Research progress on the association between glycemic variability index derived from CGM and cardiovascular disease complications

Currently, glycated hemoglobin A1c (HbA1c) has been widely used to assess the glycemic control of patients with diabetes. However, HbA1c has certain limitations in describing both short-term and long-term glycemic control. To more accurately evaluate the glycemic control of diabetes patients, the continuous glucose monitoring (CGM) technology has emerged. CGM technology can provide robust data on short-term glycemic control and introduce new monitoring parameters such as time in range, time above range, and time below range as indicators of glycemic fluctuation. These indicators are used to describe the changes in glycemic control after interventions in clinical research or treatment modifications in diabetes patient care. Recent studies both domestically and internationally have shown that these indicators are not only associated with microvascular complications of diabetes mellitus but also closely related to cardiovascular disease complications and prognosis. Therefore, this article aims to comprehensively review the association between CGM-based glycemic parameters and cardiovascular disease complications by analyzing a large number of domestic and international literature. The purpose is to provide scientific evidence and guidance for the standardized application of these indicators in clinical practice, in order to better evaluate the glycemic control of diabetes patients and prevent the occurrence of cardiovascular disease complications. This research will contribute to improving the quality of life for diabetes patients and provide important references for clinical decision-making.

The Health Economics of Automated Insulin Delivery Systems and the Potential Use of Time in Range in Diabetes Modeling: A Narrative Review

Intensive therapy with exogenous insulin is the treatment of choice for individuals living with type 1 diabetes (T1D) and some with type 2 diabetes, alongside regular glucose monitoring. The development of systems allowing (semi-)automated insulin delivery (AID), by connecting glucose sensors with insulin pumps and algorithms, has revolutionized insulin therapy. Indeed, AID systems have demonstrated a proven impact on overall glucose control, as indicated by effects on glycated hemoglobin (HbA1c), risk of severe hypoglycemia, and quality of life measures. An alternative endpoint for glucose control that has arisen from the use of sensor-based continuous glucose monitoring is the time in range (TIR) measure, which offers an indication of overall glucose control, while adding information on the quality of control with regard to blood glucose level stability. A review of literature on the health-economic value of AID systems was conducted, with a focus placed on the growing place of TIR as an endpoint in studies involving AID systems. Results showed that the majority of economic evaluations of AID systems focused on individuals with T1D and found AID systems to be cost-effective. Most studies incorporated HbA1c, rather than TIR, as a clinical endpoint to determine treatment effects on glucose control and subsequent quality-adjusted life year (QALY) gains. Likely reasons for the choice of HbA1c as the chosen endpoint is the use of this metric in most validated and established economic models, as well as the limited publicly available evidence on appropriate methodologies for TIR data incorporation within conventional economic evaluations. Future studies could include the novel TIR metric in health-economic evaluations as an additional measure of treatment effects and subsequent QALY gains, to facilitate a holistic representation of the impact of AID systems on glycemic control. This would provide decision makers with robust evidence to inform future recommendations for health care interventions.

Virtual reality's impact on children with type 1 diabetes: a proof-of-concept randomized cross-over trial on anxiety, pain, adherence, and glycemic control

AIMS

 Assess the effectiveness of virtual reality (VR) technology, in reducing pain and anxiety, and improving adherence and glycemic control among children with type 1 diabetes (T1D).

METHODS

Children with T1D, managed with continuous glucose monitoring and insulin pumps, were recruited for a randomized cross-over trial. Children were randomized to one of two interventions for diabetes management: group 1 used VR glasses first and group 2 listened to vocal-guided affective imagery first (audio). After 1 month, the interventions were crossed over. The outcome measures included pain and anxiety assessment, adherence, glycemic control, and patient-reported outcome measures (PROMs) of VR satisfaction and effectiveness.

RESULTS

 Forty children, mean age 11.4 ± 1.8 years, were participated. During the VR part, the monthly mean pain score compared to the baseline improved in both groups by 30% (p = 0.03). A 14% reduction in the state anxiety score was observed from baseline to 1 month in both groups (p = 0.009). Glycemic control measures including time in range, time above range, and glucose management indicator improved in both groups during VR part (p < 0.004 for all), compared to audio part. After one month, the patient-reported outcome measure (PROM) of satisfaction and effectiveness was sixfold higher after 1 month in group 1 compared to group 2 (p = 0.002). Adherence improved for both groups.

