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

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

The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors.

INTRODUCTION: An error grid compares measured versus reference glucose concentrations to assign clinical risk values to observed errors. Widely used error grids for blood glucose monitors (BGMs) have limited value because they do not also reflect clinical accuracy of continuous glucose monitors (CGMs). METHODS: Diabetes Technology Society (DTS) convened 89 international experts in glucose monitoring to (1) smooth the borders of the Surveillance Error Grid (SEG) zones and create a user-friendly tool-the DTS Error Grid; (2) define five risk zones of clinical point accuracy (A-E) to be identical for BGMs and CGMs; (3) determine a relationship between DTS Error Grid percent in Zone A and mean absolute relative difference (MARD) from analyzing 22 BGM and nine CGM accuracy studies; and (4) create trend risk categories (1-5) for CGM trend accuracy. RESULTS: The DTS Error Grid for point accuracy contains five risk zones (A-E) with straight-line borders that can be applied to both BGM and CGM accuracy data. In a data set combining point accuracy data from 18 BGMs, 2.6% of total data pairs equally moved from Zones A to B and vice versa (SEG compared with DTS Error Grid). For every 1% increase in percent data in Zone A, the MARD decreased by approximately 0.33%. We also created a DTS Trend Accuracy Matrix with five trend risk categories (1-5) for CGM-reported trend indicators compared with reference trends calculated from reference glucose. CONCLUSION: The DTS Error Grid combines contemporary clinician input regarding clinical point accuracy for BGMs and CGMs. The DTS Trend Accuracy Matrix assesses accuracy of CGM trend indicators.

An SMS-Guided Basal Insulin Titration in People with Type 2 Diabetes New on Insulin.

INTRODUCTION: The shortage of general practitioners (GPs) and the increasing prevalence of type 2 diabetes create significant pressure on primary healthcare services. To enable that medical services are available to all that need it, innovative solutions are needed. One of those, a Short Message Service (SMS)-supported basal insulin titration service is investigated in this study. The primary objective was to determine the percentage of subjects who achieved stable fasting blood glucose (FBG) within their individual target range with this service after week 16. METHODS: This single-arm, 16-week study aimed to enroll 111 adults diagnosed with type 2 diabetes that needed insulin. The study subjects measured their FBG 4 consecutive days to establish a baseline, then received SMS prompts for daily FBG measurements and evening insulin injections until their FBG stabilized within the target range. Adjusting the insulin based on the FBG. Once stabilization was achieved, subjects continued with their optimal insulin dose for the remainder of the study. Sixteen weeks after the baseline, subjects measured FBG for 4 days before visit 4, where these values were read by the healthcare provider. RESULTS: Out of the planned 111 subjects, only 30 were enrolled, with one withdrawal prior to service activation. Challenges in subject recruitment were attributed to the COVID-19 outbreak, limited eligibility, competing studies, and new medications delaying insulin initiation. Subjects were on average 59.97 years old, had an HbA1c of 9.29% a FBG of 205.64 mg/dl, and had diabetes for 10 years. Among the 29 subjects who started the service, 72% achieved successful titration at visit 4, with a median time of 49 days. Notable improvements were observed in HbA1c levels (decreased by 1.58%) and FBG levels (decreased by 64 mg/dl) over the 16-week study period. No adverse events or device-related issues were reported. CONCLUSIONS: Despite recruitment challenges, guided basal insulin titration holds promise for insulin therapy initiation in individuals. The findings emphasize the potential of tele-medical approaches, specifically through remote messaging, in managing diabetes and improving therapy adherence.

Characteristics of Nocturnal Hypoglycaemic Events and Their Impact on Glycaemia.

