Features of glycemic variations in drug naïve type 2 diabetic patients with different HbA1c values

Patients with type 2 diabetes who achieve reduced postprandial glucose levels during insulin intensive therapy may have a better recovery of β-cell function

OBJECTIVES

To explore parameters that may determine the improvement in C-peptide levels in patients with type 2 diabetes (T2D) receiving continuous subcutaneous insulin infusion (CSII) therapy.

METHODS

The trial included a lead-in period for collecting baseline parameters and correcting hyperglycemia, a 4-day CGM period, and a 2-3 weeks treatment period. After screening, patients were hospitalized and randomized to the metformin add-on NovoRapid group or the Prandilin group. Once the glycemic target was reached, all patients underwent a 4-day CGM, with treatments maintained for 2-3 weeks. OGTTs were performed at baseline and endpoint. The primary endpoint was identifying factors contributing to better β-cell function recovery after CSII therapy.

RESULTS

A total of 99 recruited patients were admitted as inpatients and achieved glycemic control within 3.8 ± 1.1 days. Of these, 83 (84 %) patients showed improvement in C-peptide levels, while 16 (16 %) did not show any change in C-peptide levels at the endpoint. Pearson analysis showed a negative correlation between the incremental AUC of glucose concentration (from 0700 to 1000) and the increase in incremental AUC of C-peptide levels (r = -0.199, P < 0.05).

CONCLUSIONS

Drug-naïve T2D patients with lower postprandial glucose concentration during CSII therapy exhibit better β-cell function recovery.

Time in Range Estimation in Patients with Type 2 Diabetes is Improved by Incorporating Fasting and Postprandial Glucose Levels

INTRODUCTION

Time in range (TIR) as assessed by continuous glucose monitoring (CGM) measures an individual's glucose fluctuations within set limits in a time period and is increasingly used together with HbA1c in patients with diabetes. HbA1c indicates the average glucose concentration but provides no information on glucose fluctuation. However, before CGM becomes available for patients with type 2 diabetes (T2D) worldwide, especially in developing nations, fasting plasma glucose (FPG) and postprandial plasma glucose (PPG) are still the common biomarkers used for monitoring diabetes conditions. We investigated the importance of FPG and PPG to glucose fluctuation in patients with T2D. We used machine learning to provide a new estimate of TIR based on the HbA1c, together with FPG and PPG.

METHODS

This study included 399 patients with T2D. (1) Univariate and (2) multivariate linear regression models and (3) random forest regression models were developed to predict the TIR. Subgroup analysis was performed in the newly diagnosed T2D population to explore and optimize the prediction model for patients with different disease history.

RESULTS

Regression analysis suggests that FPG was strongly linked to minimum glucose, while PPG was strongly correlated with maximum glucose. After FPG and PPG were incorporated into the multivariate linear regression model, the prediction performance of TIR was improved compared with the univariate correlation between HbA1c and TIR, and the correlation coefficient (95% CI) increased from 0.62 (0.59, 0.65) to 0.73 (0.72, 0.75) (p < 0.001). The random forest model significantly outperformed the linear model (p < 0.001) in predicting TIR through FPG, PPG and HbA1c, with a stronger correlation coefficient 0.79 (0.79, 0.80).

CONCLUSIONS

The results offered a comprehensive understanding of glucose fluctuations through FPG and PPG compared to HbA1c alone. Our novel TIR prediction model based on random forest regression with FPG, PPG, and HbA1c provides a better prediction performance than the univariate model with solely HbA1c. The results indicate a nonlinear relationship between TIR and glycaemic parameters. Our results suggest that machine learning may have the potential to be used in developing better models for understanding patients' disease status and providing necessary interventions for glycaemic control.

