Benefits and Limitations of MARD as a Performance Parameter for Continuous Glucose Monitoring in the Interstitial Space

Continuous Glucose Monitoring and Recreational Scuba Diving in Type 1 Diabetes: Head-to-Head Comparison Between Free Style Libre 3 and Dexcom G7 Performance

Background: Scuba diving was previously excluded because of hypoglycemic risks for patients with type 1 diabetes mellitus(T1DM). Specific eligibility criteria and a safety protocol have been defined, whereas continuous glucose monitoring (CGM) systems have enhanced diabetes management. This study aims to assess the feasibility and accuracy of CGM Dexcom G7 and Free Style Libre 3 in a setting of repetitive scuba diving in T1DM, exploring the possibility of nonadjunctive use. Material and Methods: The study was conducted during an event of Diabete Sommerso® association in 2023. Participants followed a safety protocol, with capillary glucose as reference standard (Beurer GL50Evo). Sensors' accuracy was evaluated through median and mean absolute relative difference (MeARD, MARD) and surveillance error grid (SEG). Data distribution and correlation were estimated by Spearman test and Bland-Altman plots. The ability of sensors to identify hypoglycemia was assessed by contingency tables. Results: Data from 202 dives of 13 patients were collected. The overall MARD was 31% (Dexcom G7) and 14.2% (Free Style Libre 3) and MeARD was 19.7% and 11.6%, respectively. Free Style Libre 3 exhibited better accuracy in normoglycemic and hyperglycemic ranges. SEG analysis showed 82.1% (Dexcom G7) and 97.4% (Free Style Libre 3) data on no-risk zone. Free Style Libre 3 better performed on hypoglycemia identification (diagnostic odds ratio of 254.10 vs. 58.95). Neither of the sensors reached the MARD for nonadjunctive use. Conclusions: The study reveals Free Style Libre 3 superior accuracy compared with Dexcom G7 in a setting of repetitive scuba diving in T1DM, except for hypoglycemic range. Both sensors fail to achieve accuracy for nonadjunctive use. Capillary tests remain crucial for safe dive planning, and sensor data should be interpreted cautiously. We suggest exploring additional factors potentially influencing sensor performance.

Using Artificial Intelligence to Improve the Accuracy of a Wrist-Worn, Noninvasive Glucose Monitor: A Pilot Study

BACKGROUND

Self-monitoring of glucose is important to the successful management of diabetes; however, existing monitoring methods require a degree of invasive measurement which can be unpleasant for users. This study investigates the accuracy of a noninvasive glucose monitoring system that analyses spectral variations in microwave signals.

METHODS

An open-label, pilot design study was conducted with four cohorts (N = 5/cohort). In each session, a dial-resonating sensor (DRS) attached to the wrist automatically collected data every 60 seconds, with a novel artificial intelligence (AI) model converting signal resonance output to a glucose prediction. Plasma glucose was measured in venous blood samples every 5 minutes for Cohorts 1 to 3 and every 10 minutes for Cohort 4. Accuracy was evaluated by calculating the mean absolute relative difference (MARD) between the DRS and plasma glucose values.

RESULTS

Accurate plasma glucose predictions were obtained across all four cohorts using a random sampling procedure applied to the full four-cohort data set, with an average MARD of 10.3%. A statistical analysis demonstrates the quality of these predictions, with a surveillance error grid (SEG) plot indicating no data pairs falling into the high-risk zones.

CONCLUSIONS

These findings show that MARD values approaching accuracies comparable to current commercial alternatives can be obtained from a multiparticipant pilot study with the application of AI. Microwave biosensors and AI models show promise for improving the accuracy and convenience of glucose monitoring systems for people with diabetes.

AI-Driven Spectral Decomposition: Predicting the Most Probable Protein Compositions from Surface Enhanced Raman Spectroscopy Spectra of Amino Acids

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for elucidating the molecular makeup of materials. It possesses the unique characteristics of single-molecule sensitivity and extremely high specificity. However, the true potential of SERS, particularly in capturing the biochemical content of particles, remains underexplored. In this study, we harnessed transformer neural networks to interpret SERS spectra, aiming to discern the amino acid profiles within proteins. By training the network on the SERS profiles of 20 amino acids of human proteins, we explore the feasibility of predicting the predominant proteins within the µL-scale detection volume of SERS. Our results highlight a consistent alignment between the model's predictions and the protein's known amino acid compositions, deepening our understanding of the inherent information contained within SERS spectra. For instance, the model achieved low root mean square error (RMSE) scores and minimal deviation in the prediction of amino acid compositions for proteins such as Bovine Serum Albumin (BSA), ACE2 protein, and CD63 antigen. This novel methodology offers a robust avenue not only for protein analytics but also sets a precedent for the broader realm of spectral analyses across diverse material categories. It represents a solid step forward to establishing SERS-based proteomics.

Diabetes Technology in People with Type 2 Diabetes: Novel Indications

PURPOSE OF REVIEW

Diabetes technology has been continuously evolving. Current versions of continuous glucose monitors (CGM) use minimally invasive designs, monitor glucose values with high accuracy, and can be used to guide insulin dosing. Extensive evidence supports the use of diabetes technology for monitoring and insulin administration in people with type 1 diabetes. However, there is emerging evidence for people with type 2 diabetes. In this review, we present the different technological devices used to monitor glucose and deliver insulin and the evidence supporting their use in people with type 2 diabetes.

RECENT FINDINGS

The use of CGMs in people with type 2 diabetes treated with insulin or non-insulin therapies has been associated with improvements in glycemic control and time spent in hypoglycemia. Smart insulin pens and smart connected devices are options to track compliance and guide insulin delivery in people who do not require insulin pump therapy. Mechanical patch pumps can be used to reduce the burden of multiple daily insulin injections. Automated insulin delivery algorithms improve glycemic control without an increase in hypoglycemia. The use of technology in the management of type 2 diabetes generates glycemic data previously inaccessible, reduces barriers for insulin initiation, improves glycemic control, tracks adherence to therapy, and improves user satisfaction.

Accuracy of continuous glucose monitoring during exercise-related hypoglycemia in individuals with type 1 diabetes

Background

Hypoglycemia is common in individuals with type 1 diabetes, especially during exercise. We investigated the accuracy of two different continuous glucose monitoring systems during exercise-related hypoglycemia in an experimental setting.

Materials and methods

Fifteen individuals with type 1 diabetes participated in two separate euglycemic-hypoglycemic clamp days (Clamp-exercise and Clamp-rest) including five phases: 1) baseline euglycemia, 2) plasma glucose (PG) decline ± exercise, 3) 15-minute hypoglycemia ± exercise, 4) 45-minute hypoglycemia, and 5) recovery euglycemia. Interstitial PG levels were measured every five minutes, using Dexcom G6 (DG6) and FreeStyle Libre 1 (FSL1). Yellow Springs Instruments 2900 was used as PG reference method, enabling mean absolute relative difference (MARD) assessment for each phase and Clarke error grid analysis for each day.

