Accuracy of a 14-Day Factory-Calibrated Continuous Glucose Monitoring System With Advanced Algorithm in Pediatric and Adult Population With Diabetes

Calibration algorithms for continuous glucose monitoring systems based on interstitial fluid sensing

Continuous glucose monitoring (CGM) is of great importance to the treatment and prevention of diabetes. As a proven commercial technology, electrochemical glucose sensor based on interstitial fluid (ISF) sensing has high sensitivity and wide detection range. Therefore, it has good promotion prospects in noninvasive or minimally-invasive CGM system. However, since there are concentration differences and time lag between glucose in plasma and ISF, the accuracy of this type of sensors are still limited. Typical calibration algorithms rely on simple linear regression which do not account for the variability of the sensitivity of sensors. To enhance the accuracy and stability of CGM based on ISF, optimization of calibration algorithm for sensors is indispensable. While there have been considerable researches on improving calibration algorithms for CGM, they have still received less attention. This article reviews the problem of typical calibration and presents the outstanding calibration algorithms in recent years. Finally, combined with existing research and emerging sensing technologies, this paper makes an outlook on the future calibration algorithms for CGM sensors.

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.

Performance of Continuous Glucose Monitoring in Patients With Acute Respiratory Failure: A Prospective, Single-Center Observational Study

OBJECTIVE

Continuous glucose monitoring (CGM) may have benefits in achieving glycemic control in critically ill patients. The aim of this study was to assess the accuracy of the Freestyle Libre H (professional version similar to the Libre Pro) in patients with acute respiratory failure (ARF) in the intensive care unit (ICU).

METHODS

Fifty-two adult patients with ARF were selected. The performance of CGM was evaluated using the arterial blood glucose (aBG) and point-of-care (POC) glucose levels as the reference values. Numerical accuracy was evaluated by the mean absolute relative difference, Bland-Altman analysis, %15/15 (the percentage of CGM values within 15 mg/dL or 15% of reference values <100 or >100 mg/dL, respectively), %20/20, and %30/30. Clinical accuracy was assessed using the Clarke error grid analysis.

RESULTS

A total of 519 and 1504 pairs of aBG/CGM and POC/CGM glucose values were analyzed. The mean absolute relative difference values were 13.8% and 14.7%, respectively. The mean deviations of the Bland-Altman analysis were 0.82 mmol/L and 0.81 mmol/L. The proportions of CGM values within %15/15, %20/20, and %30/30 of the aBG values were 62.6%, 75.5%, and 92.4%, respectively; those within %15/15, %20/20, and %30/30 of the POC values were 57.1%, 72.9%, and 88.7%, respectively. The Clarke error grid analysis showed that 97.8% and 99.3% of the values were located in zone A + B. Additionally, the accuracy of CGM was not affected by general patient factors.

CONCLUSION

This study demonstrated that the accuracy of CGM in patients with ARF is lower than that in most outpatients and it is not affected by general patient factors. Whether CGM is beneficial to glucose management in the intensive care unit needs further evaluation.

Impact in real-world of intermittent-scanned continuous glucose monitoring with alarms on hypoglycemia and its recognition in type 1 diabetes

BACKGROUND

Recent studies have demonstrated that real-time CGM use reduce the incidence severe hypoglycemic events and impaired awareness of hypoglycemia (IAH) However, there are few real-world studies evaluating the effect of intermittently scanned continuous glucose monitoring (isCGM) on hypoglycemic episodes and hypoglycemia unawareness (IAH). The present study was designed to cover this research-practice gap.

METHODS

This is a real-world, observational, prospective cohort study with 2 years of follow-up in which 60 subjects with T1D who experienced frequent hypoglycemic events were included. All the patients were invited to use isCGM type Abbott FreeStyle Libre 2® on a continuous basis for 2 years. Glucometric parameters were obtained during the initial 2 weeks using isCGM and compared with data collected for the same period at 1 year and at the end of follow-up. The IAH was evaluated using the Clarke questionnaire, and to assess psychological aspects related to hypoglycemia the Hypoglycemia Fear Survey (HFS) was used.

RESULTS

After 2-years of follow-up using isCGM, we observed a decrease in glucose variability (40.3 ± 0.8 % vs. 37.1 ± 0.9 %, p = 0.003), time in low glucose range (54-69 mg/dL) (5.2 ± 0.4 % vs. 3.6 ± 0.3 %, p = 0.001), time in very low glucose range (<54 mg/dL) (3.2 ± 0.5 % vs. 0.8 ± 0.2 %, p < 0.001), less events related to low glucose levels (10.6 ± 1.1 vs 8.0 ± 1.0, p = 0.042) and a short duration of hypoglycemia episodes (106.1 ± 5.9 min vs. 85.7 ± 5.7 min, p = 0.008). In addition, participants presented a reduction of 47 % in the frequency of IAH, assessed by the Clarke questionnaire scores (24.6 % vs. 11.6 %, p = 0.034), as well as hypoglycemia fear (77.8 ± 2.4 vs 68.2 ± 2.1, p < 0.001). Furthermore, a reduction in total insulin dose was also observed (0.64 ± 0.30 UI/Kg/day vs 0.56 ± 0.11 UI/Kg/day, p = 0.018).

CONCLUSIONS

In the real-world, long-term use of isCGM could reduce both hypoglycemic episodes and IAH in people with T1D.

Differences Between Glycated Hemoglobin and Glucose Management Indicator in Real-Time and Intermittent Scanning Continuous Glucose Monitoring in Adults With Type 1 Diabetes

BACKGROUND

This study demonstrates the difference between glucose management indicator (GMI) and glycated hemoglobin (HbA1c) according to sensor mean glucose and HbA1c status using 2 continuous glucose monitoring (CGM) sensors in people with type 1 diabetes.

METHODS

A total of 275 subjects (117 Dexcom G6 [G6] and 158 FreeStyle Libre 1 [FL]) with type 1 diabetes was included. The G6 and FL sensors were used, respectively, over 90 days to analyze 682 and 515 glycemic profiles that coincide with HbA1c.

RESULTS

The mean HbA1c was 6.6% in Dexcom G6 and 7.2% in FL profiles. In G6 profiles, GMI was significantly higher than HbA1c irrespective of mean glucose (all P < .001, mean difference: 0.58% ± 0.49%). The GMI was significantly higher than the given HbA1c when HbA1c was below 8.0% (all P < .001). The discordance was the highest at 0.9% for lower HbA1c values (5.0%-5.9%). The proportion of discordance >0.5% improved from 60.1% to 30.9% when using the revised GMI equation in G6 profiles. In FL profile, the overall mean difference between GMI and HbA1c was 0 (P = .966). The GMI was significantly lower by 0.9% than HbA1c of 9.0% to 9.9% and higher by 0.5% in HbA1c of 5.0% to 5.9% (all P < .001).

CONCLUSIONS

The GMI is overestimated in G6 users, particularly those with well-controlled diabetes, but the GMI and HbA1c discordance improved with a revised equation from the observed data. The FL profile showed greater discordance for lower HbA1c levels or higher HbA1c levels.

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.

