Rate-of-Change Dependence of the Performance of Two CGM Systems During Induced Glucose Swings

Continuous glucose monitoring and intrapersonal variability in fasting glucose

Plasma fasting glucose (FG) levels play a pivotal role in the diagnosis of prediabetes and diabetes worldwide. Here we investigated FG values using continuous glucose monitoring (CGM) devices in nondiabetic adults aged 40-70 years. FG was measured during 59,565 morning windows of 8,315 individuals (7.16 ± 3.17 days per participant). Mean FG was 96.2 ± 12.87 mg dl-1, rising by 0.234 mg dl-1 per year with age. Intraperson, day-to-day variability expressed as FG standard deviation was 7.52 ± 4.31 mg dl-1. As there are currently no CGM-based criteria for diabetes diagnosis, we analyzed the potential implications of this variability on the classification of glycemic status based on current plasma FG-based diagnostic guidelines. Among 5,328 individuals who would have been considered to have normal FG based on the first FG measurement, 40% and 3% would have been reclassified as having glucose in the prediabetes and diabetes ranges, respectively, based on sequential measurements throughout the study. Finally, we revealed associations between mean FG and various clinical measures. Our findings suggest that careful consideration is necessary when interpreting FG as substantial intraperson variability exists and highlight the potential impact of using CGM data to refine glycemic status assessment.

Leveraging continuous glucose monitoring for personalized modeling of insulin-regulated glucose metabolism

Continuous glucose monitoring (CGM) is a promising, minimally invasive alternative to plasma glucose measurements for calibrating physiology-based mathematical models of insulin-regulated glucose metabolism, reducing the reliance on in-clinic measurements. However, the use of CGM glucose, particularly in combination with insulin measurements, to develop personalized models of glucose regulation remains unexplored. Here, we simultaneously measured interstitial glucose concentrations using CGM as well as plasma glucose and insulin concentrations during an oral glucose tolerance test (OGTT) in individuals with overweight or obesity to calibrate personalized models of glucose-insulin dynamics. We compared the use of interstitial glucose with plasma glucose in model calibration, and evaluated the effects on model fit, identifiability, and model parameters' association with clinically relevant metabolic indicators. Models calibrated on both plasma and interstitial glucose resulted in good model fit, and the parameter estimates associated with metabolic indicators such as insulin sensitivity measures in both cases. Moreover, practical identifiability of model parameters was improved in models estimated on CGM glucose compared to plasma glucose. Together these results suggest that CGM glucose may be considered as a minimally invasive alternative to plasma glucose measurements in model calibration to quantify the dynamics of glucose regulation.

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.

Accuracy of a Real-Time Continuous Glucose Monitor in Pediatric Diabetic Ketoacidosis Admissions

Objective: Continuous glucose monitoring (CGM) devices are integral in the outpatient care of people with type 1 diabetes, although they lack inpatient labeling. Food and Drug Administration began allowing inpatient use during the coronavirus disease 2019 (COVID-19) pandemic, with some accuracy data now available, primarily from adult hospitals. Pediatric inpatient data remain limited, particularly during diabetic ketoacidosis (DKA) admissions and for patients receiving intravenous (IV) insulin. Design and Methods: This retrospective chart review compared point-of-care glucose values to personal Dexcom G6 sensor data during pediatric hospitalizations. Accuracy was assessed using mean absolute relative difference (MARD), Clarke Error Grids, and the percentage of values within 15/20/30% if glucose value >100 mg/dL and 15/20/30 mg/dL if glucose value ≤100 mg/dL. Results: Matched paired glucose values (N = 612) from 36 patients (median age 14 years, 58.3% non-Hispanic White, 47.2% male) and 42 inpatient encounters were included in this subanalysis of DKA admissions. The MARDs for DKA and non-DKA admissions (N = 503) were 11.8% and 11.7%, with 97.6% and 98.6% of pairs falling within A and B zones of the Clarke Error Grid, respectively. Severe DKA admissions (pH <7.15 and/or bicarbonate <5 mmol/L) had a MARD of 8.9% compared to 14.3% for nonsevere DKA admissions. The MARD during administration of IV insulin (N = 266) was 13.4%. Conclusions: CGM accuracy is similar between DKA and non-DKA admissions and is maintained in severe DKA and during IV insulin administration, suggesting potential usability in pediatric hospitalizations. Further study on the feasibility of implementation of CGM in the hospital is needed.