Serum ErbB2 concentration positively correlated to the glycemic variations in newly diagnosed Type 2 diabetic patients

Evidences indicate that elevated levels of circulating ErbB2 are closely associated with increased incidence of diabetes. However, the relationship between ErbB2 concentration and glycemic variations (GV) in type 2 diabetic (T2D) patients remains elucidated. The aim of this study was to assess whether there is an association between serum ErbB2 concentration and GV in newly diagnosed T2D patients. This was a three-center, and observational study. Between April 2019 and July 2019, a total of 106 newly diagnosed T2D patients were recruited. All recruited subjects were admitted as inpatients and received anti-diabetes agents free during the study period. At baseline, fasting serum was collected for ErbB2 measurement and all recruited patients were subjected a prospective CGM for at least 3 days. The primary endpoint was the relationships between ErbB2 concentrations and GV in T2D patients. Data of a total of 95 subjects who met the inclusion criteria were analyzed at the endpoint. Subjects were divided into quartiles according to their serum ErbB2 concentrations. We observed that subjects with an elevated level of ErbB2 had a higher value of GV in terms of mean amplitude of glucose excursion (MAGE), standard deviation of mean glucose (SDMG), and the coefficient of variation (CV%) than those with lower levels (all P < 0.05). Multiple linear regression analyzes after adjusting for confounder factors indicate that serum ErbB2 levels were significantly positively correlated with the MAGE (β = 0.664, t = 7.218, P < 0.01), SD (β = 0.469, t = 5.125, P < 0.01) and CV% (β = 0.337, t = 4.442, P < 0.01), respectively. Our data indicated that diabetic patients with higher ErbB2 concentrations may have large GV, which is an independent risk factor for microvascular and macrovascular complications.

Starch digestibility modulation significantly improves glycemic variability in type 2 diabetic subjects: A pilot study

BACKGROUND AND AIMS

In type 2 diabetes (T2D) patients, the reduction of glycemic variability and postprandial glucose excursions is essential to limit diabetes complications, beyond HbA1c level. This study aimed at determining whether increasing the content of Slowly Digestible Starch (SDS) in T2D patients' diet could reduce postprandial hyperglycemia and glycemic variability compared with a conventional low-SDS diet.

METHODS AND RESULTS

For this randomized cross-over pilot study, 8 subjects with T2D consumed a controlled diet for one week, containing starchy products high or low in SDS. Glycemic variability parameters were evaluated using a Continuous Glucose Monitoring System. Glycemic variability was significantly lower during High-SDS diet compared to Low-SDS diet for MAGE (Mean Amplitude of Glycemic Excursions, p < 0.01), SD (Standard Deviation, p < 0.05), and CV (Coefficient of Variation, p < 0.01). The TIR (Time In Range) [140-180 mg/dL[ was significantly higher during High-SDS diet (p < 0.0001) whereas TIRs ≥180 mg/dL were significantly lower during High-SDS diet. Post-meals tAUC (total Area Under the Curve) were significantly lower during High-SDS diet.

CONCLUSION

One week of High-SDS Diet in T2D patients significantly improves glycemic variability and reduces postprandial glycemic excursions. Modulation of starch digestibility in the diet could be used as a simple nutritional tool in T2D patients to improve daily glycemic control. REGISTRATION NUMBER: in clinicaltrials.gov: NCT03289494.

Sexual Differences in response to Mid- or Low-Premixed Insulin Analogue in Patients with Type 2 Diabetes

OBJECTIVE

To observe whether there are sexual-related differences in response to mid- or low-premixed insulin in type 2 diabetic patients.

METHODS

This was an analysis of CGM data of a previous study. After screening, patients with longstanding T2D receive a 7-day continuous subcutaneous insulin infusion (CSII) therapy, and then subjects were randomly assigned 1 : 1 into two groups receiving Novo Mix 30 or Humalog Mix 50 regimen for a 2-day phage, followed by a 4-day cross-over period. A 4-day continuous glucose monitoring (CGM) was performed during the cross-over period. The primary endpoint was the differences in glycemic control between male and female patients receiving mid- or low-premixed insulin therapy.