Results

Exercise had a negative effect on FSL1 accuracy in phase 2 and 3 compared to rest (ΔMARD = +5.3 percentage points [(95% CI): 1.6, 9.1] and +13.5 percentage points [6.4, 20.5], respectively). In contrast, exercise had a positive effect on DG6 accuracy during phase 2 and 4 compared to rest (ΔMARD = -6.2 percentage points [-11.2, -1.2] and -8.4 percentage points [-12.4, -4.3], respectively). Clarke error grid analysis showed a decrease in clinically acceptable treatment decisions during Clamp-exercise for FSL1 while a contrary increase was observed for DG6.

Conclusion

Physical exercise had clinically relevant impact on the accuracy of the investigated continuous glucose monitoring systems and their ability to accurately detect hypoglycemia.

Application and management of continuous glucose monitoring in diabetic kidney disease

Diabetic kidney disease (DKD) is a common complication of diabetes mellitus that contributes to the risk of end-stage kidney disease (ESKD). Wide glycemic var-iations, such as hypoglycemia and hyperglycemia, are broadly found in diabetic patients with DKD and especially ESKD, as a result of impaired renal metabolism. It is essential to monitor glycemia for effective management of DKD. Hemoglobin A1c (HbA1c) has long been considered as the gold standard for monitoring glycemia for > 3 months. However, assessment of HbA1c has some bias as it is susceptible to factors such as anemia and liver or kidney dysfunction. Continuous glucose monitoring (CGM) has provided new insights on glycemic assessment and management. CGM directly measures glucose level in interstitial fluid, reports real-time or retrospective glucose concentration, and provides multiple glycemic metrics. It avoids the pitfalls of HbA1c in some contexts, and may serve as a precise alternative to estimation of mean glucose and glycemic variability. Emerging studies have demonstrated the merits of CGM for precise monitoring, which allows fine-tuning of glycemic management in diabetic patients. Therefore, CGM technology has the potential for better glycemic monitoring in DKD patients. More research is needed to explore its application and management in different stages of DKD, including hemodialysis, peritoneal dialysis and kidney transplantation.

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.

Clinical application of real-time continuous glucose monitoring system during postoperative enteral nutrition therapy in esophageal cancer patients

BACKGROUND

Enteral nutrition (EN) support therapy increases the risk of abnormal blood glucose (BG). The aim of this study is to evaluate the clinical value of a real-time continuous glucose monitoring (rt-CGM) system in BG monitoring during postoperative EN support therapy in patients with esophageal cancer.

METHODS

Patients without diabetes mellitus (DM) with esophageal cancer who planned to receive postoperative EN were enrolled. With the self-monitoring of BG value as the reference BG, the accuracy of rt-CGM was evaluated by the mean absolute relative difference (MARD) value, correlation efficient, agreement analysis, and Parkes and Clarke error grid plot. Finally, paired t tests were used to compare the differences in glucose fluctuations between EN and non-EN days and slow and fast days.

RESULTS

The total MARD value of the rt-CGM system was 13.53%. There was a high correlation between interstitial glucose and fingertip capillary BG (consistency correlation efficient = 0.884 [95% confidence interval, 0.874-0.894]). Results of 15/15%, 20/20%, 30/30% agreement analysis were 58.51%, 84.71%, and 99.65%, respectively. The Parkes and Clarke error grid showed that the proportion of the A and B regions were 100% and 99.94%, respectively. The glucose fluctuations on EN days vs non-EN days and on fast days vs slow days were large, and the difference was statistically significant (P < 0.001).

CONCLUSION

The rt-CGM system achieved clinical accuracy and can be used as a new option for glucose monitoring during postoperative EN therapy. The magnitude of glucose fluctuation during EN therapy remains large, even in the postoperative population without DM.

The Myth of MARD (Mean Absolute Relative Difference): Limitations of MARD in the Clinical Assessment of Continuous Glucose Monitoring Data

The mean absolute relative difference (MARD) is a numerical metric that has been adopted by the diabetes technology community as the main indicator that describes the accuracy of a glucose sensor at a single point in time. The appropriateness of this adoption is questionable because there is limited evidence that MARD has meaningful clinical relevance in the current era of sensor technology. The calculation may be simple, but evaluation of MARD can be very complex because it is substantially impacted by the design of the data collection in an accuracy study. Factors that can influence the overall MARD include participant demographics such as type of diabetes and age, site of sensor wear, and the percentage of collected values in each glycemic range during the study that is, in turn, a function of the study design. MARD is only one of several important statistical metrics such as bias and precision that are relevant to assessing accuracy of a sensor. Furthermore, these analytic metrics convey little information about the safety and effectiveness of sensor use with an automated insulin delivery system or a standalone device. There are no clinical studies in people with diabetes (PWD) proving that MARD can accurately differentiate between a safe and unsafe sensor or between a more and less clinically effective sensor. Moreover, there are alternatives to MARD that can do this in a clinically meaningful way, which include error grid analyses and clinical studies in PWD. This review attempts to demythologize the status of MARD for the diabetes community in an effort to shift the focus from MARD to using clinically relevant assessments.

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.

Continuous glucose monitoring has an increasing role in pre-symptomatic type 1 diabetes: advantages, limitations, and comparisons with laboratory-based testing

Type 1 diabetes (T1D) is well-recognised as a continuum heralded by the development of islet autoantibodies, progression to islet autoimmunity causing beta cell destruction, culminating in insulin deficiency and clinical disease. Abnormalities of glucose homeostasis are known to exist well before the onset of typical symptoms. Laboratory-based tests such as the oral glucose tolerance test (OGTT) and glycated haemoglobin (HbA1c) have been used to stage T1D and assess the risk of progression to clinical T1D. Continuous glucose monitoring (CGM) can detect early glycaemic abnormalities and can therefore be used to monitor for metabolic deterioration in pre-symptomatic, islet autoantibody positive, at-risk individuals. Early identification of these children can not only reduce the risk of presentation with diabetic ketoacidosis (DKA), but also determine eligibility for prevention trials, which aim to prevent or delay progression to clinical T1D. Here, we describe the current state with regard to the use of the OGTT, HbA1c, fructosamine and glycated albumin in pre-symptomatic T1D. Using illustrative cases, we present our clinical experience with the use of CGM, and advocate for an increased role of this diabetes technology, for monitoring metabolic deterioration and disease progression in children with pre-symptomatic T1D.

Comparisons of Fifth-, Sixth-, and Seventh-Generation Continuous Glucose Monitoring Systems

BACKGROUND

Between-system differences for continuous glucose monitoring (CGM) devices have important clinical consequences.

PURPOSE

Here we review attributes of Dexcom's fifth-, sixth-, and seventh-generation (G5, G6, and G7) CGM systems.

METHODS

Accuracy metrics were derived from preapproval trials of the three systems and compared after propensity score adjustments were used to balance baseline demographic characteristics. Metrics included mean absolute relative differences (MARD) between CGM and YSI values and the proportion of CGM values within 20% or 20 mg/dL of the YSI values ("%20/20"). Ease-of-use was evaluated by formal task analysis.