Enhancement of Ambulatory Glucose Profile for Decision Assistance and Treatment Adjustments

The ambulatory glucose profile (AGP) lacks sufficient statistical metrics and insightful graphs; indeed, it is missing important information on the temporal patterns of glucose variations. The AGP graph is difficult to interpret due to the overlapping metrics and fluctuations in glucose levels over 14 days. The objective of this proposed work is to overcome these challenges, specifically the lack of insightful information and difficulty in interpreting AGP graphs, to create a platform for decision assistance. The present work proposes 20 findings built from decision rules that were developed from a combination of AGP metrics and additional statistical metrics, which have the potential to identify patterns and insightful information on hyperglycemia and hypoglycemia. The "CGM Trace" webpage was developed, in which insightful metrics and graphical representations can be used to make inferences regarding the glucose data of any user. However, doctors (endocrinologists) can access the "Findings" tab for a summarized presentation of their patients' glycemic control. The findings were implemented for 67 patients' data, in which the data of 15 patients were collected from a clinical study and the data of 52 patients were gathered from a public dataset. The findings were validated by means of MANOVA (multivariate analysis of variance), wherein a p value of < 0.05 was obtained, depicting a strong significant correlation between the findings and the metrics. The proposed work from "CGM Trace" offers a deeper understanding of the CGM data, enhancing AGP reports for doctors to make treatment adjustments based on insightful information and hidden patterns for better diabetic management.

A probabilistic computation framework to estimate the dawn phenomenon in type 2 diabetes using continuous glucose monitoring

In type 2 diabetes (T2D), the dawn phenomenon is an overnight glucose rise recognized to contribute to overall glycemia and is a potential target for therapeutic intervention. Existing CGM-based approaches do not account for sensor error, which can mask the true extent of the dawn phenomenon. To address this challenge, we developed a probabilistic framework that incorporates sensor error to assign a probability to the occurrence of dawn phenomenon. In contrast, the current approaches label glucose fluctuations as dawn phenomena as a binary yes/no. We compared the proposed probabilistic model with a standard binary model on CGM data from 173 participants (71% female, 87% Hispanic/Latino, 54 ± 12 years, with either a diagnosis of T2D for six months or with an elevated risk of T2D) stratified by HbA1c levels into normal but at risk for T2D, with pre-T2D, or with non-insulin-treated T2D. The probabilistic model revealed a higher dawn phenomenon frequency in T2D [49% (95% CI 37-63%)] compared to pre-T2D [36% (95% CI 31-48%), p = 0.01] and at-risk participants [34% (95% CI 27-39%), p < 0.0001]. While these trends were also found using the binary approach, the probabilistic model identified significantly greater dawn phenomenon frequency than the traditional binary model across all three HbA1c sub-groups (p < 0.0001), indicating its potential to detect the dawn phenomenon earlier across diabetes risk categories.

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.

Relationship Between Symptom Perception and Postprandial Glycemic Profiles in Patients With Postbariatric Hypoglycemia After Roux-en-Y Gastric Bypass Surgery

OBJECTIVE

Post-bariatric surgery hypoglycemia (PBH) is a metabolic complication of Roux-en-Y gastric bypass (RYGB). Since symptoms are a key component of the Whipple's triad to diagnose nondiabetic hypoglycemia, we evaluated the relationship between self-reported symptoms and postprandial sensor glucose profiles.

RESEARCH DESIGN AND METHODS

Thirty patients with PBH after RYGB (age: 50.1 [41.6-60.6] years, 86.7% female, BMI: 26.5 [23.5-31.2] kg/m2; median [interquartile range]) wore a blinded Dexcom G6 sensor while recording autonomic, neuroglycopenic, and gastrointestinal symptoms over 50 days. Symptoms (overall and each type) were categorized into those occurring in postprandial periods (PPPs) without hypoglycemia, or in the preceding dynamic or hypoglycemic phase of PPPs with hypoglycemia (nadir sensor glucose <3.9 mmol/L). We further explored the relationship between symptoms and the maximum negative rate of sensor glucose change and nadir sensor glucose levels.

