Clinical Performance Evaluation of Continuous Glucose Monitoring Systems: A Scoping Review and Recommendations for Reporting

Recommendations on the Collection of Comparator Measurement Data in the Performance Evaluation of Continuous Glucose Monitoring Systems

While current systems for continuous glucose monitoring (CGM) are safe and effective, there is a high degree of variability between readings within and across CGM systems. In current CGM performance studies, device readings are compared with glucose concentrations obtained with a comparator ("reference") measurement procedure (usually capillary or venous glucose). However, glucose concentrations from capillary and venous samples can systematically differ, often by as much as 5 to 10%. Different comparator methods have shown biases of up to 8%, and comparator devices of the same brand can systematically differ by more than 5%. To address these issues, the Working Group on CGM of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC WG-CGM) recommends standardizing study procedures and the comparator measurement process in CGM performance studies. The majority of IFCC WG-CGM members recommend the use of capillary samples as reference, mainly because CGM readings will then be aligned better with results from self-monitoring of blood glucose (SMBG). Even with factory-calibrated CGM systems, manufacturers require CGM users to perform SMBG in some situations, eg, manual calibration, confirmation of extreme readings, discordance between CGM readings and symptoms of hyper- or hypoglycemia, or intermittent signal loss. Comparator devices should meet defined analytical performance specifications for bias and imprecision. Comparator bias can be reduced by retrospective correction of comparator values based on measurements with a method or materials of higher metrological order. Once manufacturers align CGM readings of their systems with comparator results using standardized procedures, variability across CGM systems will be reduced.

Accuracy of FreeStyle Libre 3 During Moderate-Intensity Continuous Aerobic Exercise at Different Phases of the Menstrual Cycle in Females with Type 1 Diabetes

Background: The use of continuous glucose monitoring (CGM) devices in managing type 1 diabetes (T1D) has been associated with improved glycemic control in individuals with T1D. A key challenge for CGMs, however, is achieving accuracy, particularly under conditions where glucose levels may fluctuate rapidly, such as during exercise. Another factor contributing to blood glucose variability is the menstrual cycle, during which hormonal fluctuations affect insulin sensitivity, leading to variable glucose levels. This study aimed to assess the accuracy of FreeStyle Libre-3 (FSL3) during continuous moderate-intensity aerobic exercise (CONT) performed in the follicular and luteal phases of the menstrual cycle in females with T1D. Methods: Participants underwent CONT sessions on a cycle ergometer, one in the follicular phase and one in the luteal phase of the menstrual cycle, at the Research Laboratory of the Faculty of Physiotherapy. Glucose levels were measured every 10 min using FSL3 and the YSI 2500 as a gold standard. Measurements began 20 min before CONT and continued for 20 min after exercise. Results: A total of 26 females (mean age 32.2 ± 6.1 years and mean duration of diabetes 16.4 ± 8.4 years) participated in this study. FSL3 showed significant differences compared with YSI glucose data for both phases of the menstrual cycle (about 16 mg/dL higher in FSL3). There were no differences in mean absolute relative differences (MARDs) between the follicular (16.06%) and luteal (16.43) phases. Moreover, exercise did not affect MARDs, which were 14.21% pre-exercise and 17.63% postexercise for the follicular phase and 14.95% pre-exercise and 17.71% postexercise for the luteal phase. Conclusions: The findings suggest that the accuracy of FSL3 is not affected by CONT, showing good accuracy levels in both phases of the menstrual cycle. Thus, this study is the first to examine the influence of the menstrual cycle and exercise on the accuracy of a CGM device. The study was also prospectively registered at clinicaltrials.gov (NCT06086067).

Feasibility of a Glucose Manipulation Procedure for the Standardized Performance Evaluation of Continuous Glucose Monitoring Systems

BACKGROUND

In continuous glucose monitoring (CGM) system performance studies, it is common to implement specific procedures for manipulating the participants' blood glucose (BG) levels during the collection of comparator BG measurements. Recently, such a procedure was proposed by a group of experts, and this study assessed its ability to produce combinations of BG levels and rates of change (RoCs) with certain characteristics.