Switching from Intermittently Scanned Continuous Glucose Monitoring to Real-Time Continuous Glucose Monitoring with a Predictive Urgent Low Soon Alert Reduces Exposure to Hypoglycemia

Differences in the effectiveness of real-time continuous glucose monitoring (rtCGM) and intermittently scanned continuous glucose monitoring (isCGM) in type 1 diabetes (T1D) are reported. The impact on percent time in range of switching from an isCGM with glucose threshold-based optional alerts only (FreeStyle Libre 2 [FSL2]) to an rtCGM (Dexcom G7) with an urgent low soon predictive alert was assessed, alongside other secondary outcomes including hemoglobin A1c (HbA1c) and other continuous glucose monitoring metrics. Adults with T1D using FSL2 were switched to Dexcom G7 for 12 weeks. HbA1c and continuous glucose data during FSL2 and Dexcom G7 use were compared. Data from 29 participants (aged 44.8 ± 16.5 years, 12 male and 17 female) were analyzed. After switching to rtCGM, participants spent less time in hypoglycemia below 3.9 mmol/L (70 mg/dL) (3.0% [1.0%, 5.0%] vs. 2.0% [1.0%, 3.0%], P = 0.006) and had higher percentage achievement of time below 3.9 mmol/L (70 mg/dL) of <4% (55.2% vs. 82.8%, P = 0.005). Coefficient of variation was lower (39.3 ± 6.6% vs. 37.2 ± 5.6%, P = 0.008). In conclusion, adults with T1D who switched from isCGM to rtCGM may benefit from reduced exposure to hypoglycemia and glycemic variability.

Accuracy of FreeStyle Libre flash glucose monitoring in patients with type 2 diabetes who migrated from highlands to plains

BACKGROUND

The FreeStyle Libre flash glucose monitoring (FGM) system entered the Chinese market in 2017 to complement the self-monitoring of blood glucose. Due to its increased usage in clinics, the number of studies investigating its accuracy has increased. However, its accuracy has not been investigated in highland popu-lations in China.

AIM

To evaluate measurements recorded using the FreeStyle Libre FGM system compared with capillary blood glucose measured using the enzyme electrode method in patients with type 2 diabetes (T2D) who had migrated within 3 mo from highlands to plains.

METHODS

Overall, 68 patients with T2D, selected from those who had recently migrated from highlands to plains (within 3 mo), were hospitalized at the Department of Endocrinology from August to October 2017 and underwent continuous glucose monitoring (CGM) with the FreeStyle Libre FGM system for 14 d. Throughout the study period, fingertip capillary blood glucose was measured daily using the enzyme electrode method (Super GL, China), and blood glucose levels were read from the scanning probe during fasting and 2 h after all three meals. Moreover, the time interval between reading the data from the scanning probe and collecting fingertip capillary blood was controlled to < 5 min. The accuracy of the FGM system was evaluated according to the CGM guidelines. Subsequently, the factors influencing the mean absolute relative difference (MARD) of this system were analyzed by a multiple linear regression method.

RESULTS

Pearson's correlation analysis showed that the fingertip and scanned glucose levels were positively correlated (R = 0.86, P = 0.00). The aggregated MARD of scanned glucose was 14.28 ± 13.40%. Parker's error analysis showed that 99.30% of the data pairs were located in areas A and B. According to the probe wear time of the FreeStyle Libre FGM system, MARD1 d and MARD2-14 d were 16.55% and 14.35%, respectively (t = 1.23, P = 0.22). Multiple stepwise regression analysis showed that MARD did not correlate with blood glucose when the largest amplitude of glycemic excursion (LAGE) was < 5.80 mmol/L but negatively correlated with blood glucose when the LAGE was ≥ 5.80 mmol/L.

CONCLUSION

The FreeStyle Libre FGM system has good accuracy in patients with T2D who had recently migrated from highlands to plains. This system might be ideal for avoiding the effects of high hematocrit on blood glucose monitoring in populations that recently migrated to plains. MARD is mainly influenced by glucose levels and fluctuations, and the accuracy of the system is higher when the blood glucose fluctuation is small. In case of higher blood glucose level fluctuations, deviation in the scanned glucose levels is the highest at extremely low blood glucose levels.

The Influence of Gestational Diabetes Mellitus on Maternal and Neonatal Outcomes: A Retrospective Study in Rzeszów, Poland

BACKGROUND Gestational diabetes mellitus (GDM) affects 5.8-12.9% of pregnant women, while pre-gestational diabetes mellitus (PGDM) affects 0.4-1.1%. GDM increases the risk of perinatal complications and long-term health issues. This retrospective study from a single centre in Rzeszów, Poland aimed to evaluate maternal and neonatal outcomes of pregnancy of 65 women with gestational diabetes mellitus. MATERIAL AND METHODS The study group consisted 65 women with GDM. The control group consisted 60 women without. GDM were diagnosed with carbohydrate metabolism disorders during pregnancy based on the results of the oral glucose tolerance test (OGTT). Methods of evaluation of the mothers: age, body mass before pregnancy, body height, body mass index (BMI), gravidity, parity, the number of miscarriages, length of stay (LOS) of mother, gestational weight gain (GWG), duration of pregnancy, type of delivery, treatment of diabetes. Methods of evaluation of the child: LOS, birth weight, Apgar points. RESULTS Women with diabetes stayed in hospital longer than women without, similarly applies the length of stay (LOS) of the child (p<0.001). It turned out that the women with GDM were significantly more likely to deliver by caesarean section (CS) (p=0.024) and these women most often had gestational weight gain (GWG) within the recommended range (p<0.001). Body mass index (BMI) before pregnancy was significantly higher in the women with GDM (p=0.023). CONCLUSIONS The above study confirms that the occurrence of GDM has an undoubted impact on prolonged LOS of the mother and child, more frequent CS delivery and normal GWG.

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.

Effect of Arterialization on Venous Blood Glucose Concentrations and Implications for Observed Continuous Glucose Monitoring Accuracy

Background: Heating of the arm and/or hand ("arterialization") is sometimes used in continuous glucose monitoring (CGM) performance studies with the reported aim of reducing differences between venous and capillary glucose concentrations. In this study, the effect of heating on venous glucose concentrations and CGM accuracy was investigated. Methods: A heating pad set to 50°C (122°F) was used with 20 participants to heat either the dominant or nondominant arm and hand. Venous and capillary samples were obtained every 15 min on both arms throughout each of three 6-h glucose challenges. CGM sensors were worn on each upper arm for each of the three visits. Results: Heating of the arm led to a median increase in venous glucose concentrations of +1.4%. No similar effect on capillary concentrations was observed. As a result, the median capillary to venous difference decreased from +5.9% in the nonheated arm to +4.2% in the heated arm. CGM accuracy observed in this study was affected by the selection of heated venous, nonheated venous, or capillary glucose concentrations as comparator data. The heating effect was more pronounced with rapidly decreasing glucose concentrations. Temperatures on the skin did not exceed 40°C (104°F). No adverse events or protocol deviations were associated with the use of the heating pad. Conclusions: Heating of the arm led to a small increase in venous glucose concentrations, but venous concentrations did not reach the level of capillary glucose concentrations. CGM accuracy observed in this study varied depending on the selected comparator data. This study was registered at the German Clinical Trials Register (DRKS00031197).

Comparator Data Characteristics and Testing Procedures for the Clinical Performance Evaluation of Continuous Glucose Monitoring Systems

Comparing the performance of different continuous glucose monitoring (CGM) systems is challenging due to the lack of comprehensive guidelines for clinical study design. In particular, the absence of concise requirements for the distribution of comparator (reference) blood glucose (BG) concentrations and their rate of change (RoC) that are used to evaluate CGM performance, impairs comparability. For this article, several experts in the field of CGM performance testing have collaborated to propose characteristics of the distribution of comparator measurements that should be collected during CGM performance testing. Specifically, it is proposed that at least 7.5% of comparator BG concentrations are <70 mg/dL (3.9 mmol/L) and >300 mg/dL (16.7 mmol/L), respectively, and that at least 7.5% of BG-RoC combinations indicate fast BG changes with impending hypo- or hyperglycemia, respectively. These proposed characteristics of the comparator data can facilitate the harmonization of testing conditions across different studies and CGM systems and ensure that the most relevant scenarios representing real-life situations are established during performance testing. In addition, a study protocol and testing procedure for the manipulation of glucose levels are suggested that enable the collection of comparator data with these characteristics. This work is an important step toward establishing a future standard for the performance evaluation of CGM systems.

