Association of Time in Range, as Assessed by Continuous Glucose Monitoring, With Diabetic Retinopathy in Type 2 Diabetes

Associations between acute glucose control and peripheral nerve structure and function in type 1 diabetes

AIM

To examine the associations between continuous overlapping net glycaemic action (CONGA), percentage time in hyperglycaemia (%HG) or normoglycaemia (%NG) and peripheral nerve structure and function in type 1 diabetes.

METHODS

Twenty-seven participants with type 1 diabetes underwent continuous glucose monitoring followed by corneal confocal microscopy and nerve excitability assessments. CONGA, %HG (> 10.0 mmol/l) and %NG (3.9-10.0 mmol/l) were correlated against corneal nerve fibre length and density in the central cornea and inferior whorl region, corneal microneuromas, and a nerve excitability score while controlling for age, sex, diabetes duration and HbA_1c .

RESULTS

An increase in CONGA [median 2.5 (2.0-3.1) mmol/l] or %HG (mean 46 ± 18%) was associated with a worse nerve excitability score (r = -0.433, P = 0.036 and r = -0.670, P = 0.0012, respectively). By contrast, greater %NG (51 ± 17%) correlated with better nerve excitability scores (r = 0.672, P = 0.0011). Logistic regression revealed that increasing %HG increased the likelihood of abnormal nerve function [odds ratio (OR) 1.11, 95% confidence interval (CI) 1.01-1.23; P = 0.037). An increase in CONGA and %HG were associated with worsening nerve conduction measures, whereas longer %NG correlated with improved nerve conduction variables. CONGA and %HG were associated with inferior whorl corneal nerve fibre length (r = 0.483, P = 0.034 and r = 0.591, P = 0.021, respectively) and number of microneuromas (r = 0.433, P = 0.047 and r = 0.516, P = 0.020, respectively).

CONCLUSIONS

Short-term measures of glucose control are associated with impaired nerve function and alterations in corneal nerve morphology.

Efficacy and safety of evogliptin treatment in patients with type 2 diabetes: A multicentre, active-controlled, randomized, double-blind study with open-label extension (the EVERGREEN study)

AIM

To investigate the efficacy and safety of evogliptin compared with linagliptin in patients with type 2 diabetes.

MATERIALS AND METHODS

In this 12-week, multicentre, randomized, double-blind, active-controlled, and 12-week open-label extension study, a total of 207 patients with type 2 diabetes who had HbA1c levels of 7.0%-10.0% were randomized 1:1 to receive evogliptin 5 mg (n = 102) or linagliptin 5 mg (n = 105) daily for 12 weeks. The primary efficacy endpoint was the change from baseline HbA1c at week 12. The secondary endpoint was the change in the mean amplitude of glycaemic excursion (MAGE) assessed by continuous glucose monitoring. In the extension study conducted during the following 12 weeks, evogliptin 5 mg daily was administered to both groups: evogliptin/evogliptin group (n = 95) and linagliptin/evogliptin group (n = 92).

RESULTS

After 12 weeks of treatment, the mean change in HbA1c in the evogliptin group and in the linagliptin group was -0.85% and -0.75%, respectively. The between-group difference was -0.10% (95% CI: -0.32 to 0.11), showing non-inferiority based on a non-inferiority margin of 0.4%. The change in MAGE was -24.6 mg/dL in the evogliptin group and -16.7 mg/dL in the linagliptin group. These values were significantly lower than the baseline values in both groups. However, they did not differ significantly between the two groups. In the evogliptin/evogliptin group at week 24, HbA1c decreased by -0.94%, with HbA1c values of <7.0% in 80.2% of the patients. The incidence and types of adverse events were comparable between the two groups for 24 weeks.

CONCLUSION

In this study, the glucose-lowering efficacy of evogliptin was non-inferior to linagliptin. It was maintained at week 24 with a 0.94% reduction in HbA1c. Evogliptin therapy improved glycaemic variability without causing any serious adverse events in patients with type 2 diabetes.

Critical Reappraisal of the Time-in-Range: Alternative or Useful Addition to Glycated Hemoglobin?

The HbA1c value is a well-established parameter used to characterize glucose control. Continuous glucose monitoring (CGM)-derived parameters calculated using daily glucose profiles such as Time-in-Range (TiR) have increasingly been gaining interest for assessing a patient's current therapy. The question has arisen as to whether TiR could replace HbA1c? Because TiR focuses on the current quality of glucose control during a minimum of 10 to 14 days of CGM use and reflects the variability of glucose concentrations. Time-in-Range could be considered an attractive option for improving diabetes control in patients with diabetes. Due to the lack of established standards for glucose measurements with CGM systems, results from different CGM systems can deviate from each other. Time-in-Range should not be viewed as a replacement for HbA1c, but should be used to deliver valuable additional information.

The clinical effects of a carbohydrate-reduced high-protein diet on glycaemic variability in metformin-treated patients with type 2 diabetes mellitus: A randomised controlled study

BACKGROUND & AIMS

High glycaemic variability (GV) is associated with late complications in type 2 diabetes (T2D). We hypothesised that a carbohydrate-reduced high-protein (CRHP) diet would reduce GV acutely in patients with T2D compared with a conventional diabetes (CD) diet.

METHODS

In this controlled, randomised crossover study, 16 patients with metformin-treated T2D (median (IQR) age: 64.0 (58.8-68.0) years; HbA_1c: 47 (43-57) mmol/mol; duration of T2D: 5.5 (2.8-10.3) years) were assigned to an energy-matched CRHP diet and CD diet (31E%/54E% carbohydrate, 29E%/16E% protein and 40E%/30E% fat, respectively) for two separate 48-h intervention periods. Interstitial continuous glucose monitoring (CGM) was performed to assess accepted measures of glycaemic variability, i.e. standard deviation (SD) around the sensor glucose level; coefficient of variation in percent (CV); mean amplitude of glucose excursions (MAGE); continuous overlapping net glycaemic action (CONGA₁, CONGA₄) of observations 1 and 4 h apart; and mean absolute glucose (MAG) change.

RESULTS

All indices of glycaemic variability (mean ± SD) were significantly reduced during CRHP diet compared with CD diet; including SD (1.0 ± 0.3 (CRHP) vs 1.6 ± 0.5 mmol/L (CD)), CV (12.3 ± 3.8 vs 19.3 ± 5.5%), MAGE (2.3 ± 0.9 vs 4.2 ± 1.3 mmol/L), CONGA₁ (0.8 ± 0.3 vs 1.5 ± 0.4 mmol/L), CONGA₄ (1.4 ± 0.5 vs 2.5 ± 0.8 mmol/L), and MAG change (0.9 ± 0.3 vs 1.4 ± 0.4 mmol/L/h) (p < 0.001 for all). Compared with the CD diet, the CRHP diet improved the diurnal glucose profile by reducing 24-h mean sensor glucose (7.7 ± 1.6 vs 8.6 ± 2.0 mmol/L).

CONCLUSIONS

In T2D patients treated with diet and metformin, two days of iso-energetic replacement of dietary carbohydrates by protein and fat reduced all indices of glycaemic variability by 36%-45% when compared with a conventional diabetes diet. These data may support reduction of carbohydrates as dietary advice for T2D patients. CLINICALTRIALS.

GOV IDENTIFIER

NCT02472951.

Progression of Diabetic Complications in Subgroups of People with Long Term Diabetes Type 1 According to Clinical Course

AIMS

Prevention and prediction of microvascular complications are important aims of medical care in people with type 1 diabetes. Since the course of the disease is heterogenous, we tried to identify subgroups with specific risk profiles for microvascular complications.

METHODS

Retrospective analysis of a cohort of 285 people (22637 consultations) with >10 years of type 1 diabetes. Persons were grouped into slow (<15 years), fast (>15 years) and non progressors according to the average onset of microvascular complications. Generalized estimating equations for binary outcomes were applied and pseudo coefficients of determination were calculated.

RESULTS

Progression to microvascular disease was associated with age (OR: 1.034 [1.001-1.068]; p=0.04), diabetes duration (OR: 1.057 [1.021-1.094]; p=0.002), HbA_1c (OR: 1.035 [1.011-1.060]; p=0.005), BMI (OR: 0.928 [0.866-0.994]; p=0.034) and the social strata index (OR: 0.910 [0.830-0.998]; p=0.046). Generalized estimating equations predicted 31.02% and exclusion of HbA_1c marginally reduced the value to 28.88%. The proportion of patients with LADA was higher in fast than slow progressors [13 (26.5%) vs. 14 (11.9%); p=0.019]. A generalized estimating equation comparing slow to fast progressors revealed no significant markers.

CONCLUSION

In our analysis, we were able to confirm known risk factors for microvascular disease in people with type 1 diabetes. Overall, prediction of individual risk was difficult, the effect of individual markers minor and we could not find differences regarding slow or fast progression. We therefore emphasis the need for additional markers to predict individual risk for microvascular disease.

The dawn phenomenon across the glycemic continuum: Implications for defining dysglycemia

AIMS

To investigate the frequency of dawn phenomenon (DP) and its relationship with time in range (TIR) and glycemic variability (GV) using continuous glucose monitoring (CGM).

METHODS

781 subjects of a multicenter CGM study in China were included: those with normal glucose tolerance (NGT n = 360); impaired glucose regulation (IGR n = 173); newly diagnosed type 2 diabetes mellitus (T2D n = 248). Analysis of the magnitude of DP (ΔG) was conducted with the primary definition of 1.11 mmol/L and a secondary definition of 0.56 mmol/L.