RESULTS

In 5,851 PPPs, 775 symptoms were reported, of which 30.6 (0.0-59.9)% were perceived in PPPs without hypoglycemia, 16.7 (0.0-30.1)% in the preceding dynamic phase and 45.0 (13.7-84.7)% in the hypoglycemic phase of PPPs with hypoglycemia. Per symptom type, 53.6 (23.8-100.0)% of the autonomic, 30.0 (5.6-80.0)% of the neuroglycopenic, and 10.4 (0.0-50.0)% of the gastrointestinal symptoms occurred in the hypoglycemic phase of PPPs with hypoglycemia. Both faster glucose dynamics and lower nadir sensor glucose levels were related with symptom perception.

CONCLUSIONS

The relationship between symptom perception and PBH is complex, challenging clinical judgement and decision-making in this population.

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.

Perceptions of Continuous Glucose Monitoring Systems in the T1D Exchange Diabetes Registry: Satisfaction, Concerns, and Areas for Future Improvement

Manufacturers continue to improve performance and usability of continuous glucose monitoring (CGM) systems. As CGM becomes a standard of care, especially for people on insulin therapy, it is important to routinely gauge how satisfied people with diabetes are with this technology. This article describes survey feedback from a large cohort of people with diabetes using older and current CGM systems and highlights areas of current satisfaction, concern, and future system improvement.

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.

Discordance between postprandial plasma glucose measurement and continuous glucose monitoring

BACKGROUND

There has been growing interest in studying postprandial glucose responses using continuous glucose monitoring (CGM) in nondiabetic individuals. Accurate measurement of glucose responses to meals can facilitate applications such as precision nutrition and early detection of diabetes.

OBJECTIVES

We aimed to quantify the discordance between simultaneous postprandial glucose measurements made using plasma and CGM.

METHODS

We studied 10 nondiabetic older adults who randomly consumed 9 predefined meals of varying macronutrient compositions. Glucose was measured for 8 h after the meal by the CGM, blood samples for plasma collection were taken regularly, and plasma glucose was quantified using gold-standard laboratory measurement and a fingerstick blood glucose meter. The primary outcome measured was the mean absolute relative difference (MARD) of CGM and fingerstick measurements relative to the gold standard. Secondary outcomes were Bland-Altman statistics, Clarke Error Grid, and time in range metrics. Additional subgroup analyses were performed by stratifying the postprandial glucose measurements based on the macronutrient composition of the meals.

RESULTS

When compared against the gold-standard postprandial glucose measurements, the fingerstick meter was more accurate (MARD: 8.0%; 95% CI: 7.6%, 8.6%) than the CGM (MARD: 13.7%; 95% CI: 13.1%, 14.3%; P < 0.0001). After the meals, Bland-Altman analysis demonstrated that the CGM underestimated the 8-h gold-standard glucose rise by 12.8 mg/dL on average (P < 0.0001), whereas the fingerstick meter did so by 5.5 mg/dL on average (P < 0.0001). The CGM underestimated the time spent in the 70-180 mg/dL range (P = 0.002) and overestimated the time spent <70 mg/dL (P < 0.0001) compared with the other 2 methods.

CONCLUSIONS

We discovered discordance between gold standard, fingerstick, and CGM in measuring plasma glucose concentrations after a meal. Consequently, emerging applications of CGM in healthy individuals, such as precision nutrition and diabetes onset prediction, may need to account for these discordances.This trial was registered at clinicaltrials.gov as NCT04928872.

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

AIMS

A user-calibrated real-time continuous glucose monitoring (rt-CGM) system is compared to a factory-calibrated flash glucose monitoring (FGM) system and assessed in terms of accuracy and acceptability in patients with type 1 diabetes (T1D).

METHODS

Ten participants with T1D were enroled from a specialist diabetes centre in Singapore and provided with the Guardian Connect with Enlite Sensor (Medtronic, Northridge, CA, USA) and first-generation Freestyle Libre System (Abbott Diabetes Care, Witney, UK), worn simultaneously. Participants had to check capillary blood glucose four times per day. At the end of week 1 and week 2, participants returned for data download and were given a user evaluation survey.