Glucose values from the same continuous glucose monitoring sensor significantly differ among readers with different generations of algorithm

Continuous glucose monitoring (CGM) values obtained from CGM systems using the same sensor but with different internal algorithms (the first- and third-generation FreeStyle Libre (1st-gen-libre and 3rd-gen-libre, respectively)) were compared. We used 19,819 paired and simultaneously measured CGM values of 13 patients with diabetes. The average CGM value was significantly higher (P < 0.0001) and the time below range (CGM value < 70 mg/dL) was significantly lower (P < 0.0001) with the 3rd-gen-libre than with the 1st-gen-libre. There was a significant correlation (P < 0.0001) between the CGM values of the 3rd-gen-libre (y-axis, mg/dL) and 1st-gen-libre (x-axis, mg/dL) using the following formula: y = 0.9728x + 10.024. On assessing the association between glycated hemoglobin (HbA1c (%), y-axis) and the average CGM values (x-axis, mg/dL) by applying the obtained equation to previously reported 1st-gen-libre data and converting it to 3rd-gen-libre data, we obtained the equation y = 0.02628x + 3.233, indicating that the glucose management indicator reported in the West may be underestimated compared with the laboratory-measured HbA1c in the Japanese population. Glucose values from the same sensor were found to be significantly different between readers with different algorithms, and the calculation of CGM-related indices may need to be individualized for each device.

Non-invasive blood glucose estimation method based on the phase delay between oxy- and deoxyhemoglobin using visible and near-infrared spectroscopy

Significance

Many researchers have attempted to estimate blood glucose levels (BGLs) noninvasively using near-infrared (NIR) spectroscopy. However, the optical absorption change induced by blood glucose is weak in the NIR region and often masked by interference from other components such as water and hemoglobin.

Aim

Instead of using direct optical absorption by glucose, this study proposes an index calculated from oxy- and deoxyhemoglobin signals that shows a good correlation with BGLs while using conventional visible and NIR spectroscopy.

Approach

The metabolic index, which is based on tissue oxygen consumption, was derived through analytical methods and further verified and reproduced in a series of glucose challenge experiments. Blood glucose estimation units were prototyped by utilizing commercially available smart devices.

Results

Our experimental results showed that the phase delay between the oxy- and deoxyhemoglobin signals in near-infrared spectroscopy correlates with BGL measured by a conventional continuous glucose monitor. The proposed method was also confirmed to work well with visible spectroscopy systems based on smartphone cameras. The proposed method also demonstrated excellent repeatability in results from a total of 19 oral challenge tests.

Conclusions

This study demonstrated the feasibility of non-invasive glucose monitoring using existing photoplethysmography sensors for pulse oximeters and smartwatches. Evaluating the proposed method in diabetic or unhealthy individuals may serve to further increase its practicality.

Continuous glucose monitoring for automatic real-time assessment of eating events and nutrition: a scoping review

Background

Accurate dietary assessment remains a challenge, particularly in free-living settings. Continuous glucose monitoring (CGM) shows promise in optimizing the assessment and monitoring of ingestive activity (IA, i.e., consumption of calorie-containing foods/beverages), and it might enable administering dietary Just-In-Time Adaptive Interventions (JITAIs).

Objective

In a scoping review, we aimed to answer the following questions: (1) Which CGM approaches to automatically detect IA in (near-)real-time have been investigated? (2) How accurate are these approaches? (3) Can they be used in the context of JITAIs?

Methods

We systematically searched four databases until October 2023 and included publications in English or German that used CGM-based approaches for human (all ages) IA detection. Eligible publications included a ground-truth method as a comparator. We synthesized the evidence qualitatively and critically appraised publication quality.

Results

Of 1,561 potentially relevant publications identified, 19 publications (17 studies, total N = 311; for 2 studies, 2 publications each were relevant) were included. Most publications included individuals with diabetes, often using meal announcements and/or insulin boluses accompanying meals. Inpatient and free-living settings were used. CGM-only approaches and CGM combined with additional inputs were deployed. A broad range of algorithms was tested. Performance varied among the reviewed methods, ranging from unsatisfactory to excellent (e.g., 21% vs. 100% sensitivity). Detection times ranged from 9.0 to 45.0 min.

Conclusion

Several CGM-based approaches are promising for automatically detecting IA. However, response times need to be faster to enable JITAIs aimed at impacting acute IA. Methodological issues and overall heterogeneity among articles prevent recommending one single approach; specific cases will dictate the most suitable approach.

The Performance of Freestyle Libre Pro Flash Continuous Glucose Monitoring in Hospitalized Patients Treated with an Intravenous Insulin Infusion for Acute Prednisolone-Induced Hyperglycemia

Few studies have evaluated the performance of flash glucose monitoring in hospitalized patients requiring intravenous insulin therapy. In this prospective study, an intravenous insulin infusion was adjusted hourly using flash glucose monitoring in hospitalized adults with prednisolone-associated hyperglycemia. The difference in paired point of care (POC) and flash glucose measurements and risk of severe hyper- or hypoglycemia (assessed by Clarke error grid analysis) were assessed. Glucose concentration measured by flash glucose monitoring was lower than POC glucose (mean difference 1.5 mmol/L [27 mg/dL], p < 0.001); however, mean POC glucose was within the target range (9.1 ± 4.1 mmol/L [164 ± 72 mg/dL]) and 97.8% of glucose measurements were within Zone A and B on error grid analysis. Flash glucose monitoring could be used in combination with POC glucose monitoring to minimize the frequency of finger prick blood glucose levels in hospitalized patients prescribed an intravenous insulin infusion.

Advances in screening and diagnostic lab-on-chip tools for gynaecological cancers - a review

Gynaecological cancers are a major global health concern due to the lack of effective screening programmes for ovarian and endometrial cancer, for example, and variable access to vaccination and screening tests for cervical cancer in many countries. Recent research on portable and cost-effective lab-on-a-chip (LoC) technologies show promise for mass screening and diagnostic procedures for gynaecological cancers. However, most LoCs for gynaecological cancer are still in development, with a need to establish and clinically validate factors such as the type of biomarker, sample and method of detection, before patient use. Multiplex approaches, detecting a panel of gynaecological biomarkers in a single LoC, offer potential for more reliable diagnosis. This review highlights the current research on LoCs for gynaecological cancer screening and diagnosis, emphasizing the need for further research and validation prior to their widespread adoption in clinical practice.

Care of Young Children With Diabetes in the Childcare and Community Setting: A Statement of the American Diabetes Association

Diabetes management in children extends from the home to other settings where children spend a significant portion of their waking hours. For young children (generally, aged <5 years) with diabetes, this includes childcare centers. Given their age and developmental stage, young children require a carefully thought-out, proactive diabetes care plan for the childcare setting, developed jointly by the health care provider and parents/guardians, and implemented by childcare staff. In the U.S., federal laws and some state laws protect the rights of children with diabetes in childcare and other settings to ensure they receive appropriate assistance with the diabetes management and care. This American Diabetes Association (ADA) Statement addresses the legal rights of children in the childcare setting, outlines the current best practices for diabetes care, and provides resources and responsibilities for parents/guardians, childcare providers, and health care providers. The ADA intends for these tools and information to support the health and well-being of young children with diabetes and offer helpful guidance to those caring for them.