RESULTS

The frequency of DP was 8.9%, 30.1% and 52.4% in NGT, IGR and T2D group, respectively, using the primary definition. In all three groups, TIR was lower (all P < 0.05), coefficient of variation (CV) was higher in DP subgroup (all P < 0.05). In DP subgroup of T2D, TIR was 7.0% (1.68 h) lower and CV was 3.0% higher, and HbA_1c was 0.6% (7 mmol/mol) higher using the primary definition (all P < 0.05).

CONCLUSIONS

DP was present in a high percent of subjects with NGT and IGR. In newly diagnosed T2D group, the presence of DP was associated with poorer overall glycemic control.

TIR generated by continuous glucose monitoring is associated with peripheral nerve function in type 2 diabetes

AIMS

Continuous glucose monitoring (CGM)-derived time-in-range (TIR) of 3.9-10 mmol/L is associated with diabetic retinopathy in type 2 diabetes (T2DM), but its relationship to peripheral nerve function has not been previously investigated. To explore the association between the TIR and nerve conduction study parameters in patients with T2DM, we performed a cross-sectional analysis.

METHODS

A total of 740 patients with T2DM were enrolled in this study. All of the participants were divided into tertiles according to the TIR (TIR low: ≤53%; TIR medium: 54-76%; TIR high: ≥77%). Composite Z-scores of nerve conduction velocity (CV), latency, and amplitude were calculated. The linear correlation between the TIR and composite nerve function Z-score was evaluated and risk assessment was analysed using binary logistic regression.

RESULTS

The composite Z-score of the CV and amplitude increased with higher TIR and the composite Z-score of latency significantly decreased as the TIR tertiles increased (all P trend < 0.05). After adjusting for age, diabetes duration, height, weight and other confounding factors, higher TIR was associated with a higher composite Z-score of CV (β = 0.230, P < 0.001), amplitude (β = 0.099, P = 0.010), and lower composite Z-score of latency (β = -0.172, P < 0.001). The risk of TIR tertiles and low composite Z-score of CV remained significant even after adjustment of HbA1c (TIR medium: OR = 0.48, P = 0.001; TIR high: OR = 0.41, P < 0.001).

CONCLUSIONS

Higher TIR tertiles were independently associated with better peripheral nerve function. CGM-derived TIR may be a promising approach to screen patients for further assessment of possible diabetic peripheral neuropathy.

A Review of Continuous Glucose Monitoring-Based Composite Metrics for Glycemic Control

We performed a literature review of composite metrics for describing the quality of glycemic control, as measured by continuous glucose monitors (CGMs). Nine composite metrics that describe CGM data were identified. They are described in detail along with their advantages and disadvantages. The primary benefit to using composite metrics in clinical practice is to be able to quickly evaluate a patient's glycemic control in the form of a single number that accounts for multiple dimensions of glycemic control. Very little data exist about (1) how to select the optimal components of composite metrics for CGM; (2) how to best score individual components of composite metrics; and (3) how to correlate composite metric scores with empiric outcomes. Nevertheless, composite metrics are an attractive type of scoring system to present clinicians with a single number that accounts for many dimensions of their patients' glycemia. If a busy health care professional is looking for a single-number summary statistic to describe glucose levels monitored by a CGM, then a composite metric has many attractive features.

Continuous Glucose Monitoring of Glycemic Variability During Fasting Post-Sleeve Gastrectomy

INTRODUCTION

Day-long fasting creates considerable metabolic stress that poses challenges in people with diabetes and those who have undergone bariatric surgery. Clinical knowledge of glucose fluctuations and the risks for such patients during fasting is limited.

OBJECTIVES

This study examined the effect of intermittent fasting on glucose excursions, hypoglycemia, and hyperglycemia in people with or without diabetes who had sleeve gastrectomy compared with healthy individuals.

METHODS

This open-label, prospective study compared interstitial glucose profiles measured with continuous glucose monitoring system for 72 h during fasting and non-fasting periods between four groups comprising 15 participants each: people with obesity and medicine-treated type 2 diabetes (T2D) only, obesity and T2D treated with sleeve gastrectomy, obesity without T2D treated with sleeve gastrectomy, and healthy, normal-weight non-diabetic controls.

RESULTS

The mean 72-h glucose concentration was significantly lower during the fasting period for all groups (p ≤ 0.041), with the highest glucose concentrations in the medicine-treated T2D-only group and the lowest concentrations in the sleeve gastrectomy in non-T2D group. The mean glucose profiles of all the groups showed a marked increase in interstitial glucose on breaking the fast, which was exaggerated in the two diabetes groups. The mean amplitude of glycemic excursions did not differ significantly within each group between fasting and non-fasting. No significant difference was noted in the fraction of time in the hypoglycemic range between the fasting and non-fasting periods in any group.

CONCLUSION

Intermittent fasting had no adverse effect on glycemic control in people with or without diabetes who had undergone sleeve gastrectomy.

Glycemic variability: adverse clinical outcomes and how to improve it?

Glycemic variability (GV), defined as an integral component of glucose homoeostasis, is emerging as an important metric to consider when assessing glycemic control in clinical practice. Although it remains yet no consensus, accumulating evidence has suggested that GV, representing either short-term (with-day and between-day variability) or long-term GV, was associated with an increased risk of diabetic macrovascular and microvascular complications, hypoglycemia, mortality rates and other adverse clinical outcomes. In this review, we summarize the adverse clinical outcomes of GV and discuss the beneficial measures, including continuous glucose monitoring, drugs, dietary interventions and exercise training, to improve it, aiming at better addressing the challenging aspect of blood glucose management.

Efficacy and safety of dual add-on therapy with dapagliflozin plus saxagliptin versus glimepiride in patients with poorly controlled type 2 diabetes on a stable dose of metformin: Results from a 52-week, randomized, active-controlled trial

AIMS

To evaluate the efficacy and safety of dapagliflozin (DAPA) + saxagliptin (SAXA) compared with glimepiride (GLIM) in patients with type 2 diabetes who were inadequately controlled [glycated haemoglobin (HbA1c) 7.5-10.5% (58-91 mmol/mol)] on metformin monotherapy.

MATERIALS AND METHODS

This 52-week, multicentre, double-blind, active-controlled study (NCT02419612) randomized (1:1) patients on metformin to add-on DAPA 10 mg + SAXA 5 mg (n = 227) or GLIM 1-6 mg (titrated; n = 217). The primary efficacy endpoint was change in HbA1c from baseline to week 52.

RESULTS

Baseline mean ± standard deviation of age, duration of diabetes and HbA1c were 56.1 ± 9.7 years, 7.8 ± 6.4 years and 8.5% ± 0.8% (69 ± 9.0 mmol/mol), respectively. Adjusted mean change from baseline in HbA1c was -1.35% (-14.8 mmol/mol) with DAPA + SAXA versus -0.98% (-10.7 mmol/mol) with GLIM (P <0.001). Changes from baseline in body weight and systolic blood pressure were -3.1 kg and -2.6 mmHg with DAPA + SAXA versus +1.0 kg (P <0.001) and +1.0 mmHg (P = 0.007) with GLIM. More patients achieved HbA1c <7.0% (53 mmol/mol) (44.3% vs. 34.3%; P = 0.044), and fewer patients required treatment intensification (1.3% vs. 8.8%; P = 0.002) with DAPA + SAXA than with GLIM.

CONCLUSIONS

Compared with GLIM, concurrent addition of DAPA + SAXA significantly improved glycaemic control, body weight and other metabolic parameters in patients inadequately controlled on metformin. Trial: NCT02419612, ClinicalTrials.gov.

Effect of postprandial hyperglycemia at clinic visits on the incidence of retinopathy in patients with type 2 diabetes: An analysis using real-world long-term follow-up data

AIMS/INTRODUCTION

There is little evidence on the role of postprandial glycemia in the incidence of diabetic retinopathy (DR) in a real-world setting. We aimed to assess the effect of postprandial hyperglycemia at clinic visits on the incidence of DR in patients with type 2 diabetes, and whether its effect differs depending on glycated hemoglobin (HbA1c) values and age.

MATERIALS AND METHODS

Intrapersonal mean blood glucose levels at 1-2 h post-breakfast (1-2h-PBBG), post-lunch (1-2 h-PLBG) and both (1-2h-PBLBG) during 2 years from the first visit were used as baseline data. This retrospective cohort study enrolled 487, 323 and 406 patients who had 1-2h-PBLBG, 1-2h-PBBG and 1-2h-PLBG measurements, respectively. These three groups were followed from 1999 up through 2017.

RESULTS

DR occurred in 145, 92 and 126 patients in the 1-2h-PBLBG, 1-2h-PBBG and 1-2h-PLBG groups, respectively. Multivariate Cox regression analysis showed that the mean 1-2h-PBLBG, 1-2h-PBBG and 1-2h-PLBG levels were significant predictors of DR, independent of mean HbA1c. In patients with mean HbA1c <7.0% and those with a baseline age <60 years, the mean 1-2h-PBLBG, 1-2h-PBBG and 1-2h-PLBG levels were significant predictors.

CONCLUSIONS

Postprandial hyperglycemia at clinic visits might predict the incidence of DR, independent of HbA1c. The effect of postprandial hyperglycemia on DR is obvious in patients with well-controlled HbA1c and in younger patients. Even with the lower HbA1c level, correcting postprandial hyperglycemia is important for preventing DR, especially in middle-aged adults with type 2 diabetes.