RESULTS

Accuracy evaluation between Guardian Connect and Freestyle Libre includes the overall mean absolute relative difference value (9.7 ± 11.0% vs. 17.5 ± 10.9%), Clarke Error Grid zones A + B (98.6% vs. 98.1%), sensitivity (78.9% vs. 63.4%), and specificity (93.4% vs. 81.0%). Notably, time below range (<3.9 mmol/L) was 10.5% for FGM versus 2% for rt-CGM. From the evaluation survey, 90% of participants perceived rt-CGM to be accurate versus 40% for FGM, although the majority found both devices to be easy to use, educational, and useful in improving glycaemic control. However, due to the cost of sensors, only 30% were keen to use either device for continuous monitoring.

CONCLUSIONS

Although rt-CGM was superior to FGM in terms of accuracy, the value of glucose trends in both devices is still useful in diabetes self-management. Patients and clinicians may consider either technology depending on their requirements.

Accuracy and Safety of Dexcom G7 Continuous Glucose Monitoring in Adults with Diabetes

Background: We evaluated the accuracy and safety of a seventh generation (G7) Dexcom continuous glucose monitor (CGM) during 10.5 days of use in adults with diabetes. Methods: Adults with either type 1 or type 2 diabetes (on intensive insulin therapy or not) participated at 12 investigational sites in the United States. In-clinic visits were conducted on days 1 or 2, 4 or 7, and on the second half of day 10 or the first half of day 11 for frequent comparisons with comparator blood glucose measurements obtained with the YSI 2300 Stat Plus glucose analyzer. Participants wore sensors concurrently on the upper arm and abdomen. Accuracy evaluation included the proportion of CGM values within 15% of comparator glucose levels >100 mg/dL or within 15 mg/dL of comparator levels ≤100 mg/dL (%15/15), along with the %20/20 and %30/30 agreement rates. The mean absolute relative difference (MARD) between temporally matched CGM and comparator values was also calculated. Results: Data from 316 participants (619 sensors, 77,774 matched pairs) were analyzed. For arm- and abdomen-placed sensors, overall MARDs were 8.2% and 9.1%, respectively. Overall %15/15, %20/20, and %30/30 agreement rates were 89.6%, 95.3%, and 98.8% for arm-placed sensors and were 85.5%, 93.2%, and 98.1% for abdomen-placed sensors. Across days of wear, glucose concentration ranges, and rates of change, %20/20 agreement rates varied by no more than 9% from the overall %20/20. No serious adverse events were reported. Conclusions: The G7 CGM provides accurate glucose readings with single-digit MARD with arm or abdomen placement in adults with diabetes. Clinicaltrials.gov: NCT04794478.

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.

Accuracy of Real Time Continuous Glucose Monitoring during Different Liquid Solution Challenges in Healthy Adults: A Randomized Controlled Cross-Over Trial

Continuous glucose monitoring (CGM) represents an integral of modern diabetes management, however, there is still a lack of sensor performance data when rapidly consuming different liquids and thus changing total body water. 18 healthy adults (ten females, age: 23.1 ± 1.8 years, BMI 22.2 ± 2.1 kg·m−2) performed four trial visits consisting of oral ingestion (12 mL per kg body mass) of either a 0.9% sodium chloride, 5% glucose or Ringer’s solution and a control visit, in which no liquid was administered (control). Sensor glucose levels (Dexcom G6, Dexcom Inc., San Diego, CA, USA) were obtained at rest and in 10-min intervals for a period of 120 min after solution consumption and compared against reference capillary blood glucose measurements. The overall MedARD [IQR] was 7.1% [3.3−10.8]; during control 5.9% [2.7−10.8], sodium chloride 5.0% [2.7−10.2], 5% glucose 11.0% [5.3−21.6] and Ringer’s 7.5% [3.1−13.2] (p < 0.0001). The overall bias [95% LoA] was 4.3 mg·dL−1 [−19 to 28]; during control 3.9 mg·dL−1 [−11 to 18], sodium chloride 4.8 mg·dL−1 [−9 to 19], 5% glucose 3.6 mg·dL−1 [−33 to 41] and Ringer’s solution 4.9 mg·dL−1 [−13 to 23]. The Dexcom G6 CGM system detects glucose with very good accuracy during liquid solution challenges in normoglycemic individuals, however, our data suggest that in people without diabetes, sensor performance is influenced by different solutions.