METHODS

During three separate in-clinic sessions conducted over 15 days, capillary BG measurements were carried out every 15 minutes for 7 hours. Simultaneously, the participants' BG levels were manipulated by controlling food intake and insulin administration to induce transient hyperglycemia and hypoglycemia. Subsequently, the combinations of BG levels and RoCs were categorized into dynamic glucose regions distinguishing between rapidly increasing BG levels (Alert high), hyperglycemia (BG high), rapidly falling BG levels (Alert low), and hypoglycemia (BG low).

RESULTS

A total of 24 adult participants with type 1 diabetes were included. Capillary BG-RoC combinations showed 7.5% in the Alert high region, 13.3% in the BG high region, 9.8% in the Alert low region, and 11.0% in the BG low region. No adverse events related to the glucose manipulation procedure were documented.

CONCLUSIONS

As recommended by the experts, the percentage of data points in regions was ≥7.5%, demonstrating the procedure's feasibility. However, given that the recommendation for the alert high region was only barely achieved, we suggest optimizations to the procedure and definition of dynamic glucose regions to facilitate the procedures' adoption in standardized CGM performance evaluations.

Performance of Three Continuous Glucose Monitoring Systems in Adults With Type 1 Diabetes

BACKGROUND

The performance of continuous glucose monitoring (CGM) systems is difficult to compare due to different study designs and a lack of head-to-head studies. This study evaluated the performance of FreeStyle Libre 3 (FL3), Dexcom G7 (DG7), and Medtronic Simplera (MSP) against different comparator methods and during clinically relevant glycemic scenarios.

METHOD

Twenty-four adult participants with type 1 diabetes mellitus wore one sensor of each CGM system in parallel for up to 15 days. Sensors of DG7 and MSP were exchanged on days 5 and 8, respectively. Three 7-hour sessions with 15-minute comparator blood glucose-level measurements using YSI 2300 (YSI, venous), Cobas Integra (INT, venous), and Contour Next (CNX, capillary) were conducted on days 2, 5, and 15. Simultaneously, glucose-level excursions with transient hyperglycemia and hypoglycemia were induced according to a recently published testing procedure. The accuracy was evaluated using various metrics, including mean absolute relative differences (MARDs).

RESULTS

Compared with YSI data, the MARDs of FL3, DG7, and MSP were 11.6%, 12.0%, and 11.6%, respectively. Relative to the INT data, the corresponding MARDs were 9.5%, 9.9%, and 13.9%, respectively, and compared with CNX data, MARDs were 9.7%, 10.1%, and 16.6%, respectively. Both FL3 and DG7 showed better accuracy in the normoglycemic and hyperglycemic range, while MSP performed better in the hypoglycemic range.

CONCLUSIONS

Performance results of all CGM systems varied depending on the comparator method. However, across comparators FL3 and DG7 tended to be more accurate compared with MSP. All CGM systems showed a lower accuracy compared with previous studies, emphasizing the need for comprehensive study design guidelines.

Point-of-care testing: state-of-the art and perspectives

Point-of-care testing (POCT) is becoming an increasingly popular way to perform laboratory tests closer to the patient. This option has several recognized advantages, such as accessibility, portability, speed, convenience, ease of use, ever-growing test panels, lower cumulative healthcare costs when used within appropriate clinical pathways, better patient empowerment and engagement, and reduction of certain pre-analytical errors, especially those related to specimen transportation. On the other hand, POCT also poses some limitations and risks, namely the risk of lower accuracy and reliability compared to traditional laboratory tests, quality control and connectivity issues, high dependence on operators (with varying levels of expertise or training), challenges related to patient data management, higher costs per individual test, regulatory and compliance issues such as the need for appropriate validation prior to clinical use (especially for rapid diagnostic tests; RDTs), as well as additional preanalytical sources of error that may remain undetected in this type of testing, which is usually based on whole blood samples (i.e., presence of interfering substances, clotting, hemolysis, etc.). There is no doubt that POCT is a breakthrough innovation in laboratory medicine, but the discussion on its appropriate use requires further debate and initiatives. This collective opinion paper, composed of abstracts of the lectures presented at the two-day expert meeting "Point-Of-Care-Testing: State of the Art and Perspective" (Venice, April 4-5, 2024), aims to provide a thoughtful overview of the state-of-the-art in POCT, its current applications, advantages and potential limitations, as well as some interesting reflections on the future perspectives of this particular field of laboratory medicine.