BACKGROUND: Nocturnal hypoglycaemia is a burden for people with diabetes, particularly when treated with multiple daily injections (MDI) therapy. However, the characteristics of nocturnal hypoglycaemic events in this patient group are only poorly described in the literature. METHOD: Continuous glucose monitoring (CGM) data from 185 study participants with type 1 diabetes using MDI therapy were collected under everyday conditions for up to 13 weeks. Hypoglycaemic events were identified as episodes of consecutive CGM readings <70 mg/dl or <54 mg/dl for at least 15 minutes. Subsequently, the time <54 mg/dl (TB54), time below range (TBR), time in range (TIR), time above range (TAR), glucose coefficient of variation (CV), and incidence of hypoglycaemic events were calculated for diurnal and nocturnal periods. Furthermore, the effect of nocturnal hypoglycaemic events on glucose levels the following day was assessed. RESULTS: The incidence of hypoglycaemic events <70 mg/dl was significantly lower during the night compared to the day, with 0.8 and 3.8 events per week, respectively, while the TBR, TB54, and incidence of events with CGM readings <54 mg/dl was not significantly different. Nocturnal hypoglycaemic events <70 mg/dl were significantly longer (60 vs 35 minutes) and enveloped by less rapidly changing glucose levels. On days following nights containing hypoglycaemic events, there was a decrease in TAR, mean CGM glucose level and morning glucose levels and an increase in TB54, TBR, and CV. CONCLUSIONS: The results showed that nocturnal hypoglycaemic events are a common occurrence in persons with type 1 diabetes using MDI with significant differences between the characteristics of nocturnal and diurnal events.

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

BACKGROUND: In this multicenter study, performance of a novel continuous glucose monitoring (CGM) system was evaluated. METHODS: Adult participants with diabetes were included in the study. They each wore three sensors of the CGM system on the upper arms for up to 14 days. During four in-clinic visits, frequent comparison measurements with capillary blood glucose (BG) samples were performed. The primary endpoint was the 20/20 agreement rate (AR): the percentage of CGM readings within ±20 mg/dL (at BG values <100 mg/dL) or ±20% (at BG values ≥100 mg/dL) of the comparator. Further evaluations included mean absolute relative difference (MARD) and 20/20 AR in different BG ranges and across the wear time. RESULTS: Data from 48 participants and 139 sensors were analyzed. During in-clinic sessions the 20/20 AR was 90.5% and the MARD was 9.2%. For BG ranges <70, 70-180, and >180 mg/dL, 20/20 AR was 94.3%, 89.0%, and 92.5%, respectively. At the beginning, middle, and end of sensor wear time, 20/20 AR was 92.8%, 91.5%, and 85.9%, respectively. The 14-day survival probability was 82.4%. Pain and bleeding after sensor insertion were within the expected range. Based on the study outcome, the use of the device is regarded as safe. CONCLUSIONS: The system showed a good performance compared to capillary BG measurements. This level of accuracy could be shown over the entire measurement range, especially in the low glycemic range, and the whole wear time of the sensors. The results of this study are supporting a non-adjunctive use of the device.

Nocturnal Hypoglycemia in the Era of Continuous Glucose Monitoring.

Nocturnal hypoglycemia is a common acute complication of people with diabetes on insulin therapy. In particular, the inability to control glucose levels during sleep, the impact of external factors such as exercise, or alcohol and the influence of hormones are the main causes. Nocturnal hypoglycemia has several negative somatic, psychological, and social effects for people with diabetes, which are summarized in this article. With the advent of continuous glucose monitoring (CGM), it has been shown that the number of nocturnal hypoglycemic events was significantly underestimated when traditional blood glucose monitoring was used. The CGM can reduce the number of nocturnal hypoglycemia episodes with the help of alarms, trend arrows, and evaluation routines. In combination with CGM with an insulin pump and an algorithm, automatic glucose adjustment (AID) systems have their particular strength in nocturnal glucose regulation and the prevention of nocturnal hypoglycemia. Nevertheless, the problem of nocturnal hypoglycemia has not yet been solved completely with the technologies currently available. The CGM systems that use predictive models to warn of hypoglycemia, improved AID systems that recognize hypoglycemia patterns even better, and the increasing integration of artificial intelligence methods are promising approaches in the future to significantly minimize the risk of a side effect of insulin therapy that is burdensome for people with diabetes.

