Beyond A1C: exploring continuous glucose monitoring metrics in managing diabetes

Use of Glucose Monitoring Devices Among Adults with Diabetes in Germany: Results from Nationwide Surveys Conducted in 2017 and 2021/2022

Background: Devices for continuous glucose monitoring (CGM) have been developed to optimize blood glucose control and liberate people with diabetes from finger-prick glucose measurements. Since 2016, the devices have been reimbursed in Germany for people with diabetes receiving insulin therapy, resulting in their increased use among people with type 1 diabetes (T1D) and type 2 diabetes (T2D). We investigated the prevalence of CGM use and its associated factors among German adults with diabetes in 2017 and 2021/2022. Methods: Participants aged 18 years or older with diagnosed diabetes were identified from two nationwide population-based telephone surveys in 2017 (n = 1396) and 2021/2022 (n = 1456). Prevalence and dynamics of CGM use were examined overall and stratified by sociodemographic and diabetes-related characteristics. Factors associated with CGM use were obtained from logistic regression models. Results: The overall prevalence of CGM use was 8.2% in 2017 and 16.6% in 2021/2022. An increase in CGM use was observed across all the subgroups except for those without antidiabetic medications. CGM use increased from 31.1% to 75.4% in adults with T1D, from 6.3% to 13.6% in adults with T2D, and from 14.6% to 36.7% in all insulin users. In both surveys, younger age, insulin use, T1D, and reporting hypoglycemia were associated with CGM use. In addition, in 2017, higher education level and absence of obesity were associated with CGM use, whereas in 2021/2022, participation in the diabetes self-management education program and higher self-assessed quality of diabetes care were associated with CGM use. Conclusion: Among adults with diabetes in Germany, CGM use increased about twofold within 5 years, irrespective of sociodemographic factors. Educational inequality in CGM use diminished over time. The higher self-rated quality of diabetes care associated with the recent use of CGM provides further evidence to support its use among all adults with diabetes in Germany.

The Usefulness of the Glucose Management Indicator in Evaluating the Quality of Glycemic Control in Patients with Type 1 Diabetes Using Continuous Glucose Monitoring Sensors: A Cross-Sectional, Multicenter Study

The Glucose Management Indicator (GMI) is a biomarker of glycemic control which estimates hemoglobin A1c (HbA1c) based on the average glycemia recorded by continuous glucose monitoring sensors (CGMS). The GMI provides an immediate overview of the patient's glycemic control, but it might be biased by the patient's sensor wear adherence or by the sensor's reading errors. This study aims to evaluate the GMI's performance in the assessment of glycemic control and to identify the factors leading to erroneous estimates. In this study, 147 patients with type 1 diabetes, users of CGMS, were enrolled. Their GMI was extracted from the sensor's report and HbA1c measured at certified laboratories. The median GMI value overestimated the HbA1c by 0.1 percentage points (p = 0.007). The measurements had good reliability, demonstrated by a Cronbach's alpha index of 0.74, an inter-item correlation coefficient of 0.683 and an inter-item covariance between HbA1c and GMI of 0.813. The HbA1c and the difference between GMI and HbA1c were reversely associated (Spearman's r = -0.707; p < 0.001). The GMI is a reliable tool in evaluating glycemic control in patients with diabetes. It tends to underestimate the HbA1c in patients with high HbA1c values, while it tends to overestimate the HbA1c in patients with low HbA1c.

Glucose Abnormalities Detected by Continuous Glucose Monitoring in Very Old Adults With and Without Diabetes

OBJECTIVE

To characterize the prevalence of continuous glucose monitoring (CGM)-defined glucose abnormalities in a large, community-based population of very old adults (>75 years).

RESEARCH DESIGN AND METHODS

A cross-sectional analysis of 1,150 older adults with and without diabetes who attended the Atherosclerosis Risk in Communities Study (2021-2022). Diabetes was based on a self-reported diagnosis of diabetes by a health care provider, use of diabetes medication, or a hemoglobin A1c (HbA1c) ≥6.5%. Prediabetes was defined as an HbA1c of 5.7% to <6.5% and normoglycemia as an HbA1c of <5.7%. We analyzed CGM metrics, including mean glucose, measures of hyperglycemia, and the coefficient of variation, by diabetes status.

RESULTS

Of the 1,150 participants (mean age 83 years, 59% women, 26% who are Black), 35.1% had normoglycemia, 34.5% had prediabetes, and 30.4% had diabetes. The summary 24-h ambulatory glucose profile for participants with prediabetes was very similar to those with normoglycemia. No participants with normoglycemia or prediabetes had a CGM mean glucose >140 mg/dL, while 32.7% of participants with diabetes had a CGM mean glucose >140 mg/dL.

CONCLUSIONS

In very old adults with normal or prediabetes HbA1c, hyperglycemia detected by CGM was rare. This suggests that HbA1c adequately captures the burden of hyperglycemia for most people in this population.