Evaluating the precision and reliability of real-time continuous glucose monitoring systems in ambulatory settings: a systematic review

Background

Continuous glucose monitoring (CGM) with minimally invasive devices plays a key role in the assessment of daily diabetes management by detecting and alerting to potentially dangerous trends in glucose levels, improving quality of life, and treatment adherence. However, there is still uncertainty as to whether CGMs are accurate enough to replace self-monitoring of blood glucose, especially in detecting episodes of hypoglycemia.

Objectives

Evaluate clinical, numerical accuracy, sensitivity, and specificity of the CGM devices commercially available when compared to the reference standard of arterial or venous blood glucose.

Data sources and methods

We searched the Cochrane Library, PubMed, EMBASE, and LILACS databases. The quality was assessed with the Quality Assessment Diagnostic Accuracy Studies (QUADAS-2) tool. Clinical and numerical accuracy data were extracted. Sensitivity and specificity were calculated using Review Manager software. Heterogeneity was assessed by visual examination of forest plot and summary receiver operating characteristic curves.

Results

Twenty-two studies with a total of 2294 patients were included. The average mean absolute relative difference for overall diagnostic accuracy was 9.4%. None of the devices evaluated with ISO 15197:2013 criteria achieved values ⩾95% of measurements in the stipulated ranges in hypoglycemia (±15 mg/dL), but two devices did achieve it in hyperglycemia (±15%; Dexcom G6 and G7). Most of the devices evaluated with consensus error grids reached values above 99% in zones A and B only in overall accuracy and hyperglycemia. For hypoglycemia, the average sensitivity was 85.7% and specificity 95.33%, and for hyperglycemia was 97.45% and 96% respectively.

Conclusion

Currently available CGM devices have adequate accuracy for euglycemia and hyperglycemia; however, it is still inadequate for hypoglycemia, although it has improved over time.

Trial registration

Prospero registration ID CRD42023399767.

Consensus Considerations and Good Practice Points for Use of Continuous Glucose Monitoring Systems in Hospital Settings

Continuous glucose monitoring (CGM) systems provide frequent glucose measurements in interstitial fluid and have been used widely in ambulatory settings for diabetes management. During the coronavirus disease 2019 (COVID-19) pandemic, regulators in the U.S. and Canada temporarily allowed for CGM systems to be used in hospitals with the aim of reducing health care professional COVID-19 exposure and limiting use of personal protective equipment. As such, studies on hospital CGM system use have been possible. With improved sensor accuracy, there is increased interest in CGM usage for diabetes management in hospitals. Laboratorians and health care professionals must determine how to integrate CGM usage into practice. The aim of this consensus guidance document is to provide an update on the application of CGM systems in hospital, with insights and opinions from laboratory medicine, endocrinology, and nursing.

The Application of Continuous Glucose Monitoring Endpoints in Clinical Research: Analysis of Trends and Review of Challenges

INTRODUCTION

Considerable efforts to standardize continuous glucose monitoring (CGM) have occurred in recent years. The aim was to perform an analysis of clinical studies in clinicaltrials.gov to evaluate trends in CGM endpoint adoption.

METHODS

Clinicaltrials.gov was searched for studies of drugs, devices and combination products containing CGM terms posted from 2012 to 2023. 1269 studies were returned and 954 were excluded. 315 studies were divided into two periods (P1 [2012-2017] and P2 [2018-2023]) and differences analyzed using descriptive statistics and two-tailed t tests.