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

The use of different approaches for design and results presentation of studies for the clinical performance evaluation of continuous glucose monitoring (CGM) systems has long been recognized as a major challenge in comparing their results. However, a comprehensive characterization of the variability in study designs is currently unavailable. This article presents a scoping review of clinical CGM performance evaluations published between 2002 and 2022. Specifically, this review quantifies the prevalence of numerous options associated with various aspects of study design, including subject population, comparator (reference) method selection, testing procedures, and statistical accuracy evaluation. We found that there is a large variability in nearly all of those aspects and, in particular, in the characteristics of the comparator measurements. Furthermore, these characteristics as well as other crucial aspects of study design are often not reported in sufficient detail to allow an informed interpretation of study results. We therefore provide recommendations for reporting the general study design, CGM system use, comparator measurement approach, testing procedures, and data analysis/statistical performance evaluation. Additionally, this review aims to serve as a foundation for the development of a standardized CGM performance evaluation procedure, thereby supporting the goals and objectives of the Working Group on CGM established by the Scientific Division of the International Federation of Clinical Chemistry and Laboratory Medicine.

Narrative review of the role of technology in pediatric diabetes: from testing blood glucose to subcutaneous automated therapy and hope for cure

Background and Objective

Type 1 diabetes, the most common cause of diabetes in pediatrics, is defined by the hyperglycemia that results from the permanent autoimmune damage to the pancreas. The Diabetes Control and Complications Trial (DCCT) demonstrated that strict glycemic control targeting lower HbA1c goals can both delay the onset and progression of its complications that include diabetic neuropathy, nephropathy, retinopathy, and increased cardiovascular events. Our primary objective is to review the literature available regarding the technology applied for the treatment of diabetes, not only aiding patients' quality of life but addressing its effects on hypoglycemia and reduced risk of the long-term complications. It will synthesize the evolution of glucose monitoring devices; the development of insulin: from animal to recombinant engineering, smart insulin in the future; the development of algorithm-driven insulin delivery devices, the closed loop system/artificial pancreas; and the future utilization of technology to support islet cell transplant with the goal of a long-term cure. Emphasis will be made on what is known about the impact on its outcomes in children and adolescents.

Methods

A literature search was conducted using PubMed for publications from 1985 to present. Keywords used: type 1 diabetes, children, adolescents, pediatrics, continuous glucose monitoring (CGM), insulin pumps. Referenced articles include other reviews, current care guidelines as supported by cross sectional studies, cohort studies and randomized clinical trials.

Key Content and Findings

Understanding the pathophysiology of type 1 diabetes has led to the design of technology that facilitates glucose monitoring and insulin administration in a personalized manner. The current technology has improved outcomes and quality of life by decreasing hypoglycemic events and decreasing risk of long-term metabolic complications. Barriers remain, for children and adults, often driven by patient's preference as well as their understanding of the limitations of what they are wearing.

Conclusions

With the progressive evolution of this technology, it is now realistic to lower the burden of diabetes self-management while reducing hypoglycemia and risk of complications that otherwise impact daily life from academics, physical activity, career choices and even life expectancy.

Assessment of the FreeStyle Libre 2 interstitial glucose monitor in hypo- and euglycemic cats

BACKGROUND

Continuous glucose monitoring systems have been validated for eu- and hyperglycemic cats. The FreeStyle Libre 2 (FSL2) is sufficiently accurate in people during hypoglycemia to guide critical treatment decisions without confirmation of blood glucose concentration (BG).

OBJECTIVES

Assess FSL2 accuracy in cats with hypoglycemia.

ANIMALS

Nine healthy, purpose-bred cats.

METHODS

Hyperinsulinemic-hypoglycemic clamps were performed by IV infusion of regular insulin (constant rate) and glucose (variable rate). Interstitial glucose concentration (IG), measured by FSL2, was compared to BG measured by AlphaTrak2. Data were analyzed for all paired measurements (n = 364) and separately during stable BG (≤1 mg/dL/min change over 10 minutes). Pearson's r test, Bland-Altman test, and Parkes Error Grid analysis respectively were used to determine correlation, bias, and clinical accuracy (P < .05 considered significant).

RESULTS

Overall, BG and IG correlated strongly (r = 0.83, P < .0001) in stable glycemia and moderately at all rates of change (r = 0.69, P < .0001). Interstitial glucose concentration underestimated BG in euglycemia, but the BG-IG difference was progressively smaller as BG decreased (12.9 ± 12.2, 8.8 ± 11.2, -3.2 ± 7.4, and -7.8 ± 5.2 mg/dL in the ranges of 80-120 [n = 64], 60-79 [n = 29], 50-59 [n = 71], and 29-49 mg/dL [n = 53], respectively).

CONCLUSIONS

Although IG underestimates BG throughout most of the hypo-euglycemic range, IG generally overestimates BG in marked hypoglycemia (<60 mg/dL). It is therefore imperative to evaluate FSL2 results in this critical range with caution.

Analytical Performance of the Factory-Calibrated Flash Glucose Monitoring System FreeStyle Libre2TM in Healthy Women

Continuous glucose monitoring (CGM) is used clinically and for research purposes to capture glycaemic profiles. The accuracy of CGM among healthy populations has not been widely assessed. This study assessed agreement between glucose concentrations obtained from venous plasma and from CGM (FreeStyle Libre2TM, Abbott Diabetes Care, Witney, UK) in healthy women. Glucose concentrations were assessed after fasting and every 15 min after a standardized breakfast over a 4-h lab period. Accuracy of CGM was determined by Bland-Altman plot, 15/15% sensor agreement analysis, Clarke error grid analysis (EGA) and mean absolute relative difference (MARD). In all, 429 valid CGM readings with paired venous plasma glucose (VPG) values were obtained from 29 healthy women. Mean CGM readings were 1.14 mmol/L (95% CI: 0.97 to 1.30 mmol/L, p < 0.001) higher than VPG concentrations. Ratio 95% limits of agreement were from 0.68 to 2.20, and a proportional bias (slope: 0.22) was reported. Additionally, 45% of the CGM readings were within ±0.83 mmol/L (±15 mg/dL) or ±15% of VPG, while 85.3% were within EGA Zones A + B (clinically acceptable). MARD was 27.5% (95% CI: 20.8, 34.2%), with higher MARD values in the hypoglycaemia range and when VPG concentrations were falling. The FreeStyle Libre2TM CGM system tends to overestimate glucose concentrations compared to venous plasma samples in healthy women, especially during hypoglycaemia and during glycaemic swings.

Use of Continuous Glucose Monitoring in Patients Following Bariatric Surgery: A Scoping Review

The objective of this scoping review was to summarize the emerging literature on the use of continuous glucose monitoring (CGM) in post-bariatric surgery patients, with a focus on its features (e.g., device, mode, and accuracy), as well as purposes and outcomes of utilization. Three databases (PubMed, EMBASE, and Web of Science) were searched to obtain relevant studies. Results suggested that most studies used CGM for 3-7 days under blinded mode. Accuracy data were available in only one study, which reported a mean absolute relative difference of 21.7% for Freestyle Libre. The primary applications of CGM were for elucidating glucose patterns and assessing glycemic treatment outcomes. No study has tested the effect of CGM as an intervention strategy to enhance glucose control.