CONCLUSIONS

VR was shown to be effective in reducing pain and anxiety, improving adherence, PROM, and glycemic control among children with T1D. We suggest incorporating VR technology in pediatric diabetes clinics to facilitate and improve coping and management of diabetes.

TRIAL REGISTRATION

Trial registration number and date of registration for prospectively registered trials:ClinicalTrials.gov Identifier: NCT05883267, May 10th, 2023.

MiniMed 780G™ advanced hybrid closed-loop system performance in Egyptian patients with type 1 diabetes across different age groups: evidence from real-world users

BACKGROUND

Advanced hybrid closed loop (AHCL) system provides both automated basal rate and correction boluses to keep glycemic values in a target range.

OBJECTIVES

To evaluate the real-world performance of the MiniMed™ 780G system among different age groups of Egyptian patients with type 1diabetes.

METHODS

One-hundred seven AHCL system users aged from 3 to 71 years were enrolled. Data uploaded by patients were aggregated and analyzed. The mean glucose management indicator (GMI), percentage of time spent within glycemic ranges (TIR), time below range (TBR) and time above range (TAR) were determined.

RESULTS

Six months after initiating Auto Mode, patients spent a mean of 85.31 ± 22.04% of the time in Auto Mode (SmartGuard) and achieved a mean GMI of 6.95 ± 0.58% compared with 7.9 ± 2.1% before AHCL initiation (p < 0.001). TIR 70-180 mg/dL was increased post-AHCL initiation from 63.48 ± 10.14% to 81.54 ± 8.43% (p < 0.001) while TAR 180-250 mg/dL, TAR > 250 mg/dL, TBR < 70 mg/dL and TBR < 54 mg/dL were significantly decreased (p < 0.001). After initiating AHCL, TIR was greater in children and adults compared with adolescents (82.29 ± 7.22% and 83.86 ± 9.24% versus 78.4 ± 7.34%, respectively; p < 0.05). The total daily dose of insulin was increased in all age groups primarily due to increased system-initiated insulin delivery including auto correction boluses and basal insulin.

CONCLUSIONS

MiniMed™ 780G system users across different age groups achieved international consensus-recommended glycemic control with no serious adverse effects even in challenging age group as children and adolescents.

Relationship between key continuous glucose monitoring-derived metrics and specific cognitive domains in patients with type 2 diabetes mellitus

BACKGROUND

Continuous glucose monitoring (CGM)-derived time in range (TIR) is closely associated with micro- and macrovascular complications in type 2 diabetes mellitus (T2DM). This study was performed to investigate the relationship between key CGM-derived metrics and specific cognitive domains in patients with T2DM.

METHODS

Outpatients with T2DM who were otherwise healthy were recruited for this study. A battery of neuropsychological tests was performed to evaluate cognitive function, including memory, executive functioning, visuospatial ability, attention, and language. Participants wore a blinded flash continuous glucose monitoring (FGM) system for 72 h. The key FGM-derived metrics were calculated, including TIR, time below range (TBR), time above range (TAR), glucose coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE). Furthermore, the glycemia risk index (GRI) was also calculated by the GRI formula. Binary logistic regression was used to assess risk factors for TBR, and we further analysed the associations between neuropsychological test results and key FGM-derived metrics with multiple linear regressions.

RESULTS

A total of 96 outpatients with T2DM were recruited for this study, with 45.8% experiencing hypoglycemia (TBR^{< 3.9 mmol/L}). Spearman analysis results revealed that a higher TBR^{< 3.9 mmol/L} was correlated with worse performance on the Trail Making Test A (TMTA), Clock Drawing Test (CDT), and cued recall scores (P < 0.05). Logistic regression analysis results indicated that the TMTA (OR = 1.010, P = 0.036) and CDT (OR = 0.429, P = 0.016) scores were significant factors influencing the occurrence of TBR^{< 3.9 mmol/L}. Multiple linear regressions further demonstrated that TBR^{< 3.9 mmol/L} (β = -0.214, P = 0.033), TAR^{> 13.9 mmol/L} (β = -0.216, P = 0.030) and TAR^{10.1-13.9 mmol/L} (β = 0.206, P = 0.042) were significantly correlated with cued recall scores after adjusting for confounding factors. However, TIR, GRI, CV and MAGE showed no significant correlation with the results of neuropsychological tests (P > 0.05).