Glucose Time In Range, Time Above Range, and Time Below Range Depend on Mean or Median Glucose or HbA1c, Glucose Coefficient of Variation, and Shape of the Glucose Distribution

Background: Examine the expected relationships between time in range (%TIR), time above range (%TAR), and time below range (%TBR) with median glucose (or %HbA1c) and %coefficient of variation (%CV) of glucose for various shapes of the glucose distribution. Methods: We considered several thresholds defining hypoglycemia and hyperglycemia and examined wide ranges of median glucose and %CV using three models for the glucose distribution: gaussian, log-gaussian, and a modified log-gaussian distribution. Results: There is a linear relationship between %TIR and median glucose for any specified %CV when median glucose is well removed from the threshold for hypoglycemia. %TIR reaches a peak when median glucose is close to 120 mg/dL and declines both at higher and lower median glucose values. There is a nearly linear relationship for %TAR and median glucose for a wider range of glucose (80-220 mg/dL). Risk of hypoglycemia is minimal when %CV is below 20%, but rises exponentially as %CV increases or as median glucose decreases. Similar results were obtained for a wide range of possible shapes of glucose distribution. These simulations are consistent with results from clinical studies. Conclusion: Both %TIR and %TAR are approximately linearly related to mean and median glucose (or %HbA1c). %TAR provides linearity over a wider range than %TIR. Risk of hypoglycemia (%TBR) is critically dependent on both glycemic variability (%CV) and mean or median glucose. These relationships support the use of %TIR, %TAR, and %TBR as metrics of quality of glycemic control for clinical, research, and regulatory purposes.

Estimation of Hemoglobin A1c from Continuous Glucose Monitoring Data in Individuals with Type 1 Diabetes: Is Time In Range All We Need?

Objective: To bridge the gap between laboratory-measured hemoglobin A1c (HbA1c) and continuous glucose monitoring (CGM)-derived time in target range (TIR), introducing TIR-driven estimated A1c (eA1c). Methods: Data from Protocol 1 (training data set) and Protocol 3 (testing data set) of the International Diabetes Closed-Loop Trial were used. Training data included 3 months of CGM recordings from 125 individuals with type 1 diabetes, and HbA1c at 3 months; testing data included 9 months of CGM recordings from 168 individuals, and HbA1c at 3, 6, and 9 months. Hemoglobin glycation was modeled by a first-order differential equation driven by TIR. Three model parameters were estimated in the training data set and fixed thereafter. A fourth parameter was estimated in the testing data set, to individualize the model by calibration with month 3 HbA1c. The accuracy of eA1c was assessed on months 6 and 9 HbA1c. Results: eA1c was tracked for each individual in the testing data set for 6 months after calibration. Mean absolute differences between HbA1c and eA1c 3- and 6-month postcalibration were 0.25% and 0.24%; Pearson's correlation coefficients were 0.93 and 0.93; percentages of eA1c within 10% from reference HbA1c were 97.6% and 96.3%, respectively. Conclusions: HbA1c and TIR are reflections of the same underlying process of glycemic fluctuation. Using a model individualized with one HbA1c measurement, TIR provides an accurate approximation of HbA1c for at least 6 months, reflecting blood glucose fluctuations and nonglycemic biological factors. Thus, eA1c is an intermediate metric that mathematically adjusts a CGM-based assessment of glycemic control to individual glycation rates.

Glucose outcomes of a learning-type artificial pancreas with an unannounced meal in type 1 diabetes

BACKGROUND AND OBJECTIVES

Glycemic control with unannounced meals is the major challenge for artificial pancreas. In this study, we described the performance and safety of learning-type model predictive control (L-MPC) for artificial pancreas challenged by an unannounced meal in type 1 diabetes (T1D).

METHODS

This closed-loop (CL) system was tested in 29 T1D patients at one site in a 4 h inpatient open-label study. Participants used an L-MPC CL system for 6 days after 2-day system identification using open-loop (OL) insulin system. During the CL period, the L-MPC system was started from 8:00 am to noon each day. At 9:00 am, each participant consumed 50 g of carbohydrates with no prandial insulin bolus. At 9:30 am on CL-Day 4 or CL-Day 6, participants rode bicycles for 20 minutes or drank 50 ml of beer, in a random order.

RESULTS

As the primary outcome, TIR on CL-Day 3 was 65.2±23.3%, which was 9.8 points higher (95% CI 1.8 to 17.8; P = 0.019) than that on CL-Day 1. The time of glucose >10 mmol/L was decreased by 11.0% (95% CI -18.7 to 3.3; P = 0.007), and mean glucose level was decreased by 1.1 mmol/L (95% CI -1.1 to 0.5; P = 0.000). The total daily insulin dosage showed no significant difference (-0.1U, 95% CI -1.34 to 1.32; P = 0.982). Compared with OL-Day1 with a postprandial bolus, the TIR was increased by 13.7 points (95% CI 1.4 to 26.0; P = 0.030), the time of glucose >10 mmol/L and the mean glucose level were also decreased. Compared with the exercise day (CL-Day E, 62.0 ± 23.3%; P = 0.347) or alcohol day (CL-Day A, 64.0 ± 23.6%; P = 0.756), there was no statistically significant difference in terms of TIR, time of glucose >10 mmol/L and mean glucose level. No severe hypoglycemic events occurred and hypoglycemic episodes were not increased by using closed-loop insulin system.

CONCLUSION

The L-MPC CL insulin system achieved good glycemic control challenged by an unannounced meal.

Effects of Continuous Glucose Monitoring on Metrics of Glycemic Control in Diabetes: A Systematic Review With Meta-analysis of Randomized Controlled Trials

BACKGROUND

Continuous glucose monitoring (CGM) provides important information to aid in achieving glycemic targets in people with diabetes.

PURPOSE

We performed a meta-analysis of randomized controlled trials (RCTs) comparing CGM with usual care for parameters of glycemic control in both type 1 and type 2 diabetes.

DATA SOURCES

Many electronic databases were searched for articles published from inception until 30 June 2019.

STUDY SELECTION

We selected RCTs that assessed both changes in HbA_1c and time in target range (TIR), together with time below range (TBR), time above range (TAR), and glucose variability expressed as coefficient of variation (CV).

DATA EXTRACTION

Data were extracted from each trial by two investigators.

DATA SYNTHESIS

All results were analyzed by a random effects model to calculate the weighted mean difference (WMD) with the 95% CI. We identified 15 RCTs, lasting 12-36 weeks and involving 2,461 patients. Compared with the usual care (overall data), CGM was associated with modest reduction in HbA_1c (WMD -0.17%, 95% CI -0.29 to -0.06, I ² = 96.2%), increase in TIR (WMD 70.74 min, 95% CI 46.73-94.76, I ² = 66.3%), and lower TAR, TBR, and CV, with heterogeneity between studies. The increase in TIR was significant and robust independently of diabetes type, method of insulin delivery, and reason for CGM use. In preplanned subgroup analyses, real-time CGM led to the higher improvement in mean HbA_1c (WMD -0.23%, 95% CI -0.36 to -0.10, P < 0.001), TIR (WMD 83.49 min, 95% CI 52.68-114.30, P < 0.001), and TAR, whereas both intermittently scanned CGM and sensor-augmented pump were associated with the greater decline in TBR.

LIMITATIONS

Heterogeneity was high for most of the study outcomes; all studies were sponsored by industry, had short duration, and used an open-label design.

CONCLUSIONS

CGM improves glycemic control by expanding TIR and decreasing TBR, TAR, and glucose variability in both type 1 and type 2 diabetes.

Clinical Recommendations for the Use of the Ambulatory Glucose Profile in Diabetes Care

BACKGROUND

The ambulatory glucose profile (AGP) uses the wealth of data that are generated by continuous glucose monitoring, including flash glucose monitoring technologies, to provide a visual representation of glucose levels over a typical standard day of usually the most recent two weeks for a person with diabetes and helps to identify patterns and trends in glucose control. The AGP allows certain patterns of glucose levels to be identified and analyzed, such that treatment adjustments can be made, and new individual treatment goals can be defined. This helps to ensure increased treatment satisfaction and adherence, quality of life, and an improvement in metabolic management for people with diabetes.

OBJECTIVE

To date, a range of approaches exists for interpreting the information contained in an AGP, with different priorities given to identifying and targeting patterns of hypoglycemia and the degree of variability and stability underlying the glucose levels. The objective of the present recommendation is to describe the steps for assessing an AGP in detail and to illustrate these steps using visual examples.

CONCLUSION

This paper describes the consensus recommendations from a group of German expert diabetologists on the necessary steps for assessing an AGP in a structured and detailed way and to explain these steps using practical clinical examples.