RESULTS

There was a significant 60.3% increase in total clinical studies from P1 (121) to P2 (194). Phase 2 and Phase 3 Studies both saw significant increases of 125.8 and 169.2%, respectively, in P2. Adult-only studies predominated in both periods, with a 40.4% increase in P2. Studies that included pediatric populations, although smaller in number, increased significantly. Most studies were nonindustry-funded, and studies in this category saw a significant 80.0% increase in P2. However, industry-only funded studies also increased significantly by 78.4% in P2 in the same period. Studies of type 1 diabetes (T1DM) and type 2 diabetes (T2DM) increased by 55.8% and 26.9%, respectively, but increases were not statistically significant. Studies of nondiabetes-related indications did increase significantly (233.3%). 27.6% of studies used CGM-derived metrics as primary endpoints (PE). Studies that used time in range (TIR) increased by 222.4% in P2, which was significant. Conversely studies that used mean amplitude of glycemic excursions (MAGE) decreased significantly by 71.3%.

CONCLUSION

Our data provide evidence of significant increases in the application of CGM endpoints in clinical studies in the last six years, including studies with TIR as the PE. Increases have been driven largely by academia, but our data show that industry is starting to follow suit. The significant increase in studies that included pediatrics is encouraging.

The Need for Standardization of Continuous Glucose Monitoring Performance Evaluation: An Opinion by the International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Continuous Glucose Monitoring

Metrics derived from continuous glucose monitoring (CGM) systems are often discordant between systems. A major cause is that CGM systems are not standardized; they use various algorithms and calibration methods, leading to discordant CGM readings across systems. This discordance can be addressed by standardizing CGM performance assessments: If manufacturers aim their CGM systems at the same target, then CGM readings will align across systems. This standardization should include the comparator device, sample origin, and study procedures. With better aligned CGM readings, CGM-derived metrics will subsequently also align better between systems.

Chen K, Cherñavvsky D, Clements M, Cote GL, Dhatariya KK, Drincic A, Ejskjaer N, Espinoza J, Fabris C, Fleming GA, Gabbay MAL, Galindo RJ, Gómez-Medina AM, Heinemann L, Hermanns N, Hoang T, Hussain S, Jacobs PG, Jendle J, Joshi SR, Koliwad SK, Lal RA, Leiter LA, Lind M, Mader JK, Maran A, Masharani U, Mathioudakis N, McShane M, Mehta C, Moon SJ, Nichols JH, O’Neal DN, Pasquel FJ, Peters AL, Pfützner A, Pop-Busui R, Ranjitkar P, Rhee CM, Sacks DB, Schmidt S, Schwaighofer SM, Sheng B, Simonson GD, Sode K, Spanakis EK, Spartano NL, Umpierrez GE, Vareth M, Vesper HW, Wang J, Wright E, Wu AH, Yeshiwas S, Zilbermint M, Kohn MA. The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors

INTRODUCTION

An error grid compares measured versus reference glucose concentrations to assign clinical risk values to observed errors. Widely used error grids for blood glucose monitors (BGMs) have limited value because they do not also reflect clinical accuracy of continuous glucose monitors (CGMs).

METHODS

Diabetes Technology Society (DTS) convened 89 international experts in glucose monitoring to (1) smooth the borders of the Surveillance Error Grid (SEG) zones and create a user-friendly tool-the DTS Error Grid; (2) define five risk zones of clinical point accuracy (A-E) to be identical for BGMs and CGMs; (3) determine a relationship between DTS Error Grid percent in Zone A and mean absolute relative difference (MARD) from analyzing 22 BGM and nine CGM accuracy studies; and (4) create trend risk categories (1-5) for CGM trend accuracy.

RESULTS

The DTS Error Grid for point accuracy contains five risk zones (A-E) with straight-line borders that can be applied to both BGM and CGM accuracy data. In a data set combining point accuracy data from 18 BGMs, 2.6% of total data pairs equally moved from Zones A to B and vice versa (SEG compared with DTS Error Grid). For every 1% increase in percent data in Zone A, the MARD decreased by approximately 0.33%. We also created a DTS Trend Accuracy Matrix with five trend risk categories (1-5) for CGM-reported trend indicators compared with reference trends calculated from reference glucose.