CONCLUSIONS

A higher TBR^{< 3.9 mmol/L} and TAR^{> 13.9 mmol/L} were associated with worse cognitive functions (memory, visuospatial ability, and executive functioning). Conversely, a higher TAR of 10.1-13.9 mmol/L was associated with better memory performance in memory tasks.

The relationship between glycosylated hemoglobin, time-in-range and glycemic variability in type 1 diabetes patients under flash glucose monitoring

OBJECTIVES

Flash glucose monitoring in patients with type 1 diabetes provides new glucometric data that allow for the assessment of glycemic control beyond HbA_1c. The objective of the study was to evaluate the relationship between HbA_1c, time-in-range (TIR) and glycemic variability in a cohort of paediatric and adult patients with type 1 diabetes and treatment with flash glucose monitoring.

MATERIAL AND METHODS

This was a cross-sectional study in 195 patients with type 1 diabetes (42.6% females, 70 paediatric, 26.2% continuous subcutaneous insulin infusion, 28.7% coefficient of variation [CV]≤36%) in intensive treatment and flash glucose monitoring. Clinical, analytical and glucometric data were evaluated.

RESULTS

The relationship between the TIR and HbA_1c showed a strong negative linear correlation (R=-0.746; R²=0.557; P<.001), modified in those patients with CV≤36% (R=-0.852; R²=0.836) compared to CV>36% (R=-0.703; R²=0.551). A similar correlation was found when evaluating the TIR and the Glucose Management Indicator (R=-0.846; R²=0.715; P<.001); in patients with CV≤36% (R=-0.980; R²=0.960) versus CV>36% (R=-0.837; R²=0.701); P<.001. Both correlations remained stable in the paediatric population (R=-0.724; R²=0.525; P<.001) and adults (R=-0.706; R²=0.498; P<.001) and by type of treatment: multiple doses of insulin (R=-0.747; R²=0.558; P<.001) and continuous subcutaneous insulin infusion (R=-0.711; R²=0.506; P<.001). In a multiple regression analysis evaluating HbA_1c as dependent variable, the only parameters that maintained statistical significance were the TIR (β=-0,031; P<.001), CV (β=0.843; P<.05) and TIR-CV interaction (β=-0.017; P<.01).

CONCLUSIONS

The glycemic variability defined by the CV modifies the relationship between the TIR and HbA_1c/Glucose Management Indicator and should be taken into account when individualising TIR targets, regardless of age or the type of treatment used.

Continuous Glucose Monitoring: A Review of Recent Studies Demonstrating Improved Glycemic Outcomes

Continuous Glucose Monitoring (CGM) has been demonstrated to be clinically valuable, reducing risks of hypoglycemia and hyperglycemia, glycemic variability (GV), and improving patient quality of life for a wide range of patient populations and clinical indications. Use of CGM can help reduce HbA1c and mean glucose. One CGM device, with accuracy (%MARD) of approximately 10%, has recently been approved for self-adjustment of insulin dosages (nonadjuvant use) and approved for reimbursement for therapeutic use in the United States. CGM had previously been used off-label for that purpose. CGM has been demonstrated to be clinically useful in both type 1 and type 2 diabetes for patients receiving a wide variety of treatment regimens. CGM is beneficial for people using either multiple daily injections (MDI) or continuous subcutaneous insulin infusion (CSII). CGM is used both in retrospective (professional, masked) and real-time (personal, unmasked) modes: both approaches can be beneficial. When CGM is used to suspend insulin infusion when hypoglycemia is detected until glucose returns to a safe level (low-glucose suspend), there are benefits beyond sensor-augmented pump (SAP), with greater reduction in the risk of hypoglycemia. Predictive low-glucose suspend provides greater benefits in this regard. Closed-loop control with insulin provides further improvement in quality of glycemic control. A hybrid closed-loop system has recently been approved by the U.S. FDA. Closed-loop control using both insulin and glucagon can reduce risk of hypoglycemia even more. CGM facilitates rigorous evaluation of new forms of therapy, characterizing pharmacodynamics, assessing frequency and severity of hypo- and hyperglycemia, and characterizing several aspects of GV.