Longitudinal Analysis of Real-World Performance of an Implantable Continuous Glucose Sensor over Multiple Sensor Insertion and Removal Cycles

The Eversense® Continuous Glucose Monitoring (CGM) System, with the first long-term, implantable glucose sensor, has been commercially available in Europe and South Africa since 2016 for adults with diabetes. The performance of the sensor over multiple, sequential 90- or 180-day cycles from either real-world experience or clinical studies has not been previously published. The Eversense Data Management System (DMS) was used to evaluate the accuracy of General Data Protection Regulation (GDPR)-compliant sensor glucose (SG) values against self-monitoring of blood glucose (SMBG) from June 2016 through August 2019 among patients with at least four sensor cycles from European and South African health care practices. Mean SG and associated measures of variability, glucose management indicator (GMI), and percent and time in various hypoglycemic, euglycemic, and hyperglycemic ranges were calculated for the 24-h time period over each cycle. In addition, transmitter wear time was evaluated across each sensor wear cycle. Among the 945 users included in the analysis, the mean absolute relative difference (standard deviation [SD]) using 152,206, 174,645, 206,024, and 172,587 calibration matched pairs against SMBG was 11.9% (3.6%), 11.5% (4.0%), 11.8% (4.7%), and 11.5% (4.1%) during the first four sensor cycles, respectively. Mean values of the CGM metrics over the first sensor cycle were 156.5 mg/dL for SG, 54.7 mg/dL for SD, 0.35 for coefficient of variation, and 7.04% for GMI. Percent SG at different glycemic ranges was as follows: <54 mg/dL was 1.1% (16 min), <70 mg/dL was 4.6% (66 min), ≥70-180 mg/dL (time in range) was 64.5% (929 min), >180-250 mg/dL was 22.8% (328 min), and >250 mg/dL was 8.1% (117 min). The median transmitter wear time over the first cycle was 83.2%. CGM metrics and wear time were similar over the subsequent three cycles. This real-world evaluation of adult patients with diabetes using the Eversense CGM System in the home setting demonstrated that the implantable sensor provides consistent stable accuracy and CGM metrics over multiple, sequential sensor cycles with no indication of degradation of sensor performance.

Influence of glucometric 'dynamical' variables on duodenal-jejunal bypass liner (DJBL) anthropometric and metabolic outcomes

BACKGROUND

The endoscopically implanted duodenal-jejunal bypass liner (DJBL) is an attractive alternative to bariatric surgery for obese diabetic patients. This article aims to study dynamical aspects of the glycaemic profile that may influence DJBL effects.

METHODS

Thirty patients underwent DJBL implantation and were followed for 10 months. Continuous glucose monitoring (CGM) was performed before implantation and at month 10. Dynamical variables from CGM were measured: coefficient of variation of glycaemia, mean amplitude of glycaemic excursions (MAGE), detrended fluctuation analysis (DFA), % of time with glycaemia under 6.1 mmol/L (TU6.1), area over 7.8 mmol/L (AO7.8) and time in range. We analysed the correlation between changes in both anthropometric (body mass index, BMI and waist circumference) and metabolic (fasting blood glucose, FBG and HbA1c) variables and dynamical CGM-derived metrics and searched for variables in the basal CGM that could predict successful outcomes.

RESULTS

There was a poor correlation between anthropometric and metabolic outcomes. There was a strong correlation between anthropometric changes and changes in glycaemic tonic control (∆BMI-∆TU6.1: rho = - 0.67, P < .01) and between metabolic outcomes and glycaemic phasic control (∆FBG-∆AO7.8: r = .60, P < .01). Basal AO7.8 was a powerful predictor of successful metabolic outcome (0.85 in patients with AO7.8 above the median vs 0.31 in patients with AO7.8 below the median: Chi-squared = 5.67, P = .02).

CONCLUSIONS

In our population, anthropometric outcomes of DJBL correlate with improvement in tonic control of glycaemia, while metabolic outcomes correlate preferentially with improvement in phasic control. Assessment of basal phasic control may help in candidate profiling for DJBL implantation.

Glucagon-like Peptide 1 Receptor Agonists, Diabetic Retinopathy and Angiogenesis: The AngioSafe Type 2 Diabetes Study

AIMS

Recent trials provide conflicting results on the association between glucagon-like peptide 1 receptor agonists (GLP-1RA) and diabetic retinopathy (DR). The aim of the AngioSafe type 2 diabetes (T2D) study was to determine the role of GLP-1RA in angiogenesis using clinical and preclinical models.

METHODS

We performed two studies in humans. In study 1, we investigated the effect of GLP-1RA exposure from T2D diagnosis on the severity of DR, as diagnosed with retinal imaging (fundus photography). In study 2, a randomized 4-week trial, we assessed the effect of liraglutide on circulating hematopoietic progenitor cells (HPCs), and angio-miRNAs.We then studied the experimental effect of Exendin-4, on key steps of angiogenesis: in vitro on human endothelial cell proliferation, survival and three-dimensional vascular morphogenesis; and in vivo on ischemia-induced neovascularization of the retina in mice.

RESULTS

In the cohort of 3154 T2D patients, 10% displayed severe DR. In multivariate analysis, sex, disease duration, glycated hemoglobin (HbA1c), micro- and macroangiopathy, insulin therapy and hypertension remained strongly associated with severe DR, while no association was found with GLP-1RA exposure (o 1.139 [0.800-1.622], P = .47). We further showed no effect of liraglutide on HPCs, and angio-miRNAs. In vitro, we demonstrated that exendin-4 had no effect on proliferation and survival of human endothelial cells, no effect on total length and number of capillaries. Finally, in vivo, we showed that exendin-4 did not exert any negative effect on retinal neovascularization.

CONCLUSIONS

The AngioSafe T2D studies provide experimental and clinical data confirming no effect of GLP-1RA on angiogenesis and no association between GLP-1 exposure and severe DR.

Screening for diabetic retinopathy: new perspectives and challenges

Although the prevalence of all stages of diabetic retinopathy has been declining since 1980 in populations with improved diabetes control, the crude prevalence of visual impairment and blindness caused by diabetic retinopathy worldwide increased between 1990 and 2015, largely because of the increasing prevalence of type 2 diabetes, particularly in low-income and middle-income countries. Screening for diabetic retinopathy is essential to detect referable cases that need timely full ophthalmic examination and treatment to avoid permanent visual loss. In the past few years, personalised screening intervals that take into account several risk factors have been proposed, with good cost-effectiveness ratios. However, resources for nationwide screening programmes are scarce in many countries. New technologies, such as scanning confocal ophthalmology with ultrawide field imaging and handheld mobile devices, teleophthalmology for remote grading, and artificial intelligence for automated detection and classification of diabetic retinopathy, are changing screening strategies and improving cost-effectiveness. Additionally, emerging evidence suggests that retinal imaging could be useful for identifying individuals at risk of cardiovascular disease or cognitive impairment, which could expand the role of diabetic retinopathy screening beyond the prevention of sight-threatening disease.

The Effect of Acarbose on Glycemic Variability in Patients with Type 2 Diabetes Mellitus Using Premixed Insulin Compared to Metformin (AIM): An Open-Label Randomized Trial

Background: Acarbose (ACA) can effectively reduce the postprandial blood glucose and has similar antidiabetic effects as metformin (MET). To our knowledge, few studies have compared the effect of ACA or MET on glucose fluctuations. In the present study, we explored the effect of ACA or MET combined with premixed insulin (INS) on glycemic control and glycemic variability (GV). Methods: This was an open-label randomized trial that was conducted in type 2 diabetic patients taking premixed insulin. The patients were assigned to 12 weeks of MET (n = 62) or ACA (n = 62) treatment combined with INS. The main outcomes were changes in GV and glycosylated hemoglobin A1c (HbA1c) compared with baseline. Results: Compared with baseline, several GV indices (standard deviation [SD], mean amplitude of glycemic excursions [MAGE]) and blood glucose control indices (mean glucose [MG], time in range [TIR] and HbA1c) were both significantly improved in INS+ACA and INS+MET after 12-week therapy. However, coefficient of variation (CV) was significantly reduced in INS+ACA but not in INS+MET. Moreover, compared with INS+MET, INS+ACA led to a more pronounced percentage change from baseline in CV (26.3% [1.7%-44.6%] vs. 11.9% [-7.0% to 29.9%], P = 0.022), MAGE (40.5% [20.1%-60.5%] vs. 25.2% [-2.1% to 43.4%], P = 0.007) and SD (38.6% [25.2%-57.9%] vs. 30.1% [10.8%-46.5%], P = 0.041). Conclusion: Both MET and ACE combined with INS effectively reduced blood glucose. Compared with MET, ACA combined with INS reduced GV.

Impact of acute-phase insulin secretion on glycemic variability in insulin-treated patients with type 2 diabetes

AIMS

The association between β-cell function and glycemic variability remains to be clarified in insulin-treated patients with type 2 diabetes. Therefore, the study sought to examine the association of various indices of β-cell function with glycemic variability in Chinese insulin-treated patients with type 2 diabetes.

METHODS

Glycemic variability was assessed by the coefficient of variation (CV) of glucose levels with the use of continuous glucose monitoring (CGM). Basal β-cell function was evaluated by fasting C-peptide (FCP) and the homeostasis model assessment 2 for β-cell function (HOMA2-%β). Postload β-cell function was measured by 2-hour C-peptide (2hCP) and the acute C-peptide response (ACPR) to arginine.

RESULTS

When a cutoff value of CV ≥ 36% was used to define unstable glucose, the multivariable-adjusted odds ratios for labile glycemic control were 0.34 (95% CI 0.18-0.64) for each 1 ng/mL increase in ACPR, 0.47 (95% CI 0.27-0.81) for each 1 ng/mL increase in FCP, 0.77 (95% CI 0.61-0.97) for each 1 ng/mL increase in 2hCP, and 1.00 (95% CI 0.98-1.01) for each 1% increase in HOMA2-%β. When we further adjusted for 2hCP and HOMA2-%β in the ACPR and FCP analyses, and adjusted for ACPR or FCP in the 2hCP analyses, only ACPR but not FCP or 2hPC remained to be a significant and inverse predictor for labile glycemic control.

CONCLUSIONS

ACPR evaluated by the arginine stimulation test may be superior to other commonly used β-cell function parameters to reflect glycemic fluctuation in insulin-treated patients with type 2 diabetes.