CONCLUSION

The DTS Error Grid combines contemporary clinician input regarding clinical point accuracy for BGMs and CGMs. The DTS Trend Accuracy Matrix assesses accuracy of CGM trend indicators.

Expanding the horizon of continuous glucose monitoring into the future of pediatric medicine

Glucose monitoring has rapidly evolved with the development of minimally invasive continuous glucose monitoring (CGM) using interstitial fluid. It is recommended as standard of care in the ambulatory setting, nearly replacing capillary glucose testing in those with access to CGM. The newest CGM devices continue to be smaller and more accurate, and integration with automated insulin delivery systems has further revolutionized the management of diabetes, leading to successful improvements in care and quality of life. Many studies confirm accuracy and application of CGM in various adult inpatient settings. Studies in adult patients increased during the COVID 19 Pandemic, but despite reassuring results, inpatient CGM use is not yet approved by the FDA. There is a lack of studies in inpatient pediatric settings, although data from the NICU and PICU have started to emerge. Given the exponential increase in the use of CGM, it is imperative that hospitals develop protocols for CGM use, with a need for ongoing implementation research. In this review we describe how CGM systems work, discuss benefits and barriers, summarize research in inpatient pediatric CGM use, explore gaps in research design along with emerging recommendations for inpatient use, and discuss overall CGM utility beyond outpatient diabetes management. IMPACT: Current CGM systems allow for uninterrupted monitoring of interstitial glucose excursions, and have triggered multiple innovations including automated insulin delivery. CGM technology has become part of standard of care for outpatient diabetes management, endorsed by many international medical societies, now with significant uptake, replacing capillary glucose testing for daily management in patients with access to CGM technology. Although CGM is not approved by the FDA for inpatient hospital use, studies in adult settings support its use in hospitals. More studies are needed for pediatrics. Implementation research is paramount to expand the role of CGM in the inpatient setting and beyond.

Performance of a Novel Continuous Glucose Monitoring Device in People With Diabetes

BACKGROUND

In this multicenter study, performance of a novel continuous glucose monitoring (CGM) system was evaluated.

METHODS

Adult participants with diabetes were included in the study. They each wore three sensors of the CGM system on the upper arms for up to 14 days. During four in-clinic visits, frequent comparison measurements with capillary blood glucose (BG) samples were performed. The primary endpoint was the 20/20 agreement rate (AR): the percentage of CGM readings within ±20 mg/dL (at BG values <100 mg/dL) or ±20% (at BG values ≥100 mg/dL) of the comparator. Further evaluations included mean absolute relative difference (MARD) and 20/20 AR in different BG ranges and across the wear time.

RESULTS

Data from 48 participants and 139 sensors were analyzed. During in-clinic sessions the 20/20 AR was 90.5% and the MARD was 9.2%. For BG ranges <70, 70-180, and >180 mg/dL, 20/20 AR was 94.3%, 89.0%, and 92.5%, respectively. At the beginning, middle, and end of sensor wear time, 20/20 AR was 92.8%, 91.5%, and 85.9%, respectively. The 14-day survival probability was 82.4%. Pain and bleeding after sensor insertion were within the expected range. Based on the study outcome, the use of the device is regarded as safe.

CONCLUSIONS

The system showed a good performance compared to capillary BG measurements. This level of accuracy could be shown over the entire measurement range, especially in the low glycemic range, and the whole wear time of the sensors. The results of this study are supporting a non-adjunctive use of the device.

Diabetes Technology Meeting 2023

Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 1 to November 4, 2023. Meeting topics included digital health; metrics of glycemia; the integration of glucose and insulin data into the electronic health record; technologies for insulin pumps, blood glucose monitors, and continuous glucose monitors; diabetes drugs and analytes; skin physiology; regulation of diabetes devices and drugs; and data science, artificial intelligence, and machine learning. A live demonstration of a personalized carbohydrate dispenser for people with diabetes was presented.