Pediatric Type 1 Diabetes: Mechanisms and Impact of Technologies on Comorbidities and Life Expectancy

Type 1 diabetes (T1D) is one of the most common chronic diseases in childhood, with a progressively increasing incidence. T1D management requires lifelong insulin treatment and ongoing health care support. The main goal of treatment is to maintain blood glucose levels as close to the physiological range as possible, particularly to avoid blood glucose fluctuations, which have been linked to morbidity and mortality in patients with T1D. Indeed, the guidelines of the International Society for Pediatric and Adolescent Diabetes (ISPAD) recommend a glycated hemoglobin (HbA1c) level < 53 mmol/mol (<7.0%) for young people with T1D to avoid comorbidities. Moreover, diabetic disease strongly influences the quality of life of young patients who must undergo continuous monitoring of glycemic values and the administration of subcutaneous insulin. In recent decades, the development of automated insulin delivery (AID) systems improved the metabolic control and the quality of life of T1D patients. Continuous subcutaneous insulin infusion (CSII) combined with continuous glucose monitoring (CGM) devices connected to smartphones represent a good therapeutic option, especially in young children. In this literature review, we revised the mechanisms of the currently available technologies for T1D in pediatric age and explored their effect on short- and long-term diabetes-related comorbidities, quality of life, and life expectation.

Comment on Hochfellner et al. Accuracy Assessment of the GlucoMen® Day CGM System in Individuals with Type 1 Diabetes: A Pilot Study. Biosensors 2022, 12, 106

In their recent article entitled "Accuracy Assessment of the GlucoMen^® Day CGM System in Individuals with Type 1 Diabetes: A Pilot Study" [...].

Management of type 1 diabetes in pregnancy: update on lifestyle, pharmacological treatment, and novel technologies for achieving glycaemic targets

Glucose concentrations within target, appropriate gestational weight gain, adequate lifestyle, and, if necessary, antihypertensive treatment and low-dose aspirin reduces the risk of pre-eclampsia, preterm delivery, and other adverse pregnancy and neonatal outcomes in pregnancies complicated by type 1 diabetes. Despite the increasing use of diabetes technology (ie, continuous glucose monitoring and insulin pumps), the target of more than 70% time in range in pregnancy (TIRp 3·5-7·8 mmol/L) is often reached only in the final weeks of pregnancy, which is too late for beneficial effects on pregnancy outcomes. Hybrid closed-loop (HCL) insulin delivery systems are emerging as promising treatment options in pregnancy. In this Review, we discuss the latest evidence on pre-pregnancy care, management of diabetes-related complications, lifestyle recommendations, gestational weight gain, antihypertensive treatment, aspirin prophylaxis, and the use of novel technologies for achieving and maintaining glycaemic targets during pregnancy in women with type 1 diabetes. In addition, the importance of effective clinical and psychosocial support for pregnant women with type 1 diabetes is also highlighted. We also discuss the contemporary studies examining HCL systems in type 1 diabetes during pregnancies.

Expanding the Role of Continuous Glucose Monitoring in Modern Diabetes Care Beyond Type 1 Disease

Application of continuous glucose monitoring (CGM) has moved diabetes care from a reactive to a proactive process, in which a person with diabetes can prevent episodes of hypoglycemia or hyperglycemia, rather than taking action only once low and high glucose are detected. Consequently, CGM devices are now seen as the standard of care for people with type 1 diabetes mellitus (T1DM). Evidence now supports the use of CGM in people with type 2 diabetes mellitus (T2DM) on any treatment regimen, not just for those on insulin therapy. Expanding the application of CGM to include all people with T1DM or T2DM can support effective intensification of therapies to reduce glucose exposure and lower the risk of complications and hospital admissions, which are associated with high healthcare costs. All of this can be achieved while minimizing the risk of hypoglycemia and improving quality of life for people with diabetes. Wider application of CGM can also bring considerable benefits for women with diabetes during pregnancy and their children, as well as providing support for acute care of hospital inpatients who experience the adverse effects of hyperglycemia following admission and surgical procedures, as a consequence of treatment-related insulin resistance or reduced insulin secretion. By tailoring the application of CGM for daily or intermittent use, depending on the patient profile and their needs, one can ensure the cost-effectiveness of CGM in each setting. In this article we discuss the evidence-based benefits of expanding the use of CGM technology to include all people with diabetes, along with a diverse population of people with non-diabetic glycemic dysregulation.

Real-life 24-week changes in glycemic parameters among European users of flash glucose monitoring with type 1 and 2 diabetes and different levels of glycemic control

AIM

To evaluate real-life changes of glycemic parameters among flash glucose monitoring (FLASH) users who do not meet glycemic targets.

METHODS

De-identified data were obtained between 2014 and 2021 from patients using FLASH uninterrupted for a 24-week period. Glycemic parameters during first and last sensor use were examined in four identifiable groups: type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM) on basal-bolus insulin, T2DM on basal insulin, and T2DM without insulin treatment. Within each group, subgroup analyses were performed in persons with initial suboptimal glycemic regulation (time in range (TIR; 3.9-10 mmol/L) <70%, time above range (TAR; >10 mmol/L) >25%, or time below range (TBR; <3.9 mmol/L) >4%).

RESULTS

Data were obtained from 1,909 persons with T1DM and 1,813 persons with T2DM (1,499 basal-bolus insulin, 189 basal insulin, and 125 non-insulin users). In most of the performed analyses, both overall and in the various subgroups, significant improvements were observed in virtually all predefined primary (TIR) and secondary endpoints (eHbA1c, TAR, TBR and glucose variability).

CONCLUSIONS

24-weeks FLASH use in real life by persons with T1DM and T2DM with suboptimal glycemic regulation is associated with improvement of glycemic parameters, irrespective of pre-use regulation or treatment modality.

Low Initial Adherence with Flash Glucose Monitoring is Not a Predictor of Long-Term Glycemic Outcomes: Longitudinal Analysis of the Association Between Experience, Adherence, and Glucose Control for FreeStyle Libre Users

INTRODUCTION

Frequent scanning of FreeStyle Libre (FSL) flash glucose monitoring sensors is known to be important whilst wearing an active sensor, but adherence to sensor reapplication is also critical to effective glucose monitoring. We report novel measures of adherence for users of the FSL system and their association with improvements in metrics of glucose control.

METHODS

Anonymous data were extracted for 1600 FSL users in the Czech Republic with ≥ 36 completed sensors from October 22, 2018 to December 31, 2021. "Experience" was defined by the number of sensors used (1-36 sensors). "Adherence" was defined by time between the end of one sensor and the start of the next (gap time). User adherence was analyzed for four experience levels after initiating FLASH; Start (sensors 1-3); Early (sensors 4-6); Middle (sensors 19-21); End (sensors 34-36). Users were split into two adherence levels based on mean gap time during Start period, "low" (> 24 h, n = 723) and "high" (≤ 8 h, n = 877).

RESULTS

Low-adherence users reduced their sensor gap times significantly: 38.5% applied a new sensor within 24 h during sensors 4-6, rising to 65.0% by sensors 34-36 (p < 0.001). Improved adherence was associated with increased %TIR (time in range; mean + 2.4%; p < 0.001), reduced %TAR (time above range; mean - 3.1%; p < 0.001), and reduced glucose coefficient of variation (CV; mean - 1.7%; p < 0.001).

CONCLUSIONS

With experience, FSL users became more adherent in sensor reapplication, with associated increases in %TIR, and reductions in %TAR and glucose variability.

