A head-to-head comparison between Guardian Connect and FreeStyle Libre systems and an evaluation of user acceptability of sensors in patients with type 1 diabetes

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

BACKGROUND

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

METHOD

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

RESULTS

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

CONCLUSIONS

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

Digital applications for diet monitoring, planning, and precision nutrition for citizens and professionals: a state of the art

The objective of this review was to critically examine existing digital applications, tailored for use by citizens and professionals, to provide diet monitoring, diet planning, and precision nutrition. We sought to identify the strengths and weaknesses of such digital applications, while exploring their potential contributions to enhancing public health, and discussed potential developmental pathways. Nutrition is a critical aspect of maintaining good health, with an unhealthy diet being one of the primary risk factors for chronic diseases, such as obesity, diabetes, and cardiovascular disease. Tracking and monitoring one's diet has been shown to help improve health and weight management. However, this task can be complex and time-consuming, often leading to frustration and a lack of adherence to dietary recommendations. Digital applications for diet monitoring, diet generation, and precision nutrition offer the promise of better health outcomes. Data on current nutrition-based digital tools was collected from pertinent literature and software providers. These digital tools have been designed for particular user groups: citizens, nutritionists, and physicians and researchers employing genetics and epigenetics tools. The applications were evaluated in terms of their key functionalities, strengths, and limitations. The analysis primarily concentrated on artificial intelligence algorithms and devices intended to streamline the collection and organization of nutrition data. Furthermore, an exploration was conducted of potential future advancements in this field. Digital applications designed for the use of citizens allow diet self-monitoring, and they can be an effective tool for weight and diabetes management, while digital precision nutrition solutions for professionals can provide scalability, personalized recommendations for patients, and a means of providing ongoing diet support. The limitations in using these digital applications include data accuracy, accessibility, and affordability, and further research and development are required. The integration of artificial intelligence, machine learning, and blockchain technology holds promise for improving the performance, security, and privacy of digital precision nutrition interventions. Multidisciplinarity is crucial for evidence-based and accessible solutions. Digital applications for diet monitoring and precision nutrition have the potential to revolutionize nutrition and health. These tools can make it easier for individuals to control their diets, help nutritionists provide better care, and enable physicians to offer personalized treatment.

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

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

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.

Time In Tight Range in children and adolescents with type 1 diabetes: A cross-sectional observational single centre study evaluating efficacy of new advanced technologies

INTRODUCTION

Early and tight glycaemic control is crucial to prevent long-term complications of Type 1 Diabetes (T1D). The aim of our study was to compare glucose metrics, including Time In Tight Range (TITR), in a real-world setting.

METHODS

We performed a single-centre cross-sectional study in 534 children and adolescents with T1D. Participants were divided into four groups (multiple daily injections + real-time Continuous glucose monitoring (CGM), multiple daily injections + intermittently scanned CGM, sensor augmented pump (SAP), and Advanced Hybrid Closed-Loop (AHCL). Demographical and clinical data were collected and analysed.

RESULTS

The group with AHCL showed significantly higher Time In Range (TIR) (71.31% ± 10.88) than SAP (57.82% ± 14.98; p < 0.001), MDI + rtCGM (54.56% ± 17.04; p < 0.001) and MDI + isCGM (52.17% ± 19.36; p < 0.001) groups with a lower Time Above Range (p < 0.001). The group with AHCL also showed lower Time Below Range than MDI + isCGM and SAP groups (p < 0.01). The overall TITR was 37% ± 14 with 19% of participants who reached a TITR ≥50% with a mean TIR of 81%. AHCL had significantly higher TITR (45.46% ± 11.77) than SAP (36.25% ± 13.53; p < 0.001), MDI + rtCGM (34.03% ± 13.89; p < 0.001) and MDI + isCGM (33.37% ± 15.84; p < 0.001) groups with a lower Coefficient of Variation (p < 0.001).

CONCLUSIONS

Our study indicates that AHCL ensures a better glycaemic control with an improvement in both TIR and TITR, along with a reduction in CV. Implementation of automated insulin delivery systems should be considered in the treatment of children and adolescents with T1D.

Accuracy of a novel real-time continuous glucose monitoring system: a prospective self-controlled study in thirty hospitalized patients with type 2 diabetes

Aims

The present study aimed to investigate the accuracy of the Glunovo® real-time continuous glucose monitoring system (rtCGMS).