Improved glycaemic variability and time in range with dapagliflozin versus gliclazide modified release among adults with type 2 diabetes, evaluated by continuous glucose monitoring: A 12-week randomized controlled trial

AIMS

To evaluate whether there is a difference between the effects of dapagliflozin and gliclazide modified release (MR) on glycaemic variability (GV) and glycaemic control, as assessed by continuous glucose monitoring (CGM), in individuals with uncontrolled type 2 diabetes.

MATERIALS AND METHODS

This randomized, open-label, active-controlled study was conducted in individuals with uncontrolled type 2 diabetes who were drug-naïve or on steady-dose metformin monotherapy. Participants were treated once daily with 10 mg dapagliflozin or 120 mg gliclazide MR. CGM and GV index calculations were performed at baseline and after 12 weeks.

RESULTS

In total, 97 participants (age 57.9 ± 8.7 years, 50.5% men, baseline glycated haemoglobin 63 ± 9.8 mmol/mol [7.9 ± 0.9%]) were randomized, and 94 completed the 12-week protocol. Intention-to-treat (ITT) and per-protocol (PP) analyses showed that the reduction in GV, as measured by the mean amplitude of glycaemic excursions, was superior in the dapagliflozin group versus the gliclazide MR group (-0.9 mmol/L [95% CI -1.5, -0.4] vs -0.2 mmol/L [95% CI -0.6, 0.3]; P = 0.030 [ITT]). The reductions in GV estimated by the coefficient of variation and SD were greater in the dapagliflozin group. Moreover, dapagliflozin increased the glucose time in range (TIR; 3.9-10 mmol/L) by 24.9% (95% CI 18.6, 31.2) vs. 17.4% (95% CI 11.6, 23.3) in the gliclazide MR group (P = 0.089 [ITT]; P = 0.041 [PP]).

CONCLUSIONS

Dapagliflozin improved GV and increased TIR more efficiently than gliclazide MR in individuals with type 2 diabetes over 12 weeks, as demonstrated by CGM.

Sotagliflozin Decreases Postprandial Glucose and Insulin Concentrations by Delaying Intestinal Glucose Absorption

CONTEXT

The effect of sotagliflozin (a dual sodium-glucose cotransporter [SGLT] 2 and SGLT1 inhibitor) on intestinal glucose absorption has not been investigated in humans.

OBJECTIVE

To measure rate of appearance of oral glucose (RaO) using a dual glucose tracer method following standardized mixed meals taken after single sotagliflozin or canagliflozin doses.

SETTING

Clinical research organization.

DESIGN AND PARTICIPANTS

In a double-blind, 3-period crossover study (NCT01916863), 24 healthy participants were randomized to 2 cohorts of 12 participants. Within each cohort, participants were randomly assigned single oral doses of either sotagliflozin 400 mg, canagliflozin 300 mg, or placebo on each of test days 1, 8, and 15. On test days, Cohort 1 had breakfast containing [6,6-2H2] glucose 0.25 hours postdose and lunch containing [1-2H1] glucose 5.25 hours postdose; Cohort 2 had breakfast containing no labeled glucose 0.25 hours postdose and lunch containing [6,6-2H2] glucose 4.25 hours postdose. All participants received a 10- to 15-hour continuous [U-13C6] glucose infusion starting 5 hours before their first [6,6-2H2] glucose-containing meal.

MAIN OUTCOME

RaO, postprandial glucose (PPG), and postprandial insulin.

RESULTS

Sotagliflozin and canagliflozin decreased area under the curve (AUC)0-1 hour and/or AUC0-2 hours for RaO, PPG, and insulin after breakfast and/or the 4.25-hour postdose lunch (P < .05 versus placebo). After the 5.25-hour postdose lunch, sotagliflozin lowered RaO AUC0-1 hour and PPG AUC0-5 hours versus both placebo and canagliflozin (P < .05).

CONCLUSIONS

Sotagliflozin delayed and blunted intestinal glucose absorption after meals, resulting in lower PPG and insulin levels, likely due to prolonged local inhibition of intestinal SGLT1 that persisted for ≥5 hours after dosing.

HbA1c: The Glucose Management Indicator, Time in Range, and Standardization of Continuous Glucose Monitoring Reports in Clinical Practice

Continuous glucose monitoring (CGM) use is growing rapidly among people with diabetes and beginning to be standard of care for managing glucose levels in insulin therapy. With this increased use, there is a need to standardize CGM data. CGM standardization has been set forth by expert panels. The Glucose Management Indicator is a concept using the CGM-derived mean glucose to provide a value that can be understood similarly to hemoglobin A_1c. The times an individual spends in various glucose ranges is emerging as an important set of metrics. Metrics derived from patient CGM data are changing the way diabetes is managed.

Efficacy of the Diabeloop closed-loop system to improve glycaemic control in patients with type 1 diabetes exposed to gastronomic dinners or to sustained physical exercise

AIMS

To compare closed-loop (CL) and open-loop (OL) systems for glycaemic control in patients with type 1 diabetes (T1D) exposed to real-life challenging situations (gastronomic dinners or sustained physical exercise).

METHODS

Thirty-eight adult patients with T1D were included in a three-armed randomized pilot trial (Diabeloop WP6.2 trial) comparing glucose control using a CL system with use of an OL device during two crossover 72-hour periods in one of the three following situations: large (gastronomic) dinners; sustained and repeated bouts of physical exercise (with uncontrolled food intake); or control (rest conditions). Outcomes included time in spent in the glucose ranges of 4.4-7.8 mmol/L and 3.9-10.0 mmol/L, and time in hypo- and hyperglycaemia.

RESULTS

Time spent overnight in the tight range of 4.4 to 7.8 mmol/L was longer with CL (mean values: 63.2% vs 40.9% with OL; P ≤ .0001). Time spent during the day in the range of 3.9 to 10.0 mmol/L was also longer with CL (79.4% vs 64.1% with OL; P ≤ .0001). Participants using the CL system spent less time during the day with hyperglycaemic excursions (glucose >10.0 mmol/L) compared to those using an OL system (17.9% vs 31.9%; P ≤ .0001), and the proportions of time spent during the day with hyperglycaemic excursions of those using the CL system in the gastronomic dinner and physical exercise subgroups were of similar magnitude to those in the control subgroup (18.1 ± 6.3%, 17.2 ± 8.1% and 18.4 ± 12.5%, respectively). Finally, times spent in hypoglycaemia were short and not significantly different among the groups.

CONCLUSIONS

The Diabeloop CL system is superior to OL devices in reducing hyperglycaemic excursions in patients with T1D exposed to gastronomic dinners, or exposed to physical exercise followed by uncontrolled food and carbohydrate intake.

Glycemic variability modifies the relationship between time in range and hemoglobin A1c estimated from continuous glucose monitoring: A preliminary study

AIMS

Although there is a linear relationship between time in range (TIR) and hemoglobin A1c (HbA1c), a great variability of calculated TIR values for a given HbA1c, and vice versa, has been reported. Whether glycemic variability accounts for part of this variability remains to be investigated.

METHODS

The data of continuous glucose monitoring (CGM) from 2559 patients with type 2 diabetes was analyzed. Glycemic variability was assessed by glucose coefficient of variation (CV), and estimated HbA1C (eHbA1c) was calculated from mean sensor glucose.

RESULTS

A strong correlation between TIR and eHbA1c (r = -0.908) was observed. The slopes of regression lines fitted to TIR values as a function of eHbA1c differed significantly for individuals with varying degrees of CV, especially when patients were stratified as stable (CV < 36%) or unstable (CV ≥ 36%) glucose levels. For patients in the high- or low-range of eHbA1c, there was a high variability of TIR values according to CV.

CONCLUSIONS

Glycemic variability significantly mediates the relationship between TIR and eHbA1c, and should be taken into consideration when setting an individualized target of TIR.

Evaluating Glucose Control With a Novel Composite Continuous Glucose Monitoring Index

OBJECTIVE

The objective was to describe a novel composite continuous glucose monitoring index (COGI) and to evaluate its utility, in adults with type 1 diabetes, during hybrid closed-loop (HCL) therapy and multiple daily injections (MDI) therapy combined with real-time continuous glucose monitoring (CGM).

METHODS

COGI consists of three key components of glucose control as assessed by CGM: Time in range (TIR), time below range (TBR), and glucose variability (GV) (weighted by 50%, 35% and 15%). COGI ranges from 0 to 100, where 1% increase of time <3.9 mmol/L (<70 mg/dl) is equivalent to 4.7% reduction of TIR between 3.9-10 mmol/L (70-180 mg/dl), and 0.5 mmol/L (9 mg/dl) increase in standard deviation is equivalent to 3% reduction in TIR.

RESULTS

Continuous subcutaneous insulin infusion (CSII) users with HbA1c >7.5-10%, had significantly higher COGI during 12 weeks of HCL compared to sensor-augmented pump therapy, mean (SD), 60.3 (8.6) versus 69.5 (6.9), P < .001. Similarly, in CSII users with HbA1c <7.5%, HCL improved COGI from 59.9 (11.2) to 74.8 (6.6), P < .001. In MDI users with HbA1c >7.5% to 9.9%, use of real-time CGM led to improved COGI, 49.8 (14.2) versus 58.2 (9.1), P < .0001. In MDI users with impaired awareness of hypoglycemia, use of real-time CGM led to improved COGI, 53.4 (12.2) versus 66.7 (11.1), P < .001.

CONCLUSIONS

COGI summarizes three key aspects of CGM data into a concise metric that could be utilized to evaluate the quality of glucose control and to demonstrate the incremental benefit of a wide range of treatment modalities.