CONCLUSIONS

Adjusted MARD and %20/20 agreement rates were 9.0%/93.1% (abdomen-placed G5), 9.9%/92.3% (abdomen-placed G6), 9.1%/93.2% (abdomen-placed G7), and 8.2%/95.3% (arm-placed G7). Task analysis favored G7 over earlier systems. Favorable clinical outcomes such as hemoglobin A1c reduction and hypoglycemia avoidance seen with G5 and G6 are anticipated with G7 use.

The use of CGM to identify hypoglycemia and glycemic patterns in congenital hyperinsulinism

OBJECTIVES

Unrecognized hypoglycemia, especially in the neonatal population, is a significant cause of morbidity and poor neurologic outcomes. Children with congenital hyperinsulinism (HI) are at risk of hypoglycemia and point of care testing (POCT) is the standard of care. Studies have shown that continuous glucose monitoring (CGM) improves glycemic control and reduces the frequency of hypoglycemia among children with type 1 diabetes. There is limited experience with the use of CGM in children with HI. To assess the glycemic pattern of children with HI on stable therapy and evaluate the frequency of undetected hypoglycemia using Dexcom G6® CGM.

METHODS

A cross-sectional, observational pilot study was done in 10 children, ages 3 months to 17 years. Each child had a clinical or genetic diagnosis of HI on stable medical therapy. Participants were asked to continue their usual POCT blood glucose monitoring, as well as wear a blinded Dexcom G6® CGM during a 20-day study period with the potential of unblinding if there was severe hypoglycemia detected during the study trial.

RESULTS

During the study period, 26 hypoglycemic events were noted by CGM in 60 % of the participants with 45 % occurring between 0600 and 0800.

CONCLUSIONS

CGM can help detect hypoglycemia and blood glucose trends during a time when there is usually no POCT, which can guide medical management. 30 % of our population had a dose adjustment in their medications. This study was limited by population size.

A Nutritional Approach to Optimizing Pump Therapy in Type 1 Diabetes Mellitus

Achieving optimal glucose control in individuals with type 1 diabetes (T1DM) continues to pose a significant challenge. While continuous insulin infusion systems have shown promise as an alternative to conventional insulin therapy, there remains a crucial need for greater awareness regarding the necessary adaptations for various special circumstances. Nutritional choices play an essential role in the efficacy of diabetes management and overall health status for patients with T1DM. Factors such as effective carbohydrate counting, assessment of the macronutrient composition of meals, and comprehending the concept of the glycemic index of foods are paramount in making informed pre-meal adjustments when utilizing insulin pumps. Furthermore, the ability to handle such situations as physical exercise, illness, pregnancy, and lactation by making appropriate adjustments in nutrition and pump settings should be cultivated within the patient-practitioner relationship. This review aims to provide healthcare practitioners with practical guidance on optimizing care for individuals living with T1DM. It includes recommendations on carbohydrate counting, managing mixed meals and the glycemic index, addressing exercise-related challenges, coping with illness, and managing nutritional needs during pregnancy and lactation. Additionally, considerations relating to closed-loop systems with regard to nutrition are addressed. By implementing these strategies, healthcare providers can better equip themselves to support individuals with T1DM in achieving improved diabetes management and enhanced quality of life.

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.

High number of hypoglycaemic episodes identified by CGM among home-dwelling older people with diabetes: an observational study in Norway

BACKGROUND

A scoping review from 2021 identified a lack of studies on the incidence, prevention and management of hypoglycaemia in home-dwelling older people with diabetes. The aim of this study was to investigate the frequency and duration of hypoglycaemic episodes measured by continuous glucose monitoring (CGM) in older people with diabetes who received home care and who were treated with glucose-lowering medications, and to compare the frequency and duration of hypoglycaemic episodes between subgroups of the study population according to demographic and clinical variables.

METHODS

This was an observational study investigating the occurrence of hypoglycaemia in people with diabetes aged ≥ 65 years. Data were collected using blinded continuous glucose monitoring (CGM, iPro2) for 5 consecutive days. Frequency and duration of hypoglycaemic episodes were assessed using a sensor glucose cut-off value of 3.9 mmol/L. A blood sample for measurement of HbA1c and creatinine-based eGFR (CKD-EPI) was obtained during the monitoring period. Demographic and clinical data were collected from electronic patient records.

RESULTS

Fifty-six individuals were enrolled (median age 82 years and 52% were men). Of the 36 participants who were treated with insulin, 33% had at least one hypoglycaemic episode during the five-day period. Among 18 participants who neither used insulin nor sulfonylurea, but other glucose-lowering medications, 44% had at least one hypoglycaemicepisode. Of those with hypoglycaemic episodes, 86% lived alone. The median duration of the hypoglycaemia was 1 h and 25 min, ranging from 15 min to 8 h and 50 min.

CONCLUSION

This study identified an unacceptably high number of unknown hypoglycaemic episodes among older home-dwelling people with diabetes receiving home care, even among those not using insulin or sulfonylurea. The study provides essential knowledge that can serve as a foundation to improve the treatment and care for this vulnerable patient group. The routines for glucose monitoring and other prevention tasks need to be considered more comprehensively, also, among those treated with glucose-lowering medications other than insulin.

Blood glucose monitoring devices: current considerations

Measuring blood glucose concentrations via capillary (fingerprick) blood glucose monitoring or continuous (interstitial) glucose monitoring is an important aspect of management for many people with diabetes. Blood glucose monitoring informs patient self-management strategies, which can improve the patient's engagement in their own care and reduce barriers to achieving recommended blood glucose targets. Blood glucose monitoring also informs clinician-guided management plans. Compared to capillary blood glucose monitoring, continuous glucose monitoring in people using insulin significantly improves glycaemic metrics and is associated with improved patient-reported outcomes. Even with good glycaemic metrics, patients using continuous glucose monitoring should still have access to capillary blood glucose monitoring for correlation of hypoglycaemic readings when accuracy may be compromised or if there is a malfunction with the continuous blood glucose monitor.

The Effect of Insulin Degludec Versus Insulin Glargine U100 on Glucose Metrics Recorded During Continuous Glucose Monitoring in People With Type 1 Diabetes and Recurrent Nocturnal Severe Hypoglycemia

AIM

Comparing continuous glucose monitoring (CGM)-recorded metrics during treatment with insulin degludec (IDeg) versus insulin glargine U100 (IGlar-100) in people with type 1 diabetes (T1D) and recurrent nocturnal severe hypoglycemia.

MATERIALS AND METHODS

This is a multicenter, two-year, randomized, crossover trial, including 149 adults with T1D and minimum one episode of nocturnal severe hypoglycemia within the last two years. Participants were randomized 1:1 to treatment with IDeg or IGlar-100 and given the option of six days of blinded CGM twice during each treatment. CGM traces were reviewed for the percentage of time-within-target glucose range (TIR), time-below-range (TBR), time-above-range (TAR), and coefficient of variation (CV).

