Continuous glucose monitoring-derived time in range and CV are associated with altered tissue characteristics of the carotid artery wall in people with type 2 diabetes

Analysis glycemic variability in pregnant women with various type of hyperglycemia

OBJECTIVE

The study primarily aims to compare alterations in the daily patterns of glucose fluctuations across individuals with different kinds of diabetes in pregnancy and secondly investigate influencing factors that may react with glucose variations.

METHODS

We conducted a retrospective cohort study of 776 pregnant women in Shanghai General Hospital. We grouped participants who were exposed to gestational hyperglycemia into 5 sub-groups [Type 1 diabetes (T1DM), Type 2 diabetes (T2DM), Overt diabetes, Gestational diabetes (GDMA1 and GDMA2). Demographic variables and GV parameters were compared among 5 groups through ANOVA-test and Chi-square test. We estimated odd ratios (ORs) for the association between glucose coefficient of variation (CV) and possible influencing variables.

RESULTS

A final total of 776 pregnant women were analyzed. The proportion of pregnant women with pre-gestational diabetes was 31.83% (T1DM: 3.35%,T2DM: 28.48%), ODM 26.68%, and GDM was 41.49% (GDMA1:18.04%, GDMA2: 23.45%). T1DM group performed greatest glucose fluctuations with a CV value 35.02% whereas the number in all the other groups was no more than 22.82% (ODM group). In terms of achieving glycemic control target, only 57.70% participants hit the goal while all the other groups achieved the standard with at least a percentage of 94.20% (ODM group). Other parameters (GMI < 6.0%, GA < 15.70% and HbA1c < 6.0%) showed similar trends in each group. On multivariate logistic regression analysis of possible factors influencing CV, only body mass index (BMI) (OR: 0.754, 95% CI: 0.585-0.971; P = 0.029), HOMA- β (OR:0.969, 95%CI: 0.959-0.976; P = 0.037) and fasting plasma glucose (FPG) (OR: 1.832, 95% CI: 1.170-2.870; P = 0.008) reached statistical significance.

CONCLUSIONS

Pregnant women with type 1 or type 2 diabetes exhibit significantly greater glycemic variability compared to those with gestational diabetes, with the ODM group showing intermediate variability, and BMI, HOMA-β, and FPG identified as independent risk factors for unstable glucose variability.

Effects of switching from dipeptidyl peptidase 4 inhibitors to oral semaglutide on oxidative stress and glycemic variability in patients with type 2 diabetes: an open-label, prospective, randomized, multicenter, parallel-group comparison study

BACKGROUND

To compare the effects of switching from dipeptidyl peptidase 4 (DPP-4) inhibitors to oral semaglutide on oxidative stress and glucose variability assessed by continuous glucose monitoring in patients with type 2 diabetes mellitus (T2DM).

METHODS

This was an open-label, prospective, randomized, multicenter, parallel-group comparison study conducted over 24 weeks. Patients with T2DM who had been taking regular doses of DPP-4 inhibitors for at least 12 weeks were enrolled. They were randomly assigned to either continue on DPP-4 inhibitors (DPP-4 inhibitor group) or switch to oral semaglutide at 3 mg/day, with a dose increase to 7 mg/day after 4 weeks (semaglutide group). The primary endpoint was the change in the diacron-reactive oxygen metabolites test, an oxidative stress marker. Secondary endpoints included changes in glucose variability assessed using continuous glucose monitoring, metabolic indices, physical assessments, and Diabetes Treatment Satisfaction Questionnaire scores.

RESULTS

Fifty-eight patients with T2DM were randomized to the semaglutide group (n = 30) and the DPP-4 inhibitor group (n = 28). Six patients in the semaglutide group and one patient in the DPP-4 inhibitor group dropped out during the study. Ultimately, data from 24 patients in the semaglutide group and 27 patients in the DPP-4 inhibitor group were included for analysis. Switching to oral semaglutide therapy for 24 weeks significantly reduced oxidative stress, glucose variability, and hemoglobin A1c levels compared to continuous treatment with DPP-4 inhibitors. However, there was no significant difference in Diabetes Treatment Satisfaction Questionnaire scores between the two groups.

(II) CONCLUSIONS

Our study demonstrated that switching to oral semaglutide therapy from DPP-4 inhibitors significantly improved oxidative stress and glycemic parameters, including glucose variability, in patients with T2DM.

TRIAL REGISTRATION

jRCT1031210620.

Closed-Loop Insulin Therapy for People With Type 2 Diabetes Treated With an Insulin Pump: A 12-Week Multicenter, Open-Label Randomized, Controlled, Crossover Trial

OBJECTIVE

Continuous glucose monitoring (CGM) combined with continuous subcutaneous insulin infusion (CSII) achieves better glycemic control than multi-injection therapy in people with type 2 diabetes. The effectiveness of closed-loop therapy needs to be further evaluated in this population.

RESEARCH DESIGN AND METHODS

The study objective was to measure the impact of a hybrid closed-loop device (DBLG1) compared with CSII + CGM on glycemic control in people with type 2 diabetes previously treated with CSII. The randomized, controlled, crossover, two-period, open-label, and multicenter study was conducted from August 2022 to July 2023 in 17 individuals (9 to receive 6 weeks of CSII + CGM first and 8 to receive 6 weeks of closed-loop therapy first). The primary end point was the percentage time in range (TIR: 70-180 mg/dL). Secondary outcomes were other CGM-glucose metrics, physical activity, and sleep objectively measured using 1-week actimetry.