The burden of type 2 diabetes in Europe: Current and future aspects of insulin treatment from patient and healthcare spending perspectives

Due to the progressive nature of type 2 diabetes (T2DM), initiation of insulin therapy is very likely in the disease continuum. This article aims at highlighting the current situation with regard to insulin therapy in people with T2DM in Europe and at presenting the associated unmet need. Challenges for both people with T2DM and healthcare professionals include clinical inertia also derived from fear of hypoglycaemia, weight gain and injections as well as increased need for a comprehensive diabetes management. We compare national and international guidelines and recommendations for the initiation and intensification of insulin therapy with the real-world situation in six European countries, demonstrating that glycaemic targets are only met in a minority of people with T2DM on insulin therapy. Furthermore, this work evaluates currently recorded numbers of people with T2DM treated with insulin in Europe, the proportion not achieving the stated glycaemic targets and thus in need to enhance insulin therapy e.g. by a change in means of insulin delivery including, but not limited to, insulin pens, wearable mealtime insulin delivery patches, patch pumps, and conventional insulin pumps with continuous subcutaneous insulin infusion.

Diabetes Healthcare Professionals Use Multiple Continuous Glucose Monitoring Data Indicators to Assess Glucose Management

BACKGROUND

Continuous glucose monitoring (CGM) offers multiple data features that can be leveraged to assess glucose management. However, how diabetes healthcare professionals (HCPs) actually assess CGM data and the extent to which they agree in assessing glycemic management are not well understood.

METHODS

We asked HCPs to assess ten de-identified CGM datasets (each spanning seven days) and rank order each day by relative glycemic management (from "best" to "worst"). We also asked HCPs to endorse features of CGM data that were important in making such assessments.

RESULTS

In the study, 57 HCPs (29 endocrinologists; 28 diabetes educators) participated. Hypoglycemia and glycemic variance were endorsed by nearly all HCPs to be important (91% and 88%, respectively). Time in range and daily lows and highs were endorsed more frequently by educators (all Ps < .05). On average, HCPs endorsed 3.7 of eight data features. Overall, HCPs demonstrated agreement in ranking days by relative glycemic control (Kendall's W = .52, P < .001). Rankings were similar between endocrinologists and educators (R² = .90, Cohen's kappa = .95, mean absolute error = .4 [all Ps < .05]; Mann-Whitney U = 41, P = .53).

CONCLUSIONS

Consensus in the endorsement of certain data features and agreement in assessing glycemic management were observed. While some practice-specific differences in feature endorsement were found, no differences between educators and endocrinologists were observed in assessing glycemic management. Overall, HCPs tended to consider CGM data holistically, in alignment with published recommendations, and made converging assessments regardless of practice.

Effects of Exercise on Blood Glucose and Glycemic Variability in Type 2 Diabetic Patients with Dawn Phenomenon

Background

The dawn phenomenon (DP) is the primary cause of difficulty in blood glucose management in type 2 diabetic (T2D) patients, and the use of oral hypoglycemic agents has shown weak efficacy in controlling DP. Thus, this study is aimed at investigating the effect of moderate-intensity aerobic exercise before breakfast on the blood glucose level and glycemic variability in T2D patients with DP.

Methods

A total of 20 T2D patients with DP confirmed via continuous glucose monitoring (CGM) participated in the current study. After collecting baseline measurements by CGM as a control, CGM was reinstalled and 30 minutes of moderate-intensity aerobic exercise was performed prior to breakfast. Dawn blood glucose increase, blood glucose levels, and glycemic variability were measured before and after exercise.

Results

Dawn blood glucose increase (ΔGlu, 1.25 ± 0.84vs.2.15 ± 1.07, P = 0.005), highest blood glucose value before breakfast (Gmax, 8.01 ± 1.16vs. 8.78 ± 1.09, P = 0.005), highest blood glucose value before breakfast (Gmax, 8.01 ± 1.16vs. 8.78 ± 1.09, P = 0.005), highest blood glucose value before breakfast (Gmax, 8.01 ± 1.16vs. 8.78 ± 1.09, P = 0.005), highest blood glucose value before breakfast (Gmax, 8.01 ± 1.16vs. 8.78 ± 1.09, P = 0.005), highest blood glucose value before breakfast (Gmax, 8.01 ± 1.16vs.2.15 ± 1.07, P = 0.005), highest blood glucose value before breakfast (Gmax, 8.01 ± 1.16vs.2.15 ± 1.07, P = 0.005), highest blood glucose value before breakfast (Gmax, 8.01 ± 1.16vs.2.15 ± 1.07, P = 0.005), highest blood glucose value before breakfast (Gmax, 8.01 ± 1.16

Conclusions

Acute moderate-intensity aerobic exercise before breakfast reduced the morning rise of blood glucose in T2D patients, partially counteracting DP. Furthermore, exercise significantly reduced blood glucose fluctuations and improved blood glucose control throughout the day. We recommend that T2D patients with DP take moderate-intensity aerobic exercise before breakfast to improve DP and glycemic control.

Time in Range, as a Novel Metric of Glycemic Control, Is Reversely Associated with Presence of Diabetic Cardiovascular Autonomic Neuropathy Independent of HbA1c in Chinese Type 2 Diabetes

OBJECTIVE

The objective of this study is to investigate the relationship between time in range (TIR), a new metric of continuous glucose monitoring (CGM) and cardiovascular autonomic neuropathy (CAN) in individuals with type 2 diabetes mellitus (T2DM).

METHODS

A total of 349 individuals with T2DM were enrolled in this study. Evaluating by the standard cardiac autonomic reflex tests (CARTs), there were 228 diabetic individuals without cardiovascular autonomic neuropathy (without confirmed CAN) including absent CAN (n = 83 cases) and early CAN (n = 83 cases) and early CAN (n = 83 cases) and early CAN (n = 83 cases) and early CAN (.

RESULTS

The total presence of CAN was 34.67% (definite CAN 31.23% and severe CAN 3.44%). Patients with more severe CAN had lower TIR (P < 0.001). With increasing quartiles of TIR, the presence of CAN by severity declined (P < 0.001). With increasing quartiles of TIR, the presence of CAN by severity declined (P < 0.001). With increasing quartiles of TIR, the presence of CAN by severity declined (P < 0.001). With increasing quartiles of TIR, the presence of CAN by severity declined (.

CONCLUSION

TIR is associated with the presence of CAN independent of HbA1c and GV metrics in Chinese type 2 diabetes.

Time in Range Is Associated with Carotid Intima-Media Thickness in Type 2 Diabetes

Background: Time in range (TIR) is an emerging metric of glycemic control and is reported to be associated with microvascular complications of diabetes. We sought to investigate the association of TIR obtained from continuous glucose monitoring (CGM) with carotid intima-media thickness (CIMT) as a surrogate marker of cardiovascular disease (CVD). Methods: Data from 2215 patients with type 2 diabetes were cross-sectionally analyzed. TIR of 3.9-10.0 mmol/L was evaluated with CGM. CIMT was measured using high-resolution B-mode ultrasonography and abnormal CIMT was defined as a mean CIMT ≥1.0 mm. Logistic regression models were used to examine the independent association of TIR with CIMT. Results: Compared with patients with normal CIMT, those with abnormal CIMT had significantly lower TIR (P < 0.001). The prevalence of abnormal CIMT progressively decreased across the categories of increasing TIR (P for trend <0.001). In a fully adjusted model controlling for traditional risk factor of CVD, each 10% increase in TIR was associated with 6.4% lower risk of abnormal CIMT. Stratifying the data by sex revealed that TIR was significantly associated with CIMT in males but not in females. In a subset of patients (n = 612) with complete data on diabetic retinopathy and albuminuria, we found that the relationship between TIR and CIMT remained to be significant, regardless of the status of microvascular complications. Conclusions: TIR is associated with CIMT in a large sample of patients with type 2 diabetes, suggesting a link between TIR and macrovascular disease.

Role of Composite Glycemic Indices: A Comparison of the Comprehensive Glucose Pentagon Across Diabetes Types and HbA1c Levels

Background: Complex changes of glycemia that occur in diabetes are not fully captured by any single measure. The Comprehensive Glucose Pentagon (CGP) measures multiple aspects of glycemia to generate the prognostic glycemic risk (PGR), which constitutes the relative risk of hypoglycemia combined with long-term complications. We compare the components of CGP and PGR across type 1 and type 2 diabetes. Methods: Participants: n = 60 type 1 and n = 100 type 2 who underwent continuous glucose monitoring (CGM). Mean glucose, coefficient of variation (%CV), intensity of hypoglycemia (INT_hypo), intensity of hyperglycemia (INT_hyper), time out-of-range (TOR <3.9 and >10 mmol/L), and PGR were calculated. PGR (median, interquartile ranges [IQR]) for diabetes types, and HbA1c classes were compared. Results: While HbA1c was lower in type 1 (type 1 vs. type 2: 8.0 ± 1.6 vs. 8.6 ± 1.7, P = 0.02), CGM-derived mean glucoses were similar across both groups (P > 0.05). TOR, %CV, INT_hypo, and INT_hyper were all higher in type 1 [type 1 vs. type 2: 665 (500, 863) vs. 535 (284, 823) min/day; 39% (33, 46) vs. 29% (24, 34); 905 (205, 2951) vs. 18 (0, 349) mg/dL × min²; 42,906 (23,482, 82,120) vs. 30,166 (10,276, 57,183) mg/dL × min², respectively, all P < 0.05]. Across each HbA1c class, the PGR remained consistently and significantly higher in type 1. While mean glucose remained the same across HbA1c classes, %CV, TOR, INT_hyper, and INT_hypo were significantly higher for type 1. Even within the same HbA1c class, the variation (IQR) of each parameter in type 1 was wider. The PGR increased across diabetes groups; type 2 on orals versus type 2 on insulin versus type 1 (PGR: 1.6 vs. 2.2 vs. 2.9, respectively, P < 0.05). Conclusion: Composite indices such as the CGP capture significant differences in glycemia independent of HbA1c and mean glucose. The use of such indices must be explored in both the clinical and research settings.