RESULTS

A total of 102 patients (52 men and 50 women) completed the study. Our data showed that male patients had significant decrease in mean glucose levels monitored by CGM after three meals during Humalog Mix 50 treatment period compared to those received Novo Mix 30 regimen (0900: 11.0 ± 2.5 vs. 12.2 ± 2.8, 1000: 9.9 ± 2.9 vs. 11.3 ± 3.1, 1200: 8.0 ± 1.9 vs. 9.1 ± 2.5, 1400: 9.2 ± 2.3 vs. 10.3 ± 2.5, and 2000: 7.3 ± 2.1 vs. 8.2 ± 2.4 mmol/L, p < 0.05, respectively). In addition, male patients receiving Novo Mix 30 experienced a significantly increased hypoglycemic duration compared to those of receiving Humalog Mix 50 (0 (0, 4.8) vs. 0 (0, 0), p < 0.05, respectively). In addition, male patients receiving Novo Mix 30 experienced a significantly increased hypoglycemic duration compared to those of receiving Humalog Mix 50 (0 (0, 4.8) vs. 0 (0, 0).

CONCLUSION

Our data indicate that male patients with T2D receiving mid-premixed insulin analogue regimen may have a potential benefit of improvement in glycemic control compared to female patients. This trial is registered with ClinicalTrials.gov ChiCTR-IPR-15007340.

A View Beyond HbA1c: Role of Continuous Glucose Monitoring

Hemoglobin A1C (HbA1c) is used as an index of average blood glucose measurement over a period of months and is a mainstay of blood glucose monitoring. This metric is easy to measure and relatively inexpensive to obtain, and it predicts diabetes-related microvascular complications. However, HbA1c provides only an approximate measure of glucose control; it does not address short-term glycemic variability (GV) or hypoglycemic events. Continuous glucose monitoring (CGM) is a tool which helps clinicians and people with diabetes to overcome the limitations of HbA1c in diabetes management. Time spent in the glycemic target range and time spent in hypoglycemia are the main CGM metrics that provide a more personalized approach to diabetes management. Moreover, the glucose management indicator (GMI), which calculates an approximate HbA1c level based on the average CGM-driven glucose level, facilitates individual decision-making when the laboratory-measured HbA1c and estimated HbA1c are discordant. GV, on the other hand, is a measure of swings in blood glucose levels over hours or days and may contribute to diabetes-related complications. In addition, addressing GV is a major challenge during the optimization of glycemia. The degree of GV is associated with the frequency, duration, and severity of the hypoglycemic events. Many factors affect GV in a patient, including lifestyle, diet, the presence of comorbidities, and diabetes therapy. Recent evidence supports the use of some glucose-lowering agents to improve GV, such as the new ultra-long acting insulin analogs, as these agents have a smoother pharmacodynamic profile and improve glycemic control with fewer fluctuations and fewer nocturnal hypoglycemic events. These newer glucose-lowering agents (such as incretin hormones or sodium-glucose cotransporter 2 inhibitors) can also reduce the degree of GV. However, randomized trials are needed to evaluate the effect of GV on important diabetes outcomes. In this review, we discuss the role of HbA1c as a measure of glycemic control and its limitations. We also explore additional glycemic metrics, with a focus on time (duration) in glucose target range, time (duration) in hypoglycemia, GV, GMI, and their correlation with clinical outcomes.

Male Patients with Longstanding Type 2 Diabetes Have a Higher Incidence of Hypoglycemia Compared with Female Patients

INTRODUCTION

To explore whether there was a gender difference in the risk of hypoglycemia during intensive insulin therapy in patients with longstanding type 2 diabetes (T2D). This was a post hoc analysis of a single-center, open-label and prospective trial.

METHODS

All subjects were admitted as inpatients, underwent a standard bread meal test at baseline and received a 7-day continuous subcutaneous insulin infusion (CSII) therapy for achieving glycemic control. Patients then were randomized 1:1 to two groups receiving (1) 4 days of Novo Mix 30 followed by 2 days of Humalog Mix 50; (2) 4 days of Humalog Mix 50 followed by 2 days of Novo Mix 30. All patients were subjected to 4-day retrospective continuous glucose monitoring (CGM) during the last 4 days in this study. The primary outcome was the incidences of hypoglycemia monitored by CGM at the end point.