RESULTS

Seventy-four participants were included in the analysis. Differences between treatments were greatest during the night (23:00-06:59). Treatment with IGlar-100 resulted in 54.0% vs 49.0% with IDeg TIR (70-180 mg/dL) (estimated treatment difference [ETD]: -4.6%, 95% confidence interval [CI]: -9.1, -0.0, P = .049). TBR was lower with IDeg at level 1 (54-69 mg/dL) (ETD: -1.7% [95% CI: -2.9, -0.5], P < .05) and level 2 (<54 mg/dL) (ETD: -1.3% [95% CI: -2.1, -0.5], P = .001). TAR was higher with IDeg compared with IGlar-100 at level 1 (181-250 mg/dL) (ETD: 4.0% [95% CI: 0.8, 7.3], P < .05) and level 2 (> 250 mg/dL) (ETD: 4.0% [95% CI: 0.8, 7.2], P < .05). The mean CV was lower with IDeg than that with IGlar-100 (ETD: -3.4% [95% CI: -5.6, -1.2], P < .05).

CONCLUSION

For people with T1D suffering from recurrent nocturnal severe hypoglycemia, treatment with IDeg, compared with IGlar-100, results in a lower TBR and CV during the night at the expense of more TAR.

Current state of the art and future directions for implantable sensors in medical technology: Clinical needs and engineering challenges

Implantable sensors have revolutionized the way we monitor biophysical and biochemical parameters by enabling real-time closed-loop intervention or therapy. These technologies align with the new era of healthcare known as healthcare 5.0, which encompasses smart disease control and detection, virtual care, intelligent health management, smart monitoring, and decision-making. This review explores the diverse biomedical applications of implantable temperature, mechanical, electrophysiological, optical, and electrochemical sensors. We delve into the engineering principles that serve as the foundation for their development. We also address the challenges faced by researchers and designers in bridging the gap between implantable sensor research and their clinical adoption by emphasizing the importance of careful consideration of clinical requirements and engineering challenges. We highlight the need for future research to explore issues such as long-term performance, biocompatibility, and power sources, as well as the potential for implantable sensors to transform healthcare across multiple disciplines. It is evident that implantable sensors have immense potential in the field of medical technology. However, the gap between research and clinical adoption remains wide, and there are still major obstacles to overcome before they can become a widely adopted part of medical practice.

Reproducibility of continuous glucose monitoring results under real-life conditions in an adult population: a functional data analysis

Continuous glucose monitoring systems (CGM) are a very useful tool to understand the behaviour of glucose in different situations and populations. Despite the widespread use of CGM systems in both clinical practice and research, our understanding of the reproducibility of CGM data remains limited. The present work examines the reproducibility of the results provided by a CGM system in a random sample of a free-living adult population, from a functional data analysis approach. Functional intraclass correlation coefficients (ICCs) and their 95% confidence intervals (CI) were calculated to assess the reproducibility of CGM results in 581 individuals. 62% were females 581 participants (62% women) mean age 48 years (range 18-87) were included, 12% had previously been diagnosed with diabetes. The inter-day reproducibility of the CGM results was greater for subjects with diabetes (ICC 0.46 [CI 0.39-0.55]) than for normoglycaemic subjects (ICC 0.30 [CI 0.27-0.33]); the value for prediabetic subjects was intermediate (ICC 0.37 [CI 0.31-0.42]). For normoglycaemic subjects, inter-day reproducibility was poorer among the younger (ICC 0.26 [CI 0.21-0.30]) than the older subjects (ICC 0.39 [CI 0.32-0.45]). Inter-day reproducibility was poorest among normoglycaemic subjects, especially younger normoglycaemic subjects, suggesting the need to monitor some patient groups more often than others.

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.

Improving the Accuracy of Continuous Blood Glucose Measurement Using Personalized Calibration and Machine Learning

Despite tremendous developments in continuous blood glucose measurement (CBGM) sensors, they are still not accurate for all patients with diabetes. As glucose concentration in the blood is <1% of the total blood volume, it is challenging to accurately measure glucose levels in the interstitial fluid using CBGM sensors due to within-patient and between-patient variations. To address this issue, we developed a novel data-driven approach to accurately predict CBGM values using personalized calibration and machine learning. First, we scientifically divided measured blood glucose into smaller groups, namely, hypoglycemia (<80 mg/dL), nondiabetic (81-115 mg/dL), prediabetes (116-150 mg/dL), diabetes (151-181 mg/dL), severe diabetes (181-250 mg/dL), and critical diabetes (>250 mg/dL). Second, we separately trained each group using different machine learning models based on patients' personalized parameters, such as physical activity, posture, heart rate, breath rate, skin temperature, and food intake. Lastly, we used multilayer perceptron (MLP) for the D1NAMO dataset (training to test ratio: 70:30) and grid search for hyperparameter optimization to predict accurate blood glucose concentrations. We successfully applied our proposed approach in nine patients with type 1 diabetes and observed that the mean absolute relative difference (MARD) decreased from 17.8% to 8.3%.

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.

Continuous Glucose Monitoring (CGM) in Sports-A Comparison between a CGM Device and Lab-Based Glucose Analyser under Resting and Exercising Conditions in Athletes

The objective of this pilot study was to compare glucose concentrations in capillary blood (CB) samples analysed in a laboratory by a validated method and glucose concentrations measured in the interstitial fluid (ISF) by continuous glucose monitoring (CGM) under different physical activity levels in a postprandial state in healthy athletes without diabetes. As a physiological shift occurs between glucose concentration from the CB into the ISF, the applicability of CGM in sports, especially during exercise, as well as the comparability of CB and ISF data necessitate an in-depth assessment. Ten subjects (26 ± 4 years, 67 ± 11 kg bodyweight (BW), 11 ± 3 h) were included in the study. Within 14 days, they underwent six tests consisting of (a) two tests resting fasted (HC_Rest/Fast and LC_Rest/Fast), (b) two tests resting with intake of 1 g glucose/kg BW (HC_Rest/Glc and LC_Rest/Glc), (c) running for 60 min at moderate (ModExerc/Glc), and (d) high intensity after intake of 1 g glucose/kg BW (IntExerc/Glc). Data were collected in the morning, following a standardised dinner before test day. Sensor-based glucose concentrations were compared to those determined from capillary blood samples collected at the time of sensor-based analyses and subjected to laboratory glucose measurements. Pearson's r correlation coefficient was highest for Rest/Glc (0.92, p < 0.001) compared to Rest/Fast (0.45, p < 0.001), ModExerc/Glc (0.60, p < 0.001) and IntExerc/Glc (0.70, p < 0.001). Mean absolute relative deviation (MARD) and standard deviation (SD) was smallest for resting fasted and similar between all other conditions (Rest/Fast: 8 ± 6%, Rest/Glc: 17 ± 12%, ModExerc/Glc: 22 ± 24%, IntExerc/Glc: 18 ± 17%). However, Bland-Altman plot analysis showed a higher range between lower and upper limits of agreement (95% confidence interval) of paired data under exercising compared to resting conditions. Under resting fasted conditions, both methods produce similar outcomes. Under resting postprandial and exercising conditions, respectively, there are differences between both methods. Based on the results of this study, the application of CGM in healthy athletes is not recommended without concomitant nutritional or medical advice.