Positioning time in range in diabetes management

Recent upswings in the use of continuous glucose monitoring (CGM) technologies have given people with diabetes and healthcare professionals unprecedented access to a range of new indicators of glucose control. Some of these metrics are useful research tools and others have been welcomed by patient groups for providing insights into the quality of glucose control not captured by conventional laboratory testing. Among the latter, time in range (TIR) is an intuitive metric that denotes the proportion of time that a person's glucose level is within a desired target range (usually 3.9-10.0 mmol/l [3.5-7.8 mmol/l in pregnancy]). For individuals choosing to use CGM technology, TIR is now often part of the expected conversation between patient and healthcare professional, and consensus recommendations have recently been produced to facilitate the adoption of standardised TIR targets. At a regulatory level, emerging evidence linking TIR to risk of complications may see TIR being more widely accepted as a valid endpoint in future clinical trials. However, given the skewed distribution of possible glucose values outside of the target range, TIR (on its own) is a poor indicator of the frequency or severity of hypoglycaemia. Here, the state-of-the-art linking TIR with complications risk in diabetes and the inverse association between TIR and HbA_1c are reviewed. Moreover, the importance of including the amount and severity of time below range (TBR) in any discussions around TIR and, by inference, time above range (TAR) is discussed. This review also summarises recent guidance in setting 'time in ranges' goals for individuals with diabetes who wish to make use of these metrics. For most people with type 1 or type 2 diabetes, a TIR >70%, a TBR <3.9 mmol/l of <4%, and a TBR <3.0 mmol/l of <1% are recommended targets, with less stringent targets for older or high-risk individuals and for those under 25 years of age. As always though, glycaemic targets should be individualised and rarely is that more applicable than in the personal use of CGM and the data it provides.

Optimising the Benefits of SGLT2 Inhibitors for Type 1 Diabetes

Sodium-glucose cotransporter 2 (SGLT2) inhibitor clinical studies in type 1 diabetes mellitus (T1DM) have demonstrated reduced HbA1c and lower glucose variability with increased time in optimal glucose range as well as additional benefits of reductions in weight and insulin dose without increasing the incidence of hypoglycaemia. However, the appropriate use of SGLT2 inhibitor therapies within clinical practise to treat people with T1DM remains unclear. In this article we have used consensus expert opinion alongside the available evidence, product indication and most recent clinical guidance to provide support for the diabetes healthcare community regarding the appropriate use of SGLT2 inhibitors, focussing on specific considerations for appropriate prescribing of dapagliflozin within the T1DM management pathway. Its purpose is to provide awareness of the issues surrounding treatment with dapagliflozin in T1DM as well as offer practical guidance that also includes a checklist tool for appropriate dapagliflozin prescribing. The checklist aims to support clinicians in identifying those people with T1DM most likely to benefit from dapagliflozin treatment as well as situations where caution may be required.Funding: AstraZeneca UK Ltd.

Time in range: a new parameter to evaluate blood glucose control in patients with diabetes

The International Consensus in Time in Range (TIR) was recently released and defined the concept of the time spent in the target range between 70 and 180 mg/dL while reducing time in hypoglycemia, for patients using Continuous Glucose Monitoring (CGM). TIR was validated as an outcome measures for clinical Trials complementing other components of glycemic control like Blood glucose and HbA1c. The challenge is to implement this practice more widely in countries with a limited health public and private budget as it occurs in Brazil. Could CGM be used intermittently? Could self-monitoring blood glucose obtained at different times of the day, with the amount of data high enough be used? More studies should be done, especially cost-effective studies to help understand the possibility of having sensors and include TIR evaluation in clinical practice nationwide.

Real-world flash glucose monitoring in Brazil: can sensors make a difference in diabetes management in developing countries?

BACKGROUND

New technologies are changing diabetes treatment and contributing better outcomes in developed countries. To our knowledge, no previous studies have investigated the comparative effect of sensor-based monitoring on glycemic markers in developing countries like Brazil. The present study aims to evaluate the use of intermittent Continuous Glucose Measurements (iCGM) in a developing country, Brazil, regarding (i) frequency of glucose scans, (ii) its association with glycemic markers and (iii) comparison with these findings to those observed in global population data.

METHODS

Glucose results were de-identified and uploaded to a dedicated database when Freestyle Libre™ readers were connected to an internet-ready computer. Data between September 2014 and Dec 2018, comprising 688,640 readers and 7,329,052 sensors worldwide, were analysed (including 17,691 readers and 147,166 sensors from Brazil). Scan rate per reader was determined and each reader was sorted into 20 equally-sized rank ordered groups, categorised by scan frequency. Glucose parameters were calculated for each group, including estimated A1c, time above, below and within range identified as 70-180 mg/dL.

RESULTS

In Brazil, reader users performed an average of 14 scans per day, while around the world, reader users performed an average of 12 scans per day (p < 0.01). In Brazil dataset, those in the lowest and in the highest groups scanned on average 3.6 and 43.1 times per day had an estimated A1c of 7.56% (59 mmol/mol) and 6.71% (50 mmol/mol), respectively (p < 0.01). Worldwide, the lowest group and the highest groups scanned 3.4 times/day and 37.8 times/day and had an eA1c of 8.14% (65 mmol/mol) and 6.70% (50 mmol/mol), respectively (p < 0.01). For the scan groups in both populations, the time spent above 180 mg/dL decreased as the scan frequency increased. In both Brazil and around the world, as scan frequency increased, time in range (TIR) increased. In Brazil, TIR increased from 14.15 to 16.62 h/day (p < 0.01). Worldwide, TIR increased from 12.06 to 16.97 h/day (p < 0.01).

CONCLUSIONS

We conclude that Brazilian users have a high frequency of scans, more frequent than global data. Similarly to the world findings, increased scan frequency is associated with better glycemic control.

Influence of Metabolic Parameters and Treatment Method on OCT Angiography Results in Children with Type 1 Diabetes

AIM

To evaluate the influence of metabolic parameters and the treatment method in children with type 1 diabetes (T1D) on the optical coherence tomography angiography (OCTA) results as early markers of diabetic retinopathy (DR). Material and Methods. This prospective study enrolled 175 consecutive children with T1D. OCTA was performed using AngioVue (Avanti, Optovue). Whole superficial capillary vessel density (wsVD), fovea superficial vessel density (fsVD), parafovea superficial vessel density (psVD), whole deep vessel density (wdVD), fovea deep vessel density (fdVD), parafovea deep vessel density (pdVD), foveal thickness (FT), parafoveal thickness (PFT), and foveal avascular zone (FAZ) in superficial plexus were evaluated and analyzed in relation to individual characteristics, i.e., sex, weight, height, body mass index (BMI), and metabolic factors: current and mean value of glycated hemoglobin A1c (HbA1c). Furthermore, the analysis concerned the diabetes duration, age at the T1D onset, and type of treatment-multiple daily insulin injections (MDI) or continuous subcutaneous insulin infusion (CSII).

RESULTS

In the study group, we did not identify any patient with DR in fundus ophthalmoscopy. Age at the onset of diabetes correlated negatively with FAZ (r = -0.17, p < 0.05). The higher level of HbA1c corresponded to a decrease of wsVD (r = -0.13, p < 0.05). We found significantly lower fsVD (32.25 ± .1 vs. 33.98 ± .1, p < 0.01), wdVD (57.87 ± .1 vs. 58.64 ± .9, p < 0.01), and pdVD (60.60 ± .2 vs. 61.49 ± .1, p < 0.01) and larger FAZ area (0.25 ± .1 vs. 0.23 ± .1, p < 0.05) in the CSII vs. MDI group.

CONCLUSION

The metabolic parameters, age of the onset of diabetes, and treatment method affected the OCTA results in children with T1D. Further studies and observation of these young patients are needed to determine if these findings are important for early detection of DR or predictive of future DR severity.

The Correlation between Time in Range and Diabetic Microvascular Complications Utilizing Information Management Platform

BACKGROUND

In recent years, the time of blood glucose within the target range is a new research hotspot in blood glucose management. TIR is expected to be a novel indicator for evaluating the efficacy of glycemic control and predicting diabetic complications. However, its relationship with diabetic complications has not been fully elucidated.

OBJECTIVE

To explore the relationship between time in range (TIR) and glycosylated hemoglobin (HbA1C) through the information big data management platform. Possible association between TIR and diabetic microvascular complications (retinopathy, nephropathy, and neuropathy) was investigated, attempting to provide theoretical basis for the clinical application of TIR and to explore the TIR control scope suitable for diabetic patients.

METHODS

A total of 5,644 type 2 diabetic patients hospitalized in the Department of Endocrinology, the Second Affiliated Hospital of Nanchang University, were selected from April 2017 to June 2020. Fingertip capillary blood glucose monitoring (FCGM) was monitored for a total of 455,664 times, and patients who are nondiabetic, pregnant, or with diabetic ketosis were excluded. Patients with 7 blood glucose points monitored for at least three consecutive days were selected as subjects in the study. 1,895 males and 1,513 females with diabetes were included, with an average age of (59.74 ± 13.40) years old and an average course of disease of 8.28 ± 7.11 years. The proportion of time in range (TIR) (70∼180 mg/dl) within the target range and the correlation between TIR and HbA1C were analyzed, as well as the relationship between TIR and the risk of diabetic complications.