Comprehensive Assessment of Neuropathy and Metabolic Parameters in Type 1 Diabetic Patients with or Without Using Continuous Glucose Sensors

The present study was conducted in type 1 diabetic (T1DM) patients to evaluate the metabolic and glycemic control as well as the manifestations of neuropathy. The impact of continuous glucose monitoring (CGM) on the measured parameters was also analyzed. A total of 61 T1DM patients (age: 42.5 ± 1.8 years, DM duration: 22.8 ± 1.6 years, mean ± SE) participated in the study. In total, 24 patients had CGM sensors and 37 did not. Cardiovascular autonomic neuropathy was assessed using cardiovascular reflex tests. Peripheral sensory function was evaluated by a Neurometer and calibrated tuning fork on the upper and lower limbs. Metabolic status was characterized by the determination of triglycerides, high-density lipoprotein (HDL), low-density lipoprotein (LDL), total cholesterol, and glycated haemoglobin (HbA1c). A positive correlation was found between HbA1c and triglyceride levels (r = 0.28, p < 0.05). CGM users and non-users differed in triglyceride (0.9 ± 0.1 vs. 1.24 ± 0.12 mmol/L, p < 0.05), HDL cholesterol (1.7 ± 0.1 vs. 1.4 ± 0.1 p < 0.05 mmol/L), and HbA1c (7.5 ± 0.2 vs. 8.3 ± 0.3%, p < 0.05) levels as well. Significant differences were found for the Valsalva ratio, Neurometer, and calibrated tuning fork results between CGM users and non-users. This study found a significant correlation between HbA1c and triglyceride levels in T1DM. CGM use resulted in improved metabolic parameters and less autonomic and sensory nerve damage. As a novel finding, CGM is presumed to prevent both micro-, and macrovascular complications and, by this way, potentially reducing mortality rates.

7. Diabetes Technology: Standards of Care in Diabetes-2025

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Newer Outpatient Diabetes Therapies and Technologies

New diabetes drugs such as glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and glucose-dependent insulinotropic peptide/GLP-1 RAs have emerged to show hemoglobin A1c (HbA1c) reduction, weight loss, and cardiovascular benefits. Similarly, sodium-glucose cotransporter 2 inhibitors' benefits span from HbA1c decrease to cardiovascular and renoprotective effects. Diabetes technology has expanded to include type 2 diabetes mellitus, with literature supporting its use in T2DM on any insulin regimen. Connected insulin pens and insulin delivery devices have opened new solutions to insulin users and automated insulin delivery systems have become the standard of care therapy for type 1 diabetes mellitus.

Primary care diabetes assessment when HbA1c and other measures of glycemia disagree

AIMS

Although diabetes management decisions in primary care are typically based largely on HbA1c, mismatches between HbA1c and other measures of glycemia that are increasingly more available present challenges to optimal management. This study aimed to assess a systematic approach to identify the frequency of mismatches of potential clinical significance amongst various measures of glycemia in a primary care setting.

METHODS

Following screening to exclude conditions known to affect HbA1c interpretation, HbA1c, and fructosamine were obtained and repeated after ∼90 days on 53 adults with prediabetes or type 2 diabetes. A subset of 13 participants with repeat labs wore continuous glucose monitoring (CGM) for 10 days.

RESULTS

As expected, HbA1c and fructosamine only modestly correlated (initial R2 = 0.768/repeat R2 = 0.655). The HbA1c/fructosamine mismatch frequency of ± 0.5% (using the following regression HbA1c = 0.015 *fructosamine + 2.994 calculated from the initial sample) was 27.0%. Of the 13 participants with CGM data, HbA1c and CGM-based Glucose Management Indicator correlated at R2 = 0.786 with a mismatch frequency of ± 0.5% at 46.2% compared to a HbA1c/fructosamine mismatch frequency of ± 0.5% at 30.8%.

CONCLUSIONS

HbA1c is frequently mismatched with fructosamine and CGM data. As each of the measures has strengths and weaknesses, the utilization of multiple different measures of glycemia may be informative for diabetes assessment in the clinical setting.

Future of Time-in-Range Goals in the Era of Advanced Hybrid Closed-Loop Automated Insulin Delivery Systems

The concept of maintaining blood glucose levels within the 70-180 mg/dL range, known as time-in-range, has raised questions regarding its representation of true physiological euglycemia. Some have speculated that focusing on the time spent within the 70-140 mg/dL range, introduced as time in tight range (TITR) through the International Consensus statement, could serve as a more precise metric for assessing normoglycemia in individuals with type 1 diabetes. This article delves into the current status of TITR as an emerging marker and explores how advanced hybrid closed-loop systems may offer a promising avenue for achieving this higher level of glycemic control.

Effects of continuous glucose monitoring on glycaemic control in type 2 diabetes: A systematic review and network meta-analysis of randomized controlled trials

AIMS

The aim of this study was to assess the efficacy of continuous glucose monitoring (CGM) versus self-monitoring of blood glucose (SMBG) in maintaining glycaemic control among people with type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

The protocol was registered in PROSPERO (CRD42023387583). PubMed, Web of Science, EMBASE and OVID databases were searched from 1 January 2000 until 31 December 2022 for randomized controlled trials comparing CGM with SMBG in glycaemic control among the outpatients with T2DM. The primary endpoint was glycated haemoglobin, while the secondary endpoints included time in range, time below range and time above range. Both traditional and network meta-analyses were conducted to explore the efficacy of CGM on glycaemic control in T2DM.

RESULTS

Eleven high-quality studies, involving 1425 individuals with T2DM, were identified. Traditional meta-analysis revealed that CGM exhibited a significantly decreased [mean difference (MD): -0.31, 95% confidence interval (CI) (-0.45, -0.18)], time above range [MD: -9.06%, 95% CI (-16.00, -2.11)], time below range [MD: -0.30%, 95% CI (-0.49, -0.12)] and a significantly increased time in range [MD: 8.49%, 95% CI (3.96, 13.02)] compared with SMBG. The network meta-analysis showed that real-time CGM can improve the glycaemic control of patients with T2DM to the most extent.

CONCLUSIONS

CGM could provide T2DM with greater benefits in glycaemic management compared with SMBG, particularly in patients using real-time CGM. These findings provide an updated perspective on previous research and offer guidance for CGM use in T2DM.