Diabetic Ketoacidosis in a Patient With Type I Diabetes Treated With a Closed-Loop Sensor-Augmented Insulin Infusion System

Background/Objective

Closed-loop insulin infusion systems (CLSs) such as Tandem t:slim with Control-IQ (t:slim CIQ) improve glycemic control and decrease diabetic ketoacidosis (DKA) risk in type 1 diabetes mellitus (T1DM). We report a case of CLS failure, likely from tirzepatide-induced volume depletion, leading to DKA.

Case Report

A 36-year-old woman with T1DM on t:slim CIQ CLS was prescribed tirzepatide for weight loss. Three months later, 4 days after the last tirzepatide injection, she presented with worsening nausea, vomiting, 50-lbs weight loss, minimal oral intake for 3 days, and positive urine ketone result. Her heart rate was 137 beats/min and respiratory rate was 35 breaths/min, and she had Kussmaul breathing, with dry oral mucosa indicating volume depletion. Laboratory examination showed a fingerstick glucose level of 289 mg/dL, serum glucose level of 322 mg/dL, bicarbonate level of 12 mmol/L, and anion gap of 21 mmol/L confirming high-anion-gap metabolic acidosis, suggesting DKA. A concurrent continuous glucose monitor (CGM) reading was 40 mg/dL. The CLS and CGM were removed. DKA resolved within 72 hours (serum glucose level of 143 mg/dL, anion gap of 8 mmol/L, bicarbonate level of 24 mmol/L) on intravenous insulin and fluids. The CLS and CGM were restarted with good glycemic control. Tirzepatide was discontinued to avoid future episodes of volume depletion.

Discussion

Volume depletion affects interstitial fluid glucose levels due to compensatory mechanisms. This may result in CLS failure due to CGM dependence on interstitial glucose measurements, precipitating DKA.

Conclusion

Patients on CLS therapy should be cautioned against CLS failure in volume-depleted states with interstitial glucose-level changes. A back-up plan with multiple daily insulin injections should be discussed.

Beyond A1C: exploring continuous glucose monitoring metrics in managing diabetes

Hemoglobin A1c (HbA1c) has long been considered a cornerstone of diabetes mellitus (DM) management, as both an indicator of average glycemia and a predictor of long-term complications among people with DM. However, HbA1c is subject to non-glycemic influences which confound interpretation and as a measure of average glycemia does not provide information regarding glucose trends or about the occurrence of hypoglycemia and/or hyperglycemia episodes. As such, solitary use of HbA1c, without accompanying glucose data, does not confer actionable information that can be harnessed to guide targeted therapy in many patients with DM. While conventional capillary blood glucose monitoring (BGM) sheds light on momentary glucose levels, in practical use the inherent infrequency of measurement precludes elucidation of glycemic trends or reliable detection of hypoglycemia or hyperglycemia episodes. In contrast, continuous glucose monitoring (CGM) data reveal glucose trends and potentially undetected hypo- and hyperglycemia patterns that can occur between discrete BGM measurements. The use of CGM has grown significantly over the past decades as an ever-expanding body of literature demonstrates a multitude of clinical benefits for people with DM. Continually improving CGM accuracy and ease of use have further fueled the widespread adoption of CGM. Furthermore, percent time in range correlates well with HbA1c, is accepted as a validated indicator of glycemia, and is associated with the risk of several DM complications. We explore the benefits and limitations of CGM use, the use of CGM in clinical practice, and the application of CGM to advanced diabetes technologies.

Mixed Meal Tolerance Test Versus Continuous Glucose Monitoring for an Effective Diagnosis of Persistent Post-Bariatric Hypoglycemia

Gastric bypass determines an increase in incretin secretion and glucose excursions throughout the day and may sometimes entail the development of severe post-bariatric hypoglycemia (PBH). However, there is no consensus on the gold standard method for its diagnosis. In this study, we evaluated the usefulness of a mixed meal tolerance test (MMTT) and continuous glucose monitoring (CGM) for the diagnosis of PBH, defined as glucose levels <54 mg/dL (3.0 mmol/L). We found that hypoglycemia occurred in 60% of patients after the MMTT and in 75% during CGM, and it was predominantly asymptomatic. The MMTT confirmed the diagnosis of PBH in 88.9%of patients in whom surgery had been performed more than three years ago, in comparison to 36.4% in cases with a shorter postsurgical duration. CGM diagnosed nocturnal asymptomatic hypoglycemia in 70% of patients, and daytime postprandial hypoglycemia in 25% of cases. The mean duration of asymptomatic hypoglycemia was more than 30 min a day. Patients with ≥2% of their CGM readings with hypoglycemia exhibited a higher degree of glucose variability than those with <1% of the time in hypoglycemia. Our results show that the MMTT may be a useful dynamic test to confirm the occurrence of hypoglycemia in a large number of patients with persistent and recurrent PBH during long-term follow-up after gastric bypass. CGM, on its part, helps identify hypoglycemia in the real-world setting, especially nocturnal asymptomatic hypoglycemia, bringing to light that PBH is not always postprandial.

Clinical use of continuous glucose monitoring in critically ill pediatric patients with diabetic ketoacidosis

BACKGROUND

The use of continuous glucose monitoring (CGM) in pediatric patients with diabetic ketoacidosis (DKA) remains investigational, and data on its accuracy in pediatric intensive care units (PICU) are limited. This study evaluated the accuracy of three CGM devices in pediatric patients with DKA in the PICU.

METHODS

We compared 399 matched pairs of CGM and point-of-care (POC) capillary glucose values and grouped patients based on whether they changed their CGM sensor during their PICU stay.

RESULTS

Eighteen patients with a mean age of 10.98 ± 4.20 years were included, with three patients in the sensor change group. The overall mean absolute relative difference (MARD) was 13.02 %. The Medtronic Guardian Sensor 3 (n = 331), Dexcom G6 (n = 41), and Abbott FreeStyle Libre 1 (n = 27) showed MARD values of 13.40, 11.12, and 11.33 %, respectively. The surveillance error grid (SEG), Bland-Altman plot, and Pearson's correlation coefficient demonstrated satisfactory clinical accuracy of the CGM devices (SEG zones A and B, 98.5%; mean difference, 15.5 mg/dL; r2, 0.76, p<0.0001). MARD was significantly lower in subjects who did not experience a sensor change (11.74 % vs. 17.31 %, p<0.048). Also, a statistically significant negative correlation was found between serum bicarbonate levels and POC-CGM values (r = -0.34, p<0.001).

CONCLUSIONS

The severity of DKA has a major effect on reducing the accuracy of the CGM, especially during the first several days in the ICU. The reduced accuracy appears to be related to acidosis, as reflected in the serum bicarbonate levels.