RESULTS

(1) The average of TIR and HbA1C was 49.65 ± 23.36% and 8.92 ± 2.49%, respectively, and was linearly correlated. With the decrease of TIR, HbA1C increased significantly, and the difference was statistically significant (P < 0.01, R ² = 0.458). The correlation coefficient of mean TIR with mean HbA1C was -0.626. (2) There were 836 patients diagnosed with diabetic nephropathy (DN). The difference of TIR value between DN and non-DN was significant (T = 2.250, P < 0.05). Risk assessment showed the lower the TIR was, the higher the risk of DN was. TIR less than 40% was a risk factor for DN (OR = 1.249, 95% CI: 0.915-1.375). (3) There were 1,296 patients diagnosed with diabetic peripheral neuropathy (DPN). The difference of TIR value between DPN and non-DPN was significant (T = 3.844, P < 0.01). TIR value less than 70% was a risk factor for DPN (OR = 1.030, 95% CI: 0.769-1.379). (4) There were 2,077 patients diagnosed with diabetic retinopathy (DR). The difference of TIR value between DPN and non-DPN was significant (T = 3.608, P < 0.01). TIR value less than 50% was a risk factor for DR (OR = 1.092, 95% CI: 0.898-1.264). Summary. TIR may serve as a reference index for short-term blood glucose control, strongly reflecting the clinical blood glucose regulation and predicting the risk of diabetic microvascular complications.

Glucose time in range and peripheral neuropathy in type 2 diabetes mellitus and chronic kidney disease

​OBJECTIVE: Compared with hemoglobin A1c (HbA1c), continuous glucose monitoring (CGM) may better capture risk of diabetes complications in patients with chronic kidney disease (CKD), including diabetic peripheral neuropathy (DPN). We hypothesized that glucose time in range (TIR), measured by CGM, is associated with DPN symptoms among participants with type 2 diabetes mellitus (type 2 DM) and moderate-to-severe CKD. ​RESEARCH DESIGN AND METHODS: We enrolled 105 people with type 2 DM treated with insulin or sulfonylurea, 81 participants with CKD (estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m²) and 24 matched control participants with eGFR ≥60 mL/min/1.73 m². Each participant wore a CGM for two 6-day periods. Calculated glycemic measures included TIR (glucose 70-180 mg/dL) and glucose management indicator (GMI). DPN symptoms were assessed using the Michigan Neuropathy Screening Instrument (MNSI) questionnaire, with a positive MNSI score defined as ≥2 symptoms. ​RESULTS: Participants with CKD had a mean age of 68 years, diabetes duration 20 years, eGFR 38 mL/min/1.73 m² and HbA1c 7.8%, 61 mmol/mol. Sixty-two participants reported ≥2 DPN symptoms, 51 (63%) with CKD and 11 (46%) controls. Less TIR and higher GMI were associated with higher risk of MNSI questionnaire score ≥2 (OR 1.25 (95% CI 1.02 to 1.52) per 10% lower TIR, and OR 1.79 (95% CI 1.05 to 3.04) per 1% higher GMI, adjusting for age, gender and race). Similar results were observed when analyses were restricted to participants with CKD. In contrast, there was no significant association of HbA1c with DPN symptoms. ​CONCLUSIONS: Symptoms of DPN were common among participants with long-standing type 2 DM and CKD. Lower TIR and higher GMI were associated with DPN symptoms.

Glycaemic variability: The under-recognized therapeutic target in type 1 diabetes care

Type 1 diabetes mellitus (T1DM) remains one of the most challenging long-term conditions to manage. Despite robust evidence to demonstrate that near normoglycaemia minimizes, but does not completely eliminate, the risk of complications, its achievement has proved almost impossible in a real-world setting. HbA1c to date has been used as the gold standard marker of glucose control and has been shown to reflect directly the risk of diabetes complications. However, it has been recognized that HbA1c is a crude marker of glucose control. Continuous glucose monitoring (CGM) provides the ability to measure and observe inter- and intraday glycaemic variability (GV), a more meaningful measure of glycaemic control, more relevant to daily living for those with T1DM. This paper reviews the relationship between GV and hypoglycaemia, and micro- and macrovascular complications. It also explores the impact on GV of CGM, insulin pumps, closed-loop technologies, and newer insulins and adjunctive therapies. Looking to the future, there is an argument that GV should become a key determinant of therapeutic success. Further studies are required to investigate the pathological and psychological benefits of reducing GV.

Impact of free-living pattern of sedentary behaviour on intra-day glucose regulation in type 2 diabetes

Purpose

To investigate how the pattern of sedentary behaviour affects intra-day glucose regulation in type 2 diabetes.

Methods

This intensive longitudinal study was conducted in 37 participants with type 2 diabetes (age, 62.8 ± 10.5 years). Glucose and sedentary behaviour/physical activity were assessed with a continuous glucose monitoring (Abbott FreeStyle Libre) and an activity monitor (activPAL3) for 14 days. Multiple regression models with generalised estimating equations (GEEs) approach were used to assess the associations of sedentary time and breaks in sedentary time with pre-breakfast glucose, pre-lunch glucose, pre-dinner glucose, post-breakfast glucose, post-lunch glucose, post-dinner glucose, bedtime glucose, the dawn phenomenon, time in target glucose range (TIR, glucose 3.9–10 mmol/L) and time above target glucose range (TAR, glucose > 10 mmol/L).

Results

Sedentary time was associated with higher pre-breakfast glucose (p = 0.001), pre-dinner glucose (p < 0.001), post-lunch glucose (p = 0.005), post-dinner glucose (p = 0.013) and the dawn phenomenon (p < 0.001). Breaks in sedentary time were associated with lower pre-breakfast glucose (p = 0.023), pre-dinner glucose (p = 0.023), post-breakfast glucose (p < 0.001) and the dawn phenomenon (p = 0.004). The association between sedentary time and less TIR (p = 0.022) and the association between breaks in sedentary time and more TIR (p = 0.001) were also observed.

Conclusions

Reducing sedentary time and promoting breaks in sedentary time could be clinically relevant to improve intra-day glucose regulation in type 2 diabetes.

Electronic supplementary material

The online version of this article (10.1007/s00421-019-04261-z) contains supplementary material, which is available to authorized users.

To What Target Hemoglobin A1c Level Would You Treat This Patient With Type 2 Diabetes?: Grand Rounds Discussion From Beth Israel Deaconess Medical Center

In the United States, 9.4% of all adults-and 25% of those older than 65 years-have diabetes. Diabetes is the leading cause of blindness and end-stage renal disease and contributes to both microvascular and macrovascular complications. The management of patients with type 2 diabetes (T2D) is a common and important activity in primary care internal medicine practice. Measurement of hemoglobin A1c (HbA1c) provides an estimate of mean blood sugar levels and glycemic control. The optimal HbA1c target level among various persons with T2D is a subject of controversy. Guidelines regarding HbA1c targets have yielded differing recommendations. In 2018, the American College of Physicians (ACP) published a guideline on HbA1c targets for nonpregnant adults with T2D. In addition to a recommendation to individualize HbA1c target levels, the ACP proposed a level between 7% and 8% for most patients. The ACP also advised deintensification of therapy for patients who have an HbA1c level lower than 6.5% and avoidance of HbA1c-targeted treatment for patients with a life expectancy of less than 10 years. This guidance contrasts with a recommendation from the American Diabetes Association to aim for HbA1c levels less than 7% for many nonpregnant adults and to consider a target of 6.5% if it can be achieved safely. Here, 2 experts, a diabetologist and a general internist, discuss how to apply the divergent guideline recommendations to a patient with long-standing T2D and a current HbA1c level of 7.8%.

Vascular Inflammation Risk Factors in Retinal Disease

Inflammation of the blood vessels that serve the central nervous system has been increasingly identified as an early and possibly initiating event among neurodegenerative conditions such as Alzheimer's disease and related dementias. However, the causal relevance of vascular inflammation to major retinal degenerative diseases is unresolved. Here, we describe how genetics, aging-associated changes, and environmental factors contribute to vascular inflammation in age-related macular degeneration, diabetic retinopathy, and glaucoma. We highlight the importance of mouse models in studying the underlying mechanisms and possible treatments for these diseases. We conclude that data support vascular inflammation playing a central if not primary role in retinal degenerative diseases, and this association should be a focus of future research.

Chinese clinical guidelines for continuous glucose monitoring (2018 edition)

Blood glucose monitoring is an important part of diabetes management. Continuous glucose monitoring (CGM) technology has become an effective complement to conventional blood glucose monitoring methods and has been widely applied in clinical practice. The indications for its use, the accuracy of the generated data, the interpretation of the CGM results, and the application of the results must be standardized. In December 2009, the Chinese Diabetes Society (CDS) drafted and published the first Chinese Clinical Guideline for Continuous Glucose Monitoring (2009 edition), providing a basis for the standardization of CGM in clinical application. Based on the updates of international guidelines and the increasing evidence of domestic studies, it is necessary to revise the latest CGM guidelines in China so that the recent clinical evidence can be effectively translated into clinical benefit for diabetic patients. To this end, the CDS revised the Chinese Clinical Guideline for Continuous Glucose Monitoring (2012 Edition) based on the most recent evidence from international and domestic studies.