RESULTS

Data were analyzed using a modified intention-to-treat approach. Mean age was 63 (SD 9) years and 35% were women. Mean HbA1c at inclusion was 7.9% (SD 0.9). TIR increased to 76.0% (interquartile range 69.0-84.0) during the closed-loop condition vs. 61.0% (interquartile range 55.0-70.0) during the CSII + CGM condition; mean difference was 15.0 percentage points (interquartile range 8.0-22.0; P < 0.001). Analyses of secondary end points showed a decrease in time above range, in glucose management indicator, in glucose variability, and an increase in daily insulin dose. Actimetric sleep analysis showed an improvement in sleep fragmentation during closed-loop treatment.

CONCLUSIONS

Closed-loop therapy improved glycemic control more than did CSII + CGM in people with type 2 diabetes.

Potential Benefits of Continuous Glucose Monitoring for Predicting Vascular Outcomes in Type 2 Diabetes: A Rapid Review of Primary Research

(1) Background: Chronic hyperglycaemia is a cause of vascular damage and other adverse clinical outcomes in type 2 diabetes mellitus (T2DM). Emerging evidence suggests a significant and independent role for glycaemic variability (GV) in contributing to those outcomes. Continuous glucose monitoring (CGM) provides valuable insights into GV. Unlike in type 1 diabetes mellitus, the use of CGM-derived GV indices has not been widely adopted in the management of T2DM due to the limited evidence of their effectiveness in predicting clinical outcomes. This study aimed to explore the associations between GV metrics and short- or long-term vascular and clinical complications in T2DM. (2) Methods: A rapid literature review was conducted using the Cochrane Library, MEDLINE, and Scopus databases to seek high-level evidence. Lower-quality studies such as cross-sectional studies were excluded, but their content was reviewed. (3) Results: Six studies (five prospective cohort studies and one clinical trial) reported associations between GV indices (coefficient of variation (CV), standard deviation (SD), Mean Amplitude of Glycaemic Excursions (MAGE), Time in Range (TIR), Time Above Range (TAR), and Time Below Range (TBR)), and clinical complications. However, since most evidence came from moderate to low-quality studies, the results should be interpreted with caution. (4) Conclusions: Limited but significant evidence suggests that GV indices may predict clinical compilations in T2DM both in the short term and long term. There is a need for longitudinal studies in larger and more diverse populations, longer follow-ups, and the use of numerous CGM-derived GV indices while collecting information about all microvascular and macrovascular complications.

Association between glycemia risk index and arterial stiffness in type 2 diabetes

AIM

This study aims to investigate the association of glycemia risk index (GRI), a novel composite metric derived from continuous glucose monitoring (CGM), with arterial stiffness in patients with type 2 diabetes.

MATERIALS AND METHODS

A total of 342 adults with type 2 diabetes were enrolled between April and June 2023 from 11 communities in Shanghai, China. Medical examinations, including measurements of anthropometric parameters, blood pressure, and venous blood samples were conducted. Brachial-ankle pulse wave velocity (baPWV) was examined to evaluate arterial stiffness. All the participants underwent a 14 day CGM recording and GRI was calculated from the CGM data.

RESULTS

The mean age was 70.3 ± 6.8 years, and 162 (47.4%) were male. Participants with a higher baPWV had significantly higher levels of GRI and hyperglycemia component (both P for trend < 0.05). Linear regression revealed the significant positive linear associations of the GRI with baPWV in unadjusted or adjusted models (All P < 0.05). In the multivariable logistic analysis, each increase in the GRI quartile was associated with a 1.30-fold (95% CI 1.01-1.68, P for trend < 0.05) higher prevalence of increased arterial stiffness after adjustment for age, sex, BMI, diabetes duration, current smoking status, blood pressure, and lipid profile. Subgroup analyses showed that the association between the GRI quartiles and increased arterial stiffness was stronger among participants with a diabetes duration ≥15 years (P for interaction = 0.014).

CONCLUSION

Glycemia risk index assessed by continuous glucose monitoring is associated with increased arterial stiffness in type 2 diabetes.

Glycemic variability: Measurement, target, impact on complications of diabetes and does it really matter?

Over the past two decades, there has been continuous advancement in the accuracy and complexity of continuous glucose monitoring devices. Continuous glucose monitoring provides valuable insights into blood glucose dynamics, and can record glucose fluctuations accurately and completely. Glycemic variability (GV) is a straightforward measure of the extent to which a patient's blood glucose levels fluctuate between high peaks and low nadirs. Many studies have investigated the relationship between GV and complications, primarily in the context of type 2 diabetes. Nevertheless, the exact contribution of GV to the development of diabetes complications remains unclear. In this literature review, we aimed to summarize the existing evidence regarding the measurement, target level, pathophysiological mechanisms relating GV and tissue damage, and population-based studies of GV and diabetes complications. Additionally, we introduce novel methods for measuring GV, and discuss several unresolved issues of GV. In the future, more longitudinal studies and trials are required to confirm the exact role of GV in the development of diabetes complications.