Prevalence, characteristics, and health-related quality of life of continuous glucose monitoring use according to the Behavioral Risk Factor Surveillance System 2014-2020

BACKGROUND: Continuous glucose monitoring (CGM) can improve behavioral and clinical outcomes. The use of CGM in real-world practice appears to be increasing. However, actual prevalence and characteristics of using CGM in real-world practice are unknown. OBJECTIVE: To investigate the prevalence of CGM use by American adults with diabetes mellitus and differences in demographics and health-related quality of life (HRQOL) between users of CGM and self-monitoring of blood glucose (SMBG). METHODS: This serial cross-sectional study using 2014-2020 Behavioral Risk Factor Surveillance System data included nonpregnant adults with self-reported diabetes using CGM or 4-15 times daily SMBG. Outcomes were prevalence of CGM use, demographics, and the 4-item Centers for Disease Control and Prevention HRQOL (CDC HRQOL-4). Unadjusted analysis was performed using univariable regression, and adjusted analysis was performed using nearest neighbor matching to compare CDC HRQOL-4 between SMBG and CGM groups in SAS Studio version 5.2. RESULTS: Among 12,053 included respondents, 231 (1.9%) reported using CGM, and prevalence increased from 0.4% in 2014 to 4.1% in 2020. Compared with SMBG users, CGM users were more likely to be younger (50.3 years vs 56.1 years; P < 0.001), employed (59.6% vs 30.6%; P = 0.001), earn at least $75,000/year (48.5% vs 22.0%, P < 0.001), have insurance coverage (99.7% vs 95.4%; P = 0.005), and report fewer comorbidities (history of myocardial infarction, stroke, arthritis, depressive disorder, and kidney disease; all P < 0.05). After nearest neighbor matching, diabetes management-related characteristics were shown to have statistically significant differences between CGM and SMBG users including: age at diabetes diagnosis (30.6 vs 35.6 years; P = 0.005), not seeing a doctor because of cost concern (2.6% vs 7.8%; P = 0.011), checking hemoglobin A1c biannually (91.3% vs 86.6%; P = 0.047), performing daily foot self-examination (58.9% vs 69.6%; P = 0.028), receiving foot examination by a health care professional annually (87.9% vs 93.5%; P = 0.048), and receiving a shingles vaccine in the past (16.5% vs 10.1%; P = 0.024). CDC HRQOL-4 were shown to be similar between the 2 groups across the 4 domains (general health, physical, mental, and combined physical and mental health). CONCLUSIONS: An increased trend in CGM use was observed from 2014 to 2020. Economic factors were associated with CGM use over SMBG, and CGM use did not show a difference in HRQOL measured across the 4 domains.

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.

Insight into continuous glucose monitoring: from medical basics to commercialized devices

According to the latest statistics, more than 537 million people around the world struggle with diabetes and its adverse consequences. As well as acute risks of hypo- or hyper- glycemia, long-term vascular complications may occur, including coronary heart disease or stroke, as well as diabetic nephropathy leading to end-stage disease, neuropathy or retinopathy. Therefore, there is an urgent need to improve diabetes management to reduce the risk of complications but also to improve patient's quality life. The impact of continuous glucose monitoring (CGM) is well recognized, in this regard. The current review aims at introducing the basic principles of glucose sensing, including electrochemical and optical detection, summarizing CGM technology, its requirements, advantages, and disadvantages. The role of CGM systems in the clinical diagnostics/personal testing, difficulties in their utilization, and recommendations are also discussed. In the end, challenges and prospects in future CGM systems are discussed and non-invasive, wearable glucose biosensors are introduced. Though the scope of this review is CGMs and provides information about medical issues and analytical principles, consideration of broader use will be critical in future if the right systems are to be selected for effective diabetes management.

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.

Accurate Post-Calibration Predictions for Noninvasive Glucose Measurements in People Using Confocal Raman Spectroscopy

In diabetes prevention and care, invasiveness of glucose measurement impedes efficient therapy and hampers the identification of people at risk. Lack of calibration stability in non-invasive technology has confined the field to short-term proof of principle. Addressing this challenge, we demonstrate the first practical use of a Raman-based and portable non-invasive glucose monitoring device used for at least 15 days following calibration. In a home-based clinical study involving 160 subjects with diabetes, the largest of its kind to our knowledge, we find that the measurement accuracy is insensitive to age, sex, and skin color. A subset of subjects with type 2 diabetes highlights promising real-life results with 99.8% of measurements within A + B zones in the consensus error grid and a mean absolute relative difference of 14.3%. By overcoming the problem of calibration stability, we remove the lingering uncertainty about the practical use of non-invasive glucose monitoring, boding a new, non-invasive era in diabetes monitoring.

Numerical and clinical precision in hypoglycemia of the intermittent FreeStyle Libre glucose monitoring through an NFC-Bluetooth transmitter associated with the xDrip+ algorithm in diabetic patients under insulin therapy

INTRODUCTION

There are data capture devices that attach to the FreeStyle Libre sensor and convert its communication from NFC (Near-field communication) to Bluetooth technology, generating real-time continuous glucose monitoring. The accuracy of hypoglycemia measurements displayed by smartphone apps using this device has not been established.

METHODS

Study of diagnostic tests. Numerical accuracy was evaluated, utilizing the absolute difference with respect to capillary glucometry (ISO 15197:2015 standard) and clinical accuracy, using the Clarke and Parkes (Consensus) error grids, for glucose measurements less than 70mg/dL performed with the FreeStyle Libre system and with the digital estimation xDrip+ app, in diabetic patients managed with insulin therapy.

RESULTS

Twenty-seven patients were included (TIR 73.4%, TBR70 5.6%), who contributed 83 hypoglycemic events. Numerical accuracy was adequate in similar proportions with the FreeStyle Libre system compared to the xDrip+ app (81.92% vs. 68.67%, p=0.0630). The clinical accuracy evaluation showed that 92.8% of the measurements for xDrip+ and 98.8% for FreeStyle libre met the criteria according to the Parkes (Consensus) grid (p=0.0535); and 79.5% and 91.6% of the measurements met the criteria according to the Clarke grid (p=0.0273), being higher with FreeStyle libre.

CONCLUSIONS

The use of the NFC-Bluetooth transmitter (Miao-Miao) associated with the xDrip+ app does not improve numerical or clinical accuracy for detecting hypoglycemic events in diabetic patients managed with insulin therapy, compared to the FreeStyle Libre device.

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.

Effect of insulin degludec versus insulin glargine U100 on nocturnal glycaemia assessed by plasma glucose profiles in people with type 1 diabetes prone to nocturnal severe hypoglycaemia

AIM

To compare nocturnal glucose profiles according to hourly plasma glucose measurements during treatment with insulin degludec and insulin glargine U100 in a cohort of people with type 1 diabetes prone to nocturnal severe hypoglycaemia.

MATERIALS AND METHODS

The HypoDeg trial is a 2-year investigator-initiated, randomized, controlled crossover trial in 149 participants randomized to treatment with insulin degludec and insulin glargine U100 for 12 months each. The 51 participants in this predefined substudy stayed at least one night in hospital during each treatment arm for plasma glucose samples to be taken. Endpoints were glucose profiles, including mean plasma glucose, glycaemic variability and risk of hypoglycaemia.