RESULTS

A total of 102 patients met the inclusion criteria and completed the study. Our data revealed that 29 patients (28%) experienced hypoglycemia as detected by CGM at the end point. Binary logistic stepwise regression analysis showed that only gender significantly correlated with hypoglycemia (B = 1.17, p = 0.017). Importantly, male patients had a significantly higher incidence of hypoglycemia than female patients (male = 20/52, female = 9/50, p = 0.022), although male patients required significantly lower insulin doses to maintain glycemic control than female patient (p = 0.00).

CONCLUSION

Male patients with longstanding T2D had a higher incidence of hypoglycemia than female patients during intensive insulin therapy.

TRIAL REGISTRATION

ClinicalTrials.gov identifier, ChiCTR-IPR-15007340.

Metformin add-on continuous subcutaneous insulin infusion on precise insulin doses in patients with type 2 diabetes

To investigate whether metformin add-on to the continuous subcutaneous insulin infusion (Met + CSII) therapy leads to a significant reduction in insulin doses required by type 2 diabetes (T2D) patients to maintain glycemic control, and an improvement in glycemic variation (GV) compared to CSII only therapy. We analyzed data from our two randomized, controlled open-label trials. Newly diagnoses T2D patients were randomized assigned to receive either CSII therapy or Met + CSII therapy for 4 weeks. Subjects were subjected to a 4-day continuous glucose monitoring (CGM) at the endpoint. Insulin doses and GV profiles were analyzed. The primary endpoint was differences in insulin doses and GV between the two groups. A total of 188 subjects were admitted as inpatients. Subjects in metformin add-on therapy required significantly lower total, basal and bolus insulin doses than those of control group. CGM data showed that patients in Met + CSII group exhibited significant reduction in the 24-hr mean amplitude of glycemic excursions (MAGE), the standard deviation, and the coefficient of variation compared to those of control group. Our data suggest that metformin add-on to CSII therapy leads to a significant reduction in insulin doses required by T2D patients to control glycemic variations.

Glycaemic variability-based classification of impaired glucose tolerance vs. type 2 diabetes using continuous glucose monitoring data

Many glycaemic variability (GV) indices extracted from continuous glucose monitoring systems data have been proposed for the characterisation of various aspects of glucose concentration profile dynamics in both healthy and non-healthy individuals. However, the inter-index correlations have made it difficult to reach a consensus regarding the best applications or a subset of indices for clinical scenarios, such as distinguishing subjects according to diabetes progression stage. Recently, a logistic regression-based method was used to address the basic problem of differentiating between healthy subjects and those affected by impaired glucose tolerance (IGT) or type 2 diabetes (T2D) in a pool of 25 GV-based indices. Whereas healthy subjects were classified accurately, the distinction between patients with IGT and T2D remained critical. In the present work, by using a dataset of CGM time-series collected in 62 subjects, we developed a polynomial-kernel support vector machine-based approach and demonstrated the ability to distinguish between subjects affected by IGT and T2D based on a pool of 37 GV indices complemented by four basic parameters-age, sex, BMI, and waist circumference-with an accuracy of 87.1%.

Relationship between Thyroid Function and Kidney Function in Patients with Type 2 Diabetes

PURPOSE

To determine if the TSH is related to estimated glomerular filtration rate (eGFR) in T2D patients without overt thyroid dysfunction.

METHODS

A cohort study of 5936 T2D patients was assessed for thyroid and kidney functions, in whom 248 with subclinical hyperthyroidism and 362 with subclinical hypothyroidism. Serum creatinine and 24-hour urine albumin excretion (UAE) were collected. Chronic kidney disease (CKD) was defined as eGFR < 60 ml/min/1.73 m².