Noninvasive Continuous Glucose Monitoring With a Novel Wearable Dial Resonating Sensor: A Clinical Proof-of-Concept Study

BACKGROUND

A noninvasive, wearable continuous glucose monitor would be a major advancement in diabetes therapy. This trial investigated a novel noninvasive glucose monitor which analyzes spectral variations in radio frequency/microwave signals reflected from the wrist.

METHODS

A single-arm, open-label, experimental study compared glucose values from a prototype investigational device with laboratory glucose measurements from venous blood samples (Super GL Glucose Analyzer, Dr. Müller Gerätebau GmbH) at varying levels of glycemia. The study included 29 male participants with type 1 diabetes (age range = 19-56 years). The study comprised three stages with the following aims: (1) demonstrate initial proof-of-principle, (2) test an improved device design, and (3) test performance on two consecutive days without device recalibration. The co-primary endpoints in all trial stages were median and mean absolute relative difference (ARD) calculated across all data points.

RESULTS

In stage 1, the median and mean ARDs were 30% and 46%, respectively. Stage 2 produced marked performance improvements with a median and mean ARD of 22% and 28%, respectively. Stage 3 showed that, without recalibration, the device performed as well as the initial prototype (stage 1) with a median and mean ARD of 35% and 44%, respectively.

CONCLUSION

This proof-of-concept study shows that a novel noninvasive continuous glucose monitor was capable of detecting glucose levels. Furthermore, the ARD results are comparable to first models of commercially available minimally invasive products without the need to insert a needle. The prototype has been further developed and is being tested in subsequent studies.

TRIAL REGISTRATION NUMBER

NCT05023798.

Accuracy of the Third Generation of a 14-Day Continuous Glucose Monitoring System

INTRODUCTION

We have evaluated the performance of the FreeStyle Libre® 3 continuous glucose monitoring system (FSL3) compared to (1) the venous plasma reference for participants aged ≥ 6 years and (2) the fingerstick capillary blood glucose (BG) reference for pediatric participants aged 4 and 5 years. The analytical performance of the third-generation factory-calibrated FSL3 CGM system was compared to the plasma venous blood glucose reference using the YSI 2300 STAT PLUS Glucose and Lactate Analyzer (the YSI reference) and the self-monitoring blood glucose (SMBG) reference for participants aged ≥ 6 years and participants aged 4 and 5 years, respectively.

METHODS

A total of 108 participants aged ≥ 4 years with type 1 or type 2 diabetes from four sites in the USA were enrolled in the study. The data of 100 participants were ultimately evaluated. Adult participants (aged ≥ 18 years) participated in three in-clinic sessions, and pediatric participants (aged 4-17 years) participated in up to two in-clinic sessions, all stratified to provide data for days 1, 2, 3, 7, 8, 9, 12, 13 or 14 of sensor wear. Performance evaluation included accuracy measures, such as proportion of CGM values that fell within ± 20% or ± 20 mg/dL (1.1 mmol/L) of the reference glucose values, and difference measures, such as the mean absolute relative difference (MARD) between the CGM and reference values.

RESULTS

Data from the 100 study participants were analyzed. The overall MARD was 7.8%, and 93.4% of the CGM values were within ± 20% or ± 20 mg/dL of the YSI reference for participants aged ≥ 6 years, with 6845 CGM-YSI matched pairs. The performance was stable over the 14-day wear period. For participants aged 4-5 years, MARD was 10.0%, and 88.9% of the CGM values were within 20%/20 mg/dL compared to a SMBG reference. No serious adverse events were reported.

CONCLUSIONS

The FSL3 CGM system demonstrated accurate performance across the dynamic glycemic range during the 14-day sensor wear period.

CGM accuracy: Contrasting CE marking with the governmental controls of the USA (FDA) and Australia (TGA): A narrative review

The National Institute for Clinical Excellence updated guidance for continuous glucose monitoring (CGM) in 2022, recommending that CGM be available to all people living with type 1 diabetes. Manufacturers can trade in the UK with Conformité Européenne (CE) marking without an initial national assessment. The regulatory process for CGM CE marking, in contrast to the Food and Drug Administration (FDA) and Australian Therapeutic Goods Administration (TGA) process, is described. Manufacturers operating in the UK provided clinical accuracy studies submitted for CE marking. Critical appraisal of the studies shows several CGM devices have CE marking for wide-ranging indications beyond available data, unlike FDA and TGA approval. The FDA and TGA use tighter controls, requiring comprehensive product-specific clinical data evaluation. In 2018, the FDA published the integrated CGM (iCGM) criteria permitting interoperability. Applying the iCGM criteria to clinical data provided by manufacturers trading in the UK identified several study protocols that minimized glucose variability, thereby improving CGM accuracy on all metrics. These results do not translate into real-life performance. Furthermore, for many CGM devices available in the UK, accuracy reported in the hypoglycaemic range is below iCGM standards, or measurement is absent. We offer a framework to evaluate CGM accuracy studies critically. The review concludes that FDA- and TGA-approved indications match the available clinical data, whereas CE marking indications can have discrepancies. The UK can bolster regulation with UK Conformity Assessed marking from January 2025. However, balanced regulation is needed to ensure innovation and timely technological access are not hindered.

Constrained IoT-Based Machine Learning for Accurate Glycemia Forecasting in Type 1 Diabetes Patients

Individuals with diabetes mellitus type 1 (DM1) tend to check their blood sugar levels multiple times daily and utilize this information to predict their future glycemic levels. Based on these predictions, patients decide on the best approach to regulate their glucose levels with considerations such as insulin dosage and other related factors. Nevertheless, modern developments in Internet of Things (IoT) technology and innovative biomedical sensors have enabled the constant gathering of glucose level data using continuous glucose monitoring (CGM) in addition to other biomedical signals. With the use of machine learning (ML) algorithms, glycemic level patterns can be modeled, enabling accurate forecasting of this variable. Constrained devices have limited computational power, making it challenging to run complex machine learning algorithms directly on these devices. However, by leveraging edge computing, using lightweight machine learning algorithms, and performing preprocessing and feature extraction, it is possible to run machine learning algorithms on constrained devices despite these limitations. In this paper we test the burdens of some constrained IoT devices, probing that it is feasible to locally predict glycemia using a smartphone, up to 45 min in advance and with acceptable accuracy using random forest.

Emerging Diabetes Technologies: Continuous Glucose Monitors/Artificial Pancreases

Over the past decade there have been many advances in diabetes technologies, such as continuous glucose monitors (CGM s), insulin-delivery devices, and hybrid closed loop systems . Now most CGMs (Medtronic-Guardian, Dexcom-G6, and Abbott-Libre-2) have MARD values of < 10%, in contrast to two decades ago when the MARD used to be > 20%. In addition, the majority of the new CGMs do not require calibrations, and the latest CGMs last for 10-14 days. An implantable 6-months CGM by Eversense-3 is now approved in the USA and Europe. Recently, the FDA approved Libre 3 which provides real-time glucose values every minute. Even though it is approved as an iCGM it is not interoperable with automatic-insulin-delivery (AID) systems. The newer CGMs that are likely to be launched in the next few months in the USA include the 10-11 days Dexcom G7 (60% smaller than the existing G6), and the 7-days Medtronic Guardian 4. Most of the newer CGM have several features like automatic initialization, easy insertion, predictive alarms, and alerts. It has also been noticed that an arm insertion site might have better accuracy than abdomen or other sites, like the buttock for kids. Lag time between YSI and different sensors have been reported differently, sometimes it is down to 2-3 min; however, in many instances, it is still 15-20 min, especially when the rate of change of glucose is > 2 mg/min. We believe that in the next decade there will be a significant increase in the number of people who use CGM for their day-to-day diabetes care.