Methods

We conducted a 14-day interstitial glucose level monitoring using Glunovo® rtCGMS on thirty hospitalized patients with type 2 diabetes. The flash glucose monitoring (FGM) was used as a self-control. Consistency tests, error grid analysis, and calculation of the mean absolute relative difference (MARD) were performed using R software to assess the accuracy of Glunovo® rtCGMS.

Results

Glunovo® exhibited an overall MARD value of 8.89% during hospitalization, compared to 10.42% for FGM. The overall percentages of glucose values within ±10%/10, ± 15%/15, ± 20%/20, ± 30%/30, and ±40%/40 of the venous blood glucose reference value were 63.34%, 81.31%, 90.50%, 97.29%, and 99.36% for Glunovo®, respectively, compared with 61.58%, 79.63%, 88.31%, 96.22% and 99.23% for FGM. The Clarke Error Grid Analysis showed that 99.61% of Glunovo® glucose pairs and 100.00% of FGM glucose pairs within zones A and B.

Conclusion

Our study confirms the superior accuracy of Glunovo® in monitoring blood glucose levels among hospitalized patients with type 2 diabetes.

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.

Wearable filamentary continuous sensor for interstitial glucose detection in diabetes management

The development of novel diabetes monitoring sensors is important for the diabetes management of millions of diabetic patients. This work reports a flexible filamentary continuous glucose monitoring (CGM) sensor. A multilayer CGM sensor has been constructed on titanium filament with low cost and ease of use. The sensor, made of flexible material, offers better adaptability and comfort than traditional rigid filament CGM sensors, allowing continuous monitoring of subcutaneous blood glucose levels to provide patients with treatment strategies. The performance and reliability of the sensor were verified through rat experiments. The trend of the increase and decrease of the detected current was generally consistent with the actual blood glucose, and the detected values were located in regions A and B of the Clarke error grid. The results show that the sensor has the advantages of high sensitivity, high accuracy and fast response speed, which is suitable for monitoring the blood glucose level for a long time and has a broad application prospect in diabetes monitoring, exercise monitoring, health management and clinical application.

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.

Preoperative considerations for patients with diabetes

INTRODUCTION

Patients undergoing surgery require a thorough assessment preoperatively. Hyperglycemia is associated with poor outcomes, and stability of glucose levels is an important factor in preoperative management. Diabetes presents a particular challenge since patients are often on multiple medications encompassing glycemic management and cardiovascular therapies.

AREAS COVERED

A PubMed search of published data and reviews on preoperative approaches in diabetes was conducted. Consensus opinion drives most of the guidelines and recommendations for management of diabetes in surgical patients. Pathophysiology is often complex with varying levels of glucose and surgical stress. Establishing well-controlled diabetes prior to surgical intervention should be standard practice in non-emergent procedures. We review the best practices for implementing preoperative assessment, with diabetes with a focus on diabetes medications.

EXPERT OPINION

The management of a patient preoperatively varies by region and country. Institutions differ in approaches to preoperative evaluation and the establishment of consistent approaches would provide a platform for monitoring patient outcomes. Multidisciplinary teams and pre-assessment clinics for preoperative evaluation can enhance patient care for those undergoing surgery.

Clinical application guidelines for blood glucose monitoring in China (2022 edition)

Glucose monitoring is an important component of diabetes management. The Chinese Diabetes Society (CDS) has been producing evidence-based guidelines on the optimal use of glucose monitoring since 2011. In recent years, new technologies in glucose monitoring and more clinical evidence, especially those derived from Chinese populations, have emerged. In this context, the CDS organised experts to revise the Clinical application guidelines for blood glucose monitoring in China in 2021. In this guideline, we focus on four methods of glucose monitoring that are commonly used in clinical practice, including capillary glucose monitoring, glycated haemoglobin A1c, glycated albumin, and continuous glucose monitoring. We describe the definitions and technical characteristics of these methods, the factor that may interfere with the measurement, the advantages and caveats in clinical practice, the interpretation of glucose metrics, and the relevant supporting evidence. The recommendations for the use of these methods are also provided. The various methods of glucose monitoring have their strengths and limitations and cannot be replaced by one another. We hope that these guidelines could aid in the optimal application of common methods of glucose monitoring in clinical practice for better diabetes care.