RESULTS

Compared with euthyroid subjects, the patients with subclinical hypothyroidism had lower eGFR (82.7 ± 22.4 vs. 90.5 ± 22.4 ml/min/1.73 m², p < 0.01), higher UAE (114 ± 278 vs. 88 ± 229 mg/24 h, p < 0.05), and high incidence of CKD (16.0% vs. 10.1%, p < 0.05). The participants with a TSH level between 0.55 and 3.0 μIU/ml had a higher eGFR (91.4 ± 22.2 ml/min/1.73 m²) and a lower prevalence of CKD (9.5%) than those with higher TSH (3.01-4.78 μIU/ml, 85.6 ± 22.7 ml/min/1.73 m², p < 0.01 and 13.1%, p < 0.01). Linear logistic regression analysis showed that the eGFR was significantly negatively associated with TSH (OR: 0.519, 95% CI: 0.291-0.927, p < 0.05), after adjustment of confounders.

CONCLUSION

High TSH was independently associated with decreased eGFR in type 2 diabetes patients without overt thyroid dysfunction. Our findings indicate that doctors who treat T2D patients should routinely measure the thyroid function.

Young onset type 2 diabetic patients might be more sensitive to metformin compared to late onset type 2 diabetic patients

It is unknown whether YOD (young onset diabetes) and LOD (late onset diabetes) require similar insulin doses for intensive insulin therapy with a metformin add-on to achieve glycemic control. We analyzed data from our two previously performed randomized, controlled open-label trials. Patients were randomized to receive either continuous subcutaneous insulin infusion (CSII) therapy or CSII combined with metformin therapy for 4 weeks. The studies concentrated on the differences in the insulin doses used for the two groups. We included 36 YOD (age < 40 yrs) and 152 LOD (age > 40 yrs) patients. YOD patients who received metformin combined with CSII therapy required significantly lower insulin doses to maintain euglycemic control compared to patients with LOD. A multivariate analysis, controlled for gender and the fasting blood concentration, was performed to determine the significance of the differences between groups, particularly with respect to the total and basal insulin doses. There was a trend toward improvement in β-cell function and insulin resistance in terms of ΔHOMA-B and ΔHOMA-IR in patients with YOD compared to those with LOD. Newly diagnosed T2D patients with YOD required significantly lower insulin doses, particularly basal insulin doses, to maintain glycemic control compared to the LOD patients.

Effects of Vildagliptin Add-on Insulin Therapy on Nocturnal Glycemic Variations in Uncontrolled Type 2 Diabetes

INTRODUCTION

To investigate whether vildagliptin add-on insulin therapy improves glycemic variations in patients with uncontrolled type 2 diabetes (T2D) compared to patients with placebo therapy.

METHODS

This was a 24-week, single-center, double-blind, placebo-controlled trial. Inadequately controlled T2D patients treated with insulin therapy were recruited between June 2012 and April 2013. The trial included a 2-week screening period and a 24-week randomized period. Subjects were randomly assigned to a vildagliptin add-on insulin therapy group (n = 17) or a matched placebo group (n = 16). Scheduled visits occurred at weeks 4, 8, 12, 16, 20, and 24. Continuous glucose monitoring (CGM) was performed before and at the endpoint of the study.

RESULTS

A total of 33 subjects were admitted, with 1 patient withdrawing from the placebo group. After 24 weeks of therapy, HbA1c values were significantly reduced at the endpoint in the vildagliptin add-on group. CGM data showed that patients with vildagliptin add-on therapy had a significantly lower 24-h mean glucose concentration and mean amplitude of glycemic excursion (MAGE). At the endpoint of the study, patients in the vildagliptin add-on group had a significantly lower MAGE and standard deviation compared to the control patients during the nocturnal period (0000-0600). A severe hypoglycemic episode was not observed in either group.

CONCLUSION

Vildagliptin add-on therapy to insulin has the ability to improve glycemic variations, especially during the nocturnal time period, in patients with uncontrolled T2D.