A Critical Discussion of Alert Evaluations in the Context of Continuous Glucose Monitoring System Performance

Many continuous glucose monitoring (CGM) systems provide functionality which alerts users of potentially unwanted glycemic conditions. These alerts can include glucose threshold alerts to call the user's attention to hypoglycemia or hyperglycemia, predictive alerts warning about impeding hypoglycemia or hyperglycemia, and rate-of-change alerts. A recent review identified 129 articles about CGM performance studies, of which approximately 25% contained alert evaluations. In some studies, real alerts were assessed; however, most of these studies retrospectively determined the timing of CGM alerts because not all CGM systems record alerts which necessitates manual documentation. In contrast to assessment of real alerts, retrospective determination allows assessment of a variety of alert settings for all three types of glycemic condition alerts. Based on the literature and the Clinical and Laboratory Standards Institute's POCT05 guideline, two common approaches to threshold alert evaluation were identified, one value-based and one episode-based approach. In this review, a critical discussion of the two approaches, including a post hoc analysis of clinical study data, indicates that the episode-based approach should be preferred over the value-based approach. For predictive alerts, fewer results were found in the literature, and retrospective determination of CGM alert timing is complicated by the prediction algorithms being proprietary information. Rate-of-change alert evaluations were not reported in the identified literature, and POCT05 does not contain recommendations for assessment. A possible approach is discussed including post hoc analysis of clinical study data. To conclude, CGM systems should record alerts, and the episode-based approach to alert evaluation should be preferred.

A Proposal for the Clinical Characterization of Continuous Glucose Monitoring Trend Arrow Accuracy

The assessment and characterization of trend accuracy, that is, the ability of a continuous glucose monitoring (CGM) system to correctly indicate the direction and rate of change (RoC) of glucose levels, has received comparatively little attention in the overall evaluation of CGM performance. As such, only few approaches that examine the trend accuracy have been put forward. In this article, we review existing approaches and propose the clinical trend concurrence analysis (CTCA) which is an adaptation of the conventional trend concurrence analysis. The CTCA is intended to directly evaluate the trend arrows displayed by the CGM systems by characterizing their agreement to suitably categorized comparator RoCs. Here, we call on manufactures of CGM systems to provide the displayed trend arrows for retrospective analysis. The CTCA classifies any deviations between the CGM trend and comparator RoC according to their risk for an adverse clinical event arising from a possibly erroneous treatment decision. For that, the existing rate error grid analysis and a specific set of trend arrow-based insulin dosing recommendations were used. The results of the CTCA are presented in an accessible graphical display and exemplified on data from three CGM systems. With this article, we hope to increase the awareness for the importance and challenges of assessing the accuracy of trend information displayed by CGM systems.

Importance of FDA-Integrated Continuous Glucose Monitors to Ensure Accuracy of Continuous Glucose Monitoring

Continuous glucose monitoring (CGM) has been shown to improve glycemic control and self-monitoring, as well as to reduce the risk of hypoglycemia. Integrated CGM (iCGM) FDA-cleared systems with published performance data are established nonadjunctive and accurate CGM tools that can directly inform decision-making in the treatment of diabetes (i.e., insulin dosing). Studies have assessed accuracy and safety data of CGMs that were eventually cleared for iCGM by the FDA and that informed the recommendation for their nonadjunctive use. Subsequent robust clinical trials and real-world studies demonstrated clinical effectiveness with improvements in a range of patient outcomes. In recent years, a number of non-iCGM-approved CGM devices have entered the market outside the United States worldwide. Some of these non-iCGM-approved CGM devices require additional user verification of blood glucose levels to be performed for making treatment decisions, termed adjunctive. Moreover, in many non-iCGM-approved CGM devices, accuracy studies published in peer-reviewed journals are scarce or have many limitations. Consequently, non-iCGM-approved CGM devices cannot be automatically perceived as having the same performance or quality standards than those approved for iCGM by the FDA. As a result, although these devices tend to cost less than iCGMs that carry FDA clearance and could therefore be attractive from the point of view of a health care payer, it must be emphasized that evaluation of costs should not be limited to the device (such as the usability preference that patients have for nonadjunctive sensors compared to adjunctive sensors) but to the wider value of the total benefit that the product provides to the patient.