RESULTS

There were no differences between treatments regarding mean plasma glucose. We saw a flatter glucose profile during insulin degludec compared with insulin glargine U100 treatment, which had a nadir at 4:00 AM, with a subsequent rise. During treatment with insulin degludec, the participants had lower glycaemic variability, with an estimated treatment difference of -4.3% (95% confidence interval [CI] -8.1 to -0.5; P < 0.05). Participants treated with insulin degludec were less likely to experience nocturnal hypoglycaemia below 3.0 mmol/L (hazard ratio 0.36 [95% CI 0.17-0.73; P < 0.05]).

CONCLUSION

Based on nocturnal plasma glucose measurements, treatment with insulin degludec compared with insulin glargine U100 administered in the evening results in lower glycaemic variability and lower risk of nocturnal hypoglycaemia without differences in mean plasma glucose.

Post-Market Surveillance Assessment of the Clinical Accuracy of a Blood Glucose Monitoring System with an Improved Algorithm for Enhanced Product Performance

BACKGROUND

On-going manufacturer-led post-market surveillance (PMS), assessing the clinical accuracy of blood glucose monitoring (BGM) systems, is critical to substantiate the performance of such products for people with diabetes.

MATERIALS AND METHODS

Batches of Verio test-strip product were randomly and routinely selected over the period from launch of an improved-algorithm product to reporting date and sent to 3 clinic sites for clinician-led accuracy assessment. Accuracy is reported as per recently adopted FDA guidance for BGM systems, EN ISO 15197:2015 and MARD/MAD (Mean absolute relative difference/Mean absolute difference).

RESULTS

Thirty-three individual test-strip batches were evaluated corresponding to 506 unique donors. Accuracy performance - FDA: 98.9% of values within ±15% of comparator; ISO: 99.0% within ±15 mg/dL or ±15% at <100 mg/dL (<5.55 mmol/L) or ≥100 mg/dL (≥5.55 mmol/L) glucose, respectively. Overall MARD was 4.19% with a MARD range of 3.54%-5.73% across all test strip batches.

CONCLUSIONS

This post-market surveillance program demonstrates the new BGM system consistently meets measures of clinical accuracy specified by regulators. This program supports a growing demand by regulators for real-world evidence demonstrating consistent in-market product efficacy as opposed to the current largely passive approach that relies on assessment of reports filed by device users.

Analysis of "Multicenter Evaluation Study Comparing a New Factory-Calibrated Real-Time Continuous Glucose Monitoring System to Existing Flash Glucose Monitoring System"

In an article in the Journal of Diabetes Science and Technology, Ji et al. report on the accuracy of a new factory calibrated continuous glucose monitoring system, the AiDEX CGM (Microtech Medical Company, Ltd., Hangzhou, China). This is the first report from a new manufacturer of a highly accurate factory calibrated CGM. The authors report that the accuracy of the AiDEX CGM is comparable to previous results from Abbott Diabetes Care and Dexcom. However, the study protocol was significantly different from previous studies. This study is the first of numerous studies likely from other manufacturers of CGM technology. It raises the question of how to evaluate sensor performance in the coming era of mass adoption of CGM and increased use of automated insulin delivery systems.

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.

Continuous glucose monitoring during therapeutic hypothermia for hypoxic ischaemic encephalopathy: a feasibility study

OBJECTIVES

Glucose dysregulation is common in infants with hypoxic ischaemic encephalopathy (HIE) and is likely to exacerbate cerebral injury. Infrequent measurement of glucose concentrations makes both identification and prevention of this risk challenging. Continuous glucose monitoring (CGM) has the potential to address both these challenges, but has not been explored in these infants. We aimed to evaluate the feasibility and potential impact of real-time CGM in term infants with HIE being treated with therapeutic hypothermia (TH).

DESIGN

Feasibility study.

SETTING

Tertiary-level neonatal unit, UK.

PATIENTS

Term infants with HIE undergoing TH.

INTERVENTION

A CGM sensor was inserted within 48 hours of birth and kept in situ for the first week of life. Clinical staff were blinded to the CGM recordings and clinical decisions were based on blood glucose assays.

MAIN OUTCOME MEASURES

(1) Accuracy of CGM values during and post TH, (2) Per cent of time spent outside the clinical range (2.6-10 mmol/L), (3) Episodes of hypoglycaemia and hyperglycaemia, (4) Adverse effects.

RESULTS

The accuracy of CGM values during TH were comparable to those when infants were normothermic. There was wide variation in per cent time outside the target range (2.6-10 mmol/L) between infants (median 5%, range 0%-34%). CGM identified 44% of infants with ≥1 episode of hypoglycaemia (<2.6 mmol/L) and 50% with ≥1 episode of hyperglycaemia (>10 mmol/L). No adverse events were observed.

CONCLUSIONS

This study demonstrates that CGM could be a useful adjunct for glucose monitoring in babies undergoing TH who are at risk of both hypoglycaemia and hyperglycaemia.

The Devil Is in the Details: Use, Limitations, and Implementation of Continuous Glucose Monitoring in the Inpatient Setting

Until recently, continuous glucose monitoring (CGM) systems were reserved for use in the outpatient setting or for investigational purposes in hospitalized patients. However, during the coronavirus disease 2019 pandemic, use of CGM in the inpatient setting has grown rapidly. This review outlines important details related to the accuracy, limitations, and implementation of, as well as necessary staff education for, inpatient CGM use and offers a glimpse into the future of CGM in the inpatient setting.

Pilot study in human healthy volunteers on the use of magnetohydrodynamics in needle-free continuous glucose monitoring

The benefits of continuous glucose monitoring (CGM) in diabetes management are extensively documented. Yet, the broader adoption of CGM systems is limited by their cost and invasiveness. Current CGM devices, requiring implantation or the use of hypodermic needles, fail to offer a convenient solution. We have demonstrated that magnetohydrodynamics (MHD) is effective at extracting dermal interstitial fluid (ISF) containing glucose, without the use of needles. Here we present the first study of ISF sampling with MHD for glucose monitoring in humans. We conducted 10 glucose tolerance tests on 5 healthy volunteers and obtained a significant correlation between the concentration of glucose in ISF samples extracted with MHD and capillary blood glucose samples. Upon calibration and time lag removal, the data indicate a Mean Absolute Relative Difference (MARD) of 12.9% and Precision Absolute Relative Difference of 13.1%. In view of these results, we discuss the potential value and limitations of MHD in needle-free glucose monitoring.

Continuous Glucose Deviation Interval and Variability Analysis (CG-DIVA): A Novel Approach for the Statistical Accuracy Assessment of Continuous Glucose Monitoring Systems

BACKGROUND

The accuracy of continuous glucose monitoring (CGM) systems is crucial for the management of glucose levels in individuals with diabetes mellitus. However, the discussion of CGM accuracy is challenged by an abundance of parameters and assessment methods. The aim of this article is to introduce the Continuous Glucose Deviation Interval and Variability Analysis (CG-DIVA), a new approach for a comprehensive characterization of CGM point accuracy which is based on the U.S. Food and Drug Administration requirements for "integrated" CGM systems.

METHODS

The statistical concept of tolerance intervals and data from two approved CGM systems was used to illustrate the CG-DIVA.