Unlocking Potential: Personalized Lifestyle Therapy for Type 2 Diabetes Through a Predictive Algorithm-Driven Digital Therapeutic.

BACKGROUND: We present a digital therapeutic (DTx) using continuous glucose monitoring (CGM) and an advanced artificial intelligence (AI) algorithm to digitally personalize lifestyle interventions for people with type 2 diabetes (T2D). METHOD: A study of 118 participants with non-insulin-treated T2D (HbA1c ≥ 6.5%) who were already receiving standard care and had a mean baseline (BL) HbA1c of 7.46% (0.93) used the DTx for three months to evaluate clinical endpoints, such as HbA1c, body weight, quality of life and app usage, for a pre-post comparison. The study also included an assessment of initial long-term data from a second use of the DTx. RESULTS: After three months of using the DTx, there was an improvement of 0.67% HbA1c in the complete cohort and -1.08% HbA1c in patients with poorly controlled diabetes (BL-HbA1c ≥ 7.0%) compared with standard of care (P < .001). The number of patients within the therapeutic target range (< 7.0%) increased from 38% to 60%, and 33% were on the way to remission (< 6.5%). Patients who used the DTx a second time experienced a reduction of -0.76% in their HbA1c levels and a mean weight loss of -6.84 kg after six months (P < .001) compared with BL. CONCLUSIONS: These results indicate that the DTx has clinically relevant effects on glycemic control and weight reduction for patients with both well and poorly controlled diabetes, whether through single or repeated usage. It is a noteworthy improvement in T2D management, offering a non-pharmacological, fully digital solution that integrates biofeedback through CGM and an advanced AI algorithm.

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

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

Quality assessment of glucose measurement with regard to epidemiology and clinical management of diabetes mellitus in Germany.

Background: During the last decade, Germany has seen an increased prevalence and a redistribution from undetected to diagnosed diabetes mellitus. Due to this substantial epidemiological development, the number of people with documented type 2 diabetes was 8.7 million in 2022. An estimated two million undiagnosed subjects are to be added. Beyond that, the life expectancy of diabetic subjects is increasing due to more responsive health systems in terms of care. Possible reasons include improved screening of at-risk individuals, the introduction of HbA1c for diagnosis in 2010, and the higher use of risk scores. Additionally, quality aspects of the laboratory methodology should be taken into consideration. Methods: Epidemiology and clinical management of diabetes in Germany are presented in the light of publications retrieved by a selective search of the PubMed database. Additionally, the data from German external quality assessment (EQA) surveys for the measurands glucose in plasma and HbA1c in whole blood, reviewed from 2010 until 2022, were evaluated. Above this, data concerning the analytical performance of near-patient glucometer devices, according to the ISO norm 15197:2013, were analyzed. Results: Two laboratory aspects are in good accordance with the observation of an increase in the diabetes mellitus prevalence when retrospectively reviewing the period 2010 to 2022: First, the analytical performance according to the ISO norm 15197:2013 of the glucometer devices widely used by patients with diabetes for the glucose self-testing, has improved during this period. Secondly, concerning the EQA program of INSTAND, the number of participating laboratories raised significantly in Germany. The spreads of variations of the specified results for plasma glucose remained unchanged between 2010 and 2022, whereas for HbA1c a significant decrease of the result scattering could be observed. Conclusion: These retrospectively established findings testify to an excellent analytical quality of laboratory diagnostics for glucose and HbA1c throughout Germany which may be involved in a better diagnosis and therapy of previously undetected diabetes mellitus.

Benefits of Usability Evaluation in the Development Process of Diabetes Technologies Using the Example of a Continuous Glucose Monitoring System Prototype.