Comparison of Point Accuracy Between Two Widely Used Continuous Glucose Monitoring Systems

BACKGROUND

Safe and effective self-management of glucose levels requires immediate access to accurate data. We assessed the point accuracy of the Dexcom G7 Continuous Glucose Monitoring System (Dexcom, Inc., San Diego, CA, USA) and FreeStyle Libre 3 (Abbott Diabetes Care, Alameda, CA, USA) sensors in a head-to-head comparison.

METHOD

Multicenter, single-arm, prospective, nonsignificant risk evaluation enrolled adults (≥ 18 years) with diagnosed type 1 diabetes (T1D) or type 2 diabetes (T2D). Accuracy was assessed by comparing sensor data to laboratory reference values Yellow Springs Instrument [YSI] and capillary blood glucose values. Outcome measures were differences in mean absolute relative difference (MARD), number and percentage of matched glucose pairs within ±20 mg/dL/±20 of reference values within glucose ranges: < 54, 54 to 69, 70 to 180, 181 to 250, > 250 mg/dL, and combined.

RESULTS

Data from 55 adults were included in the analysis. Analysis showed significantly lower MARD with the FreeStyle Libre 3 sensor vs the Dexcom G7 sensor (8.9% vs 13.6%, respectively, P < .0001) with a higher percentage of glucose values within ±20 mg/dL/±20 of reference (91.4% vs 78.6%). The MARD values for both continuous glucose monitoring (CGM) sensors were similar during the first 12 hours; however, the FreeStyle Libre 3 MARD was notably lower than the Dexcom G7 MARD during the next 12 hours (10.0% vs 15.1%, respectively, P < .0001) and throughout the study period.

CONCLUSIONS

The FreeStyle Libre 3 sensor was more accurate than the Dexcom G7 sensor in all metrics evaluated throughout the study period. This is the first head-to-head study to our knowledge that compares the flagship products currently in widespread use of the two largest CGM manufacturers.

[Features of glycemic variability in men with different types of obesity]

BACKGROUND

Obesity generally determines the metabolic basis for the development of type 2 diabetes. Therefore the analysis of glycemic variability in obese individuals, especially in its different phenotypes, acquires particular relevance.

AIM

To investigate the features of glycemic variability in men with different adipose tissue distribution topography within usual dietary conditions.

MATERIALS AND METHODS

The study enrolled 43 men aged 25-65 years. Group 1 (n=17) represented obese men with subcutaneous fat distribution (SFD) while group 2 (n=16) consisted of obese men with abdominal fat distribution (AFD) and group 3 (comparator) included 10 male subjects with normal body weight (NBW). A 2-day continuous glucose monitoring (CGM) under condition of usual diet, work and physical activity was performed in each study subject. A number of parameters, indices and ratios had been assessed describing glycemic variability (GV) for daytime (6.00-23.59) and night (0.00-5.59) hours.

RESULTS

Comparative analysis of key parameters and indices describing daytime and night GV in NBW and obese men without fat distribution adjustment did not reveal statistically significant differences. After fat distribution adjustment  significantly higher mean glucose levels, standard deviation of glycemic levels and coefficient of variation were found in AFD group; also statistically significant differences were revealed in CONGA index and J-index. An analysis of the LBGI and HBGI indices that are respectively reflecting the risks of hypo- and hyperglycemia showed that the LBGI index was higher in obese men with SFD while the НBGI index was higher in men with AFD. A comparative analysis of GV parameters showed that daytime indicators values were significantly higher relative to nighttime. However the ambiguous changes in the mean glucose levels was found between study groups. Specifically in NBW men daytime and nighttime glycemia didn't differ, whereas in AFD group there was a trend to decrease in night glucose levels (p = 0.08) while in men with SFD night decrease in glycemia became statistically significant (p=0.005).

CONCLUSION

Results of glycemic variability assessment in obese men suggest that abdominal and subcutaneous types of fat distribution are associated with specific features of carbohydrate metabolism and determine different risk levels for developing type 2 diabetes in patients with AFD and SFD.