RESULTS

The CG-DIVA characterizes the expected range of deviations of the CGM system from a comparison method in different glucose concentration ranges and the variability of accuracy within and between sensors. The results of the CG-DIVA are visualized in an intuitive and straightforward graphical presentation. Compared with conventional accuracy characterizations, the CG-DIVA infers the expected accuracy of a CGM system and highlights important differences between CGM systems. Furthermore, it provides information on the incidence of large errors which are of particular clinical relevance. A software implementation of the CG-DIVA is freely available (https://github.com/IfDTUlm/CGM_Performance_Assessment).

CONCLUSIONS

We argue that the CG-DIVA can simplify the discussion and comparison of CGM accuracy and could replace the high number of conventional approaches. Future adaptations of the approach could thus become a putative standard for the accuracy characterization of CGM systems and serve as the basis for the definition of future CGM performance requirements.

Rossitto J, Ray K, A. Dufurrena Q, Blue RS. Blood Glucose Alterations and Continuous Glucose Monitoring in Centrifuge-Simulated Spaceflight

INTRODUCTION: Sympathetic stimulation is known to be associated with transient alterations of blood glucose (BG) concentration; spaceflight acceleration may be similarly associated with alterations of BG, potentially posing a risk to diabetic individuals engaging in future spaceflight activities. Despite prior studies demonstrating diabetic subjects’ tolerance to centrifuge-simulated spaceflight, data are lacking regarding blood glucose response to hypergravity. It remains unclear whether hypergravity or associated physiological response may pose a risk to diabetics. Continuous glucose monitors (CGM) offer a means of noninvasive glucose monitoring and may be useful in spaceflight and analog environments. Here, we describe the results of continuous glucose monitoring during centrifuge-simulated spaceflight.METHODS: Subjects participated in 1–5 centrifuge-simulated spaceflight profiles (maximum +4.0 Gz, +6.0 Gx, 6.1 G resultant). Data collection included heart rate, blood pressure, electrocardiogram, continuous glucose via CGM, intermittent fingerstick BG, and postrun questionnaires regarding symptoms related to hypergravity exposure.RESULTS: CGM data were collected from 26 subjects, including 4 diabetics. While diabetic subjects had significantly higher BG compared to nondiabetics, this was not associated with any difference in symptoms or tolerance. Transient hypergravity-associated CGM glucose alterations did not affect tolerance of the centrifuge experience. CGM data were found to be reliable with occasional exceptions, including four instances of false critical low glucose alarms.DISCUSSION: While further study is necessary to better characterize CGM fidelity during hypergravity and other spaceflight-related stressors, CGM may be a feasible option for spaceflight and analog settings. As in prior studies, individuals with well-controlled diabetes appear able to tolerate the accelerations anticipated for commercial spaceflight.Ong KM, Rossitto JJ, Ray K, Dufurrena QA, Blue RS. Blood glucose alterations and continuous glucose monitoring in centrifuge-simulated spaceflight. Aerosp Med Hum Perform. 2022; 93(9):688–695.

Mean Absolute Relative Difference of Blood Glucose Monitoring Systems and Relationship to ISO 15197

BACKGROUND

The analytical quality of a blood glucose monitoring system (BGMS) is often assessed according to the requirements described in the international standard ISO 15197. However, the mean absolute relative difference (MARD) is sometimes used as well. This analysis aims at providing empirical data from BGMS evaluation studies conducted according to ISO 15197 and at providing an estimation of how MARD and percentage of measurement results within ISO accuracy limits are related.

METHODS

Results of 77 system accuracy evaluations conducted according to ISO 15197 were used to calculate MARD between BGMS and a laboratory comparison method's results (glucose oxidase or hexokinase method). Additionally, bias and 95%-limits of agreement (LoA) using the Bland and Altman method were calculated.

RESULTS

MARD results ranged from 2.3% to 20.5%. The lowest MARD of a test strip lot that showed <95% of results within ISO limits was 6.1%. The distribution of MARD results shows that only 3.6% of test strip lots with a MARD equal to or below 7% showed <95% of results within ISO limits (2.2% of all test strip lots). Bias of test strip lots that showed ≥95% of results within the limits ranged from -10.3% to +7.4%. The half-width of the 95%-LoA of test strip lots that showed ≥95% of results within the limits ranged from 4.8% to 24.0%.

CONCLUSION

There is a threshold MARD that may allow an estimate whether ISO 15197 requirements are fulfilled, but this statement cannot be made with certainty.

Variation of Mean Absolute Relative Differences of Continuous Glucose Monitoring Systems Throughout the Day

BACKGROUND

There is an increasing use of continuous glucose monitoring (CGM) by people with diabetes. Measurement performance is often characterized by the mean absolute relative difference (MARD). However, MARD is influenced by a number of factors and little is known about whether MARD is stable throughout the day.

MATERIAL AND METHODS

A total of 24 participants with type 1 diabetes were enrolled in the study. The study was performed for seven in-patient days. Participants wore two CGM systems in parallel and performed additional frequent blood glucose (BG) measurements. On two days, glucose excursions were induced.MARD was calculated between pairs of CGM and BG values, with BG values serving as reference values. ARD values calculated from CGM-BG pairs were grouped by hour of the day. Results were analyzed separately for glucose excursion days and for regular days.

RESULTS

Total MARDs for the complete study duration were 12.5% ± 3.6% and 13.2% ± 2.4% (n = 24). Throughout the day marked variability of MARD was observed (8.0% ± 1.3%-16.3% ± 2.9% (G5); 9.1% ± 1.4%-16.3% ± 5.3% (FL), up to n = 157 each). Low(est) MARD values were observed before breakfast and dinner, when subjects were in or near a fasting state. Especially after breakfast and lunch, MARD values were higher than average.

CONCLUSIONS

Analytical performance of the two CGM systems, assessed by MARD, was found to vary markedly throughout the day. Activities of daily life likely triggered these variations. An increasing number of CGM users base therapeutic decisions on CGM values, and they should be aware of these variations of performance throughout the day.

Validation of the Application of Solid Contact Ion-Selective Electrode for Off-Body Sweat Ion Monitoring

The solid contact ion-selective electrode (ISE) is a promising skin-interfaced monitoring system for sweat ions. Despite a growing number of on-body usages of ISE with fancy new materials and device fabrications, there are very few reports attempting to validate ISE results with a gold standard technique. For this purpose, this work uses inductively coupled plasma-optical emission spectrometry (ICP-OES) as a reference technique to conduct a direct evaluation of the sweat sodium and potassium ion levels obtained by ISE in an off-body approach. Eight healthy male subjects were recruited to collect exercise-induced sweat. It was found that sweat sodium and potassium ions present a rather wide concentration range. The sweat sodium concentration did not vary greatly in an exercise period of half an hour, while the sweat potassium concentration typically decreased with exercise. Mineral drink intake had no clear impact on the sweat sodium level, but increased the sweat potassium level. A paired t-test and mean absolute relative difference (MARD) analysis, a method typically used for evaluating the performance of glucometers, was employed to compare the results of ISE and ICP-OES. The statistical analysis validated the feasibility of ISE for measuring sweat ions, although better accuracy is required. Our data suggests that overweight subjects are likely to possess a higher sweat sodium level.