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

BACKGROUND

FIND, the global alliance for diagnostics, identified the nonmarket-approved continuous glucose monitoring (CGM) system, FiberSense system (FBS), as a potential device for use in low- and middle-income countries. Together with two market-approved, factory-calibrated CGM systems, namely, the FreeStyle Libre 2 (FL2) and the GlucoRx AiDEX (ADX), the FBS was subjected to a clinical performance evaluation.

METHODS

Thirty adult participants with type 1 diabetes were enrolled. The study was mainly conducted at home, with three in-clinic sessions conducted over the study period of 28 days. Comparator measurements were collected from capillary samples, using a high-quality blood glucose monitoring system.

RESULTS

Data from 31, 70, and 78 sensors of FBS, FL2, and ADX, respectively, were included in the performance analysis. The mean absolute relative differences between CGM and comparator data for FBS, FL2, and ADX were 14.7%, 9.2%, and 21.9%, and relative biases were -2.1%, -2.5%, and -18.5%, respectively. Analysis of individual sensor accuracy revealed low, moderate, and high sensor-to-sensor variability for FBS, FL2, and ADX, respectively. Sensor survival probabilities until the end of sensor life were 47.2% for FBS (28 days), 71.3% for FL2 (14 days), and 48.4% for ADX (14 days).

CONCLUSIONS

The results of FBS were encouraging enough to conduct further performance and usability evaluations in a low- and middle-income country. The results of FL2 mainly agreed with existing studies, whereas ADX showed substantial deviations from previously reported results.

Advances in Continuous Glucose Monitoring and Integrated Devices for Management of Diabetes with Insulin-Based Therapy: Improvement in Glycemic Control

Continuous glucose monitoring (CGM) technology has evolved over the past decade with the integration of various devices including insulin pumps, connected insulin pens (CIPs), automated insulin delivery (AID) systems, and virtual platforms. CGM has shown consistent benefits in glycemic outcomes in type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) treated with insulin. Moreover, the combined effect of CGM and education have been shown to improve glycemic outcomes more than CGM alone. Now a CIP is the expected future technology that does not need to be worn all day like insulin pumps and helps to calculate insulin doses with a built-in bolus calculator. Although only a few clinical trials have assessed the effectiveness of CIPs, they consistently show benefits in glycemic outcomes by reducing missed doses of insulin and improving problematic adherence. AID systems and virtual platforms made it possible to achieve target glycosylated hemoglobin in diabetes while minimizing hypoglycemia, which has always been challenging in T1DM. Now fully automatic AID systems and tools for diabetes decisions based on artificial intelligence are in development. These advances in technology could reduce the burden associated with insulin treatment for diabetes.

Should continuous glucose monitoring be used to manage neonates at risk of hypoglycaemia?

The National Institute for Clinical Excellence (NICE) now recommends that continuous glucose monitoring (CGM) be offered to adults and children with diabetes who are at risk from hypoglycaemia. Hypoglycaemia is common in the neonatal period, and is a preventable cause of poor neurodevelopmental outcome, but is CGM helpful in the management of neonates at risk of hypoglycaemia? Neonatal studies have shown that CGM can detect clinically silent hypoglycaemia, which has been associated with reduced executive and visual function in early childhood. Intervention trials have further shown CGM can support the targeting of glucose levels in high-risk extremely preterm neonates. In spite of significant advances in technology, including smaller sensors, better accuracy and factory calibration, further progress and adoption into clinical practice has been limited as current devices are not designed nor have regulatory approval for the specific needs of the newborn. The use of CGM has the potential to support clinical management, and prevention of hypoglycaemia but must be set within its current limitations. The data CGM provides however also provides an important opportunity to improve our understanding of potential risks of hypoglycaemia and the impact of clinical interventions to prevent it.

Continuous glucose monitoring and metrics for clinical trials: an international consensus statement

Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA1c as the measure of average blood glucose levels for the 3 months preceding the HbA1c test date. The use of this measure highlights the long-established correlation between HbA1c and relative risk of diabetes complications; the change in the measure, before and after the therapeutic intervention, is used by regulators for the approval of medications for diabetes. However, with the increasing use of continuous glucose monitoring (CGM) in clinical practice, prospective clinical studies are also increasingly using CGM devices to collect data and evaluate glucose profiles among study participants, complementing HbA1c findings, and further assess the effects of therapeutic interventions on HbA1c. Data is collected by CGM devices at 1-5 min intervals, which obtains data on glycaemic excursions and periods of asymptomatic hypoglycaemia or hyperglycaemia (ie, details of glycaemic control that are not provided by HbA1c concentrations alone that are measured continuously and can be analysed in daily, weekly, or monthly timeframes). These CGM-derived metrics are the subject of standardised, internationally agreed reporting formats and should, therefore, be considered for use in all clinical studies in diabetes. The purpose of this consensus statement is to recommend the ways CGM data might be used in prospective clinical studies, either as a specified study endpoint or as supportive complementary glucose metrics, to provide clinical information that can be considered by investigators, regulators, companies, clinicians, and individuals with diabetes who are stakeholders in trial outcomes. In this consensus statement, we provide recommendations on how to optimise CGM-derived glucose data collection in clinical studies, including the specific glucose metrics and specific glucose metrics that should be evaluated. These recommendations have been endorsed by the American Association of Clinical Endocrinologists, the American Diabetes Association, the Association of Diabetes Care and Education Specialists, DiabetesIndia, the European Association for the Study of Diabetes, the International Society for Pediatric and Adolescent Diabetes, the Japanese Diabetes Society, and the Juvenile Diabetes Research Foundation. A standardised approach to CGM data collection and reporting in clinical trials will encourage the use of these metrics and enhance the interpretability of CGM data, which could provide useful information other than HbA1c for informing therapeutic and treatment decisions, particularly related to hypoglycaemia, postprandial hyperglycaemia, and glucose variability.

Metabolic control and satisfaction in a diabetes education programme in flash glucose monitoring through telemedicine in type 1 diabetes

OBJECTIVE

To evaluate metabolic control and satisfaction with a telemedicine diabetes education programme for the initiation of flash glucose monitoring (FGM) in type 1 diabetes.

MATERIAL AND METHODS

Prospective study in 48 patients (52.1% women, 22.9% on insulin pump) who started FGM. They were analysed at baseline and 3 months after the beginning of the FGM. The results were compared with an on-site learning cohort matched by age, sex and HbA1c.

RESULTS

At the beginning and 3 months after the MFG, HbA1c improvement was observed (7.9±1.4 vs 7.3±1.1%), p<0.01; with a decrease in time below range - TBR - (4.7±4.9 vs 3.5±3.5%), p<0.05 and number of hypoglycaemic events (9.4±8.7 vs 6.9±5.7/15 days), p<0.05, associated with a worsening in time above range - TAR - (33.5±19.9 vs 37.0±20.9%), p<0.05. No significant differences were observed in the TIR 70-180mg/dl (61.7±18.6 vs 59.4±20.0%), glycemic variability or the use of FGM. Patient satisfaction with telemedicine training was 4.8±0.3 out of 5. No significant differences were observed in the follow-up, either in HbA1c or other glucometer parameters between on-site and online training. In a multivariate analysis adopting the HbA1c at follow-up as the dependent variable, only the TIR (β=-0.034; p<0.001) and the initial HbA1c (β=0.303; p<0.001) maintained statistical significance, unrelated to the on-site or online training (β=0.136; p=ns).

