showed that 1.88 was the optimal S-CPR index level to predict TIR ≥ 70%. In addition to HbA1c and biguanide use, the S-CPR index was a significant factor associated with TIR > 70%. S-CPR index values of ≥ 1.88 also correlated significantly with TIR > 70%. In conclusion, insulin secretory capacity is associated with TIR in Japanese T2DM, suggesting that the S-CPR index might be a potentially useful biomarker insulin secretory capacity, in association with TIR.Trial registration UMIN0000254333.

An in-silico modeling approach to separate exogenous and endogenous plasma insulin appearance, with application to inhaled insulin

The aim of this study was to develop a dynamic model-based approach to separately quantify the exogenous and endogenous contributions to total plasma insulin concentration and to apply it to assess the effects of inhaled-insulin administration on endogenous insulin secretion during a meal test. A three-step dynamic in-silico modeling approach was developed to estimate the two insulin contributions of total plasma insulin in a group of 21 healthy subjects who underwent two equivalent standardized meal tests on separate days, one of which preceded by inhalation of a Technosphere® Insulin dose (22U or 20U). In the 30-120 min test interval, the calculated endogenous insulin component showed a divergence in the time course between the test with and without inhaled insulin. Moreover, the supra-basal area-under-the-curve of endogenous insulin in the test with inhaled insulin was significantly lower than that in the test without (2.1 ± 1.7 × 104 pmol·min/L vs 4.2 ± 1.8 × 104 pmol·min/L, p < 0.01). The percentage of exogenous insulin reaching the plasma, relative to the inhaled dose, was 42 ± 21%. The proposed in-silico approach separates exogenous and endogenous insulin contributions to total plasma insulin, provides individual bioavailability estimates, and can be used to assess the effect of inhaled insulin on endogenous insulin secretion during a meal.

Positive association between the proinsulin-to-C-peptide ratio and prolonged hyperglycemic time in type 2 diabetes

The proinsulin-to-C-peptide (PI:C) ratio is an index applied during the early stage of pancreatic β-cell dysfunction. The aim of this study was to identify the characteristics associated with the PI:C ratio to discuss pancreatic β-cell dysfunction progression during the natural course of type 2 diabetes and its relationship with glycemic management. This multicenter, prospective observational study included 272 outpatients with type 2 diabetes. Continuous glucose monitoring was performed and fasting blood samples were collected and analyzed. We identified the clinical factors associated with the PI:C ratio by multiple regression analysis. The mean age of the cohort was 68.0 years, mean hemoglobin A1c 7.1% (54 mmol/mol), and mean body mass index 24.9 kg/m2. Multiple regression analysis showed that a prolonged time above the target glucose range (>180 mg/dL) and high body mass index contributed to a high PI:C ratio. However, no associations were found between the PI:C ratio and glucose variability indices. These findings suggested that the PI:C ratio is positively associated with a prolonged hyperglycemic time in type 2 diabetes, whereas its relationship with glucose variability remains unclear.

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.

Analysis of detrended fluctuation function derived from continuous glucose monitoring may assist in distinguishing latent autoimmune diabetes in adults from T2DM

BACKGROUND

We aimed to explore the performance of detrended fluctuation function (DFF) in distinguishing patients with latent autoimmune diabetes in adults (LADA) from type 2 diabetes mellitus (T2DM) with glucose data derived from continuous glucose monitoring.

METHODS

In total, 71 LADA and 152 T2DM patients were enrolled. Correlations between glucose parameters including time in range (TIR), mean glucose, standard deviation (SD), mean amplitude of glucose excursions (MAGE), coefficient of variation (CV), DFF and fasting and 2-hour postprandial C-peptide (FCP, 2hCP) were analyzed and compared. Receiver operating characteristics curve (ROC) analysis and 10-fold cross-validation were employed to explore and validate the performance of DFF in diabetes classification respectively.

RESULTS

Patients with LADA had a higher mean glucose, lower TIR, greater SD, MAGE and CV than those of T2DM (P<0.001). DFF achieved the strongest correlation with FCP (r = -0.705, P<0.001) as compared with TIR (r = 0.485, P<0.001), mean glucose (r = -0.337, P<0.001), SD (r = -0.645, P<0.001), MAGE (r = -0.663, P<0.001) and CV (r = -0.639, P<0.001). ROC analysis showed that DFF yielded the greatest area under the curve (AUC) of 0.862 (sensitivity: 71.2%, specificity: 84.9%) in differentiating LADA from T2DM as compared with TIR, mean glucose, SD, MAGE and CV (AUC: 0.722, 0.650, 0.800, 0.820 and 0.807, sensitivity: 71.8%, 47.9%, 63.6%, 72.7% and 78.8%, specificity: 67.8%, 83.6%, 80.9%, 80.3% and 72.4%, respectively). The kappa test indicated a good consistency between DFF and the actual diagnosis (kappa = 0.551, P<0.001). Ten-fold cross-validation showed a stable performance of DFF with a mean AUC of 0.863 (sensitivity: 78.8%, specificity: 77.8%) in 10 training sets and a mean AUC of 0.866 (sensitivity: 80.9%, specificity: 84.1%) in 10 test sets.

CONCLUSIONS

A more violent glucose fluctuation pattern was marked in patients with LADA than T2DM. We first proposed the possible role of DFF in distinguishing patients with LADA from T2DM in our study population, which may assist in diabetes classification.