BACKGROUND: Usability engineering analyzes the interaction between the intended users and a device. Its implementation is mandatory for manufacturers to obtain regulatory approval for the European market. The aim of this evaluation was assessing the role of usability testing in the development process. For this purpose, a continuous glucose monitoring (CGM) device under development was investigated to determine whether it could be used safely and effectively by the intended users. METHODS: Conduct of the usability testing was based on the international standard IEC 62366-1. Medical device use of CGM-experienced and non-experienced users (n = 15 each) was observed without initial training in use scenarios containing 18 tasks. The success rate of task completion was determined and the System Usability Scale (SUS) score was calculated from a questionnaire. A prototype of the FiberSense CGM System (EyeSense GmbH, Großostheim, Germany), comprising of a single-use sensor and a reusable detector, was investigated. RESULTS: Most use errors made by both user groups were related to ease of handling of the reusable detectors. The SUS scores achieved in this study were below the pre-defined SUS score acceptance criterion of ≥68. The most frequently mentioned reason for use errors was an incomprehensible and non-chronological instructions for use (IFU). CONCLUSIONS: The evaluation provides valuable insights on how to improve usability of the prototype device and demonstrates the value of conducting structured usability testing prior to product finalization. The results reflected areas for improvement of the user interface, mainly by restructuring the IFU, provision of an additional leaflet, and device training prior to use.

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.

Investigation of the Effect of 70 Potential Interferents on Measurement Results of Two Blood Glucose Monitoring Systems.

BACKGROUND: Reliable blood glucose (BG) measurements are important for people with diabetes to manage their therapy as well as in point-of-care testing (POCT) performed by health care professionals to monitor BG of patients or even to diagnose diabetes. Among other factors, endogenous and exogenous substances present in blood samples can impact the measurement results. To ensure and prove that blood glucose monitoring systems (BGMSs) are robust in terms of potential interferents, manufacturers have to perform extensive evaluations. METHOD: An interference screening test was performed for three reagent system lots of a POCT system and of a BGMS for self-monitoring of BG. A paired-difference approach based on ISO 15197:2013 and CLSI guideline EP07 was used with venous whole blood samples at two different glucose concentrations. Seventy potential interferents expected to be common in people with diabetes were evaluated. RESULTS: The interference effects were determined as normalized biases between test samples and corresponding control samples. For 69 of the 70 investigated potential interferents, both systems met the predefined acceptance criteria, with the normalized biases falling within ±10 mg/dL or ±10% at glucose concentrations ≤100 mg/dL or >100 mg/dL, respectively, for each of the three evaluated reagent system lots. CONCLUSIONS: The BGMS investigated in this study were found to be robust with respect to the 70 evaluated potential interferents. Interference effects were observed only for N-Acetyl-L-cysteine. Extensive evaluations of potential interfering factors can make an important contribution to ensure reliability of BGMS.

Plasma Glucose Concentrations in Different Sampling Tubes Measured on Different Glucose Analysers.

INTRODUCTION: The German Diabetes Association recommends using sampling tubes with citrate and fluoride additives to diagnose diabetes by oral glucose tolerance test to inhibit glycolysis. The effect of different tubes on measurement results was assessed. MATERIALS AND METHODS: In a first study, an oral glucose tolerance test was performed on 41 participants without anamnestically known diabetes. Venous blood was sampled in two different tubes with citrate/fluoride additives from different manufacturers and one with only lithium-heparin additive. A second study with 42 participants was performed to verify the initial results with an adapted design, in which a third tube with citrate buffer was used, and glucose measurements were performed on two additional devices of another analyser model. Samples were centrifuged either immediately (<5 min incubation time) or after 20 min or 4 h. All glucose measurements were performed in plasma. Glucose concentrations in lithium-heparin tubes with<5 min incubation time served as baseline concentrations. RESULTS: In the first study, glucose concentrations in one of the citrate/fluoride tubes were similar to the baseline. In the other citrate/fluoride tube, markedly lower concentrations (approximately - 5 mg/dL (- 0.28 mmol/L)) were measured. This was reproduced in the verification study for the same analyser, but not with the other analyser model. Lithium-heparin tubes centrifuged after 20 and 240 min showed systematically lower glucose concentrations. CONCLUSIONS: The results confirm that glycolysis can be effectively inhibited in citrate/fluoride-containing sampling tubes. However, glucose measurement results of one analyser showed a relevant negative bias in tubes containing liquid citrate buffer.

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.

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.