CONCLUSIONS

A telemedicine programme is an adequate tool for training in FGM, with results similar to on-site training, and it was associated with a high degree of satisfaction.

Moving with technological advancements: blood glucose monitoring from a district nurse's perspective

Capillary blood glucose monitoring is a standard safety protocol before administering insulin. Over the past 12 months, there has been a notable increase in patients under the district nursing service using a flash glucose sensor (FGS), which is a portable technological device inserted into the skin via a stamp-like mechanism. The device sits in the interstitial fluid under the skin; the device can be scanned using a sensor to obtain glucose readings, which can eliminate the need for capillary finger pricking. From experience, some people opt for this device, considering the pain and inconvenience associated with capillary finger pricking. Despite some patients already utilising FGS, some community teams may still have to take a capillary finger prick before insulin administration, depending on local trust policy. Interestingly, while looking into the reasons for this, one discovered some contradictory concerns over the safety of FGS due to a difference in time lag, where interstitial fluid readings differ from blood glucose readings. However, new national guidelines reflect the push towards this technological innovation that could revolutionise patient care in glucose monitoring and diabetes management.

Reduced Rate of Acute Diabetes Events with Flash Glucose Monitoring Is Sustained for 2 Years After Initiation: Extended Outcomes from the RELIEF Study

Background: The RELIEF study has previously shown a fall in the rate of acute diabetes events (ADEs) in people living with type 1 diabetes (PwDT1) or people living with type 2 diabetes (PwDT2) in the 12 months after initiation of flash glucose monitoring (FLASH) in France. The 2-year follow-up has provided new insights on the frequency of ADEs, including severe hypoglycemia and diabetic ketoacidosis (DKA), during use of FLASH. Methods: The RELIEF study included 31,446 PwDT1 and 41,027 PwDT2 with a first delivery of FreeStyle Libre (FSL) between August 1 and December 31, 2017. Hospitalizations for DKA, severe hypoglycemia, diabetes-related coma, and hyperglycemia were recorded for the 12 months before and 24 months after FSL initiation. Persistence of the FSL system use was estimated through a Kaplan-Meier survival curve. Change in usual blood glucose monitoring was estimated through acquisition of blood glucose test strips. Results: In the 2 years after FSL initiation, hospitalizations for ADEs were reduced by 49% and by 48% in PwDT1 or PwDT2, respectively, driven by reductions in DKA. After 2 years, 88% of patients persisted with the system and estimated mean consumption of blood glucose test strips had fallen after 2 years by -82% and by -84% in type 1 diabetes mellitus and type 2 diabetes mellitus, respectively. Conclusion: Use of FSL consistently reduces the rates of hospitalization for ADEs, mainly DKA, 2 years after initiation, confirming this is not a transitory effect. Use of FSL also results in a clear and progressive drop in use of blood glucose test strips over the 2-year period.

Intralymphatic GAD-Alum (Diamyd®) Improves Glycemic Control in Type 1 Diabetes With HLA DR3-DQ2

AIMS

Residual beta cell function in type 1 diabetes (T1D) is associated with lower risk of complications. Autoantigen therapy with GAD-alum (Diamyd) given in 3 intralymphatic injections with oral vitamin D has shown promising results in persons with T1D carrying the human leukocyte antigen (HLA) DR3-DQ2 haplotype in the phase 2b trial DIAGNODE-2. We aimed to explore the efficacy of intralymphatic GAD-alum on blood glucose recorded by continuous glucose monitoring (CGM).

METHODS

DIAGNODE-2 (NCT03345004) was a multicenter, randomized, placebo-controlled, double-blind trial of 109 recent-onset T1D patients aged 12 to 24 years with GAD65 antibodies and fasting C-peptide > 0.12 nmol/L, which randomized patients to 3 intralymphatic injections of 4 μg GAD-alum and oral vitamin D, or placebo. We report results for exploratory endpoints assessed by 14-day CGM at months 0, 6, and 15. Treatment arms were compared by mixed-effects models for repeated measures adjusting for baseline values.

RESULTS

We included 98 patients with CGM recordings of sufficient quality (DR3-DQ2-positive patients: 27 GAD-alum-treated and 15 placebo-treated). In DR3-DQ2-positive patients, percent of time in range (TIR, 3.9-10 mmol/L) declined less between baseline and month 15 in GAD-alum-treated compared with placebo-treated patients (-5.1% and -16.7%, respectively; P = 0.0075), with reduced time > 13.9 mmol/L (P = 0.0036), and significant benefits on the glucose management indicator (P = 0.0025). No differences were detected for hypoglycemia. GAD-alum compared to placebo lowered the increase in glycemic variability (standard deviation) observed in both groups (P = 0.0219). Change in C-peptide was correlated with the change in TIR.

CONCLUSIONS

Intralymphatic GAD-alum improves glycemic control in recently diagnosed T1D patients carrying HLA DR3-DQ2.

Clinical feasibility of remote intermittently scanned continuous glucose monitoring in coronavirus disease 2019 patients with and without diabetes during dexamethasone therapy

The clinical utility of intermittently scanned continuous glucose monitoring (isCGM) in patients with coronavirus disease 2019 (COVID-19) is unclear. Hence, we investigated the accuracy of isCGM in COVID-19 patients during dexamethasone therapy. We evaluated the accuracy of the FreeStyle Libre via smartphone isCGM device compared to point-of-care (POC) fingerstick glucose level monitoring in 16 patients with COVID-19 (10 with and 6 without diabetes, 13 men; HbA1c 6.9 ± 1.0%). Overall, isCGM correlated well with POC measurements (46.2% and 53.8% within areas A and B of the Parkes error grid, respectively). The overall mean absolute relative difference (MARD) for isCGM compared to POC measurements was 19.4%. The MARDs were 19.8% and 19.7% for POC blood glucose measurements ranging from 70 to 180 mg/dL and >180 mg/dL, respectively. When divided according to the presence and absence of diabetes, both groups of paired glucose measurements showed a good correlation (56.3% and 43.7%, and 27.1% and 72.9% within the A and B areas in patients with and without diabetes, respectively), but the MARD was not significant but higher in patients without diabetes (16.5% and 24.2% in patients with and without diabetes). In conclusion, although isCGM may not be as accurate as traditional blood glucose monitoring, it has good reliability in COVID-19 patients with and without diabetes during dexamethasone therapy.

A guide for the use of LibreView digital diabetes platform in clinical practice: Expert paper of the Italian Working Group on Diabetes and Technology

Wider access to continuous glucose monitoring systems, including flash glucose monitoring, has enabled people with diabetes to achieve lower HbA1c levels and reduce the amount of time they spend in hypoglycaemia or hyperglycaemia, and has improved their quality of life. An International Consensus Panel proposed different target glucose ranges and recommendations according to different ages and situations (adults, young people and children with type 1 or type 2 diabetes, as well as elderly people who are at higher risk of hypoglycaemia, and women with diabetes during pregnancy). In this expert opinion, we interpret the international recommendations in the context of established clinical practice for diabetes care, and propose three different step-by-step algorithms to help the healthcare professionals use the most innovative glucose metrics, including time in glucose ranges, glucose management indicator, coefficient of variation, and ambulatory glucose profile. In detail, we focus on glucose metrics as measured by the FreeStyle Libre system and as visualized on the LibreView digital diabetes platform to support appropriate interpretation of flash glucose monitoring data. This is specifically structured for healthcare professionals and general practitioners who may have a low level of confidence with diabetes technology, with the aim of optimizing diabetes management, ensuring effective use of healthcare resources and to maximise outcomes for people with diabetes.