Digital Solutions to Diagnose and Manage Postbariatric Hypoglycemia

Postbariatric hypoglycemia (PBH) is an increasingly recognized late metabolic complication of bariatric surgery, characterized by low blood glucose levels 1–3 h after a meal, particularly if the meal contains rapid-acting carbohydrates. PBH can often be effectively managed through appropriate nutritional measures, which remain the cornerstone treatment today. However, their implementation in daily life continues to challenge both patients and health care providers. Emerging digital technologies may allow for more informed and improved decision-making through better access to relevant data to manage glucose levels in PBH. Examples include applications for automated food analysis from meal images, digital receipts of purchased food items or integrated platforms allowing the connection of continuously measured glucose with food and other health-related data. The resulting multi-dimensional data can be processed with artificial intelligence systems to develop prediction algorithms and decision support systems with the aim of improving glucose control, safety, and quality of life of PBH patients. Digital innovations, however, face trade-offs between user burden vs. amount and quality of data. Further challenges to their development are regulatory non-compliance regarding data ownership of the platforms acquiring the required data, as well as user privacy concerns and compliance with regulatory requirements. Through navigating these trade-offs, digital solutions could significantly contribute to improving the management of PBH.

Performance of intermittently scanned continuous glucose monitoring systems in people with type 1 diabetes: A pooled analysis

AIMS

To conduct a pooled analysis to assess the performance of intermittently scanned continuous glucose monitoring (isCGM) in association with the rate of change in sensor glucose in a cohort of children, adolescents, and adults with type 1 diabetes.

MATERIAL AND METHODS

In this pooled analysis, isCGM system accuracy was assessed depending on the rate of change in sensor glucose. Clinical studies that have been investigating isCGM accuracy against blood glucose, accompanied with collection time points were included in this analysis. isCGM performance was assessed by means of median absolute relative difference (MedARD), Parkes error grid (PEG) and Bland-Altman plot analyses.

RESULTS

Twelve studies comprising 311 participants were included, with a total of 15 837 paired measurements. The overall MedARD (interquartile range) was 12.7% (5.9-23.5) and MedARD differed significantly based on the rate of change in glucose (P < 0.001). An absolute difference of -22 mg/dL (-1.2 mmol/L) (95% limits of agreement [LoA] 60 mg/dL (3.3 mmol/L), -103 mg/dL (-5.7 mmol/L)) was found when glucose was rapidly increasing (isCGM glucose minus reference blood glucose), while a -32 mg/dL (1.8 mmol/L) (95% LoA 116 mg/dL (6.4 mmol/L), -51 mg/dL (-2.8 mmol/L)) absolute difference was observed in periods of rapidly decreasing glucose.

CONCLUSIONS

The performance of isCGM was good when compared to reference blood glucose measurements. The rate of change in glucose for both increasing and decreasing glucose levels diminished isCGM performance, showing lower accuracy during high rates of glucose change.

Validity of continuous glucose monitoring for categorizing glycemic responses to diet: implications for use in personalized nutrition

BACKGROUND

Continuous glucose monitor (CGM) devices enable characterization of individuals' glycemic variation. However, there are concerns about their reliability for categorizing glycemic responses to foods that would limit their potential application in personalized nutrition recommendations.

OBJECTIVES

We aimed to evaluate the concordance of 2 simultaneously worn CGM devices in measuring postprandial glycemic responses.

METHODS

Within ZOE PREDICT (Personalised Responses to Dietary Composition Trial) 1, 394 participants wore 2 CGM devices simultaneously [n = 360 participants with 2 Abbott Freestyle Libre Pro (FSL) devices; n = 34 participants with both FSL and Dexcom G6] for ≤14 d while consuming standardized (n = 4457) and ad libitum (n = 5738) meals. We examined the CV and correlation of the incremental area under the glucose curve at 2 h (glucoseiAUC0-2 h). Within-subject meal ranking was assessed using Kendall τ rank correlation. Concordance between paired devices in time in range according to the American Diabetes Association cutoffs (TIRADA) and glucose variability (glucose CV) was also investigated.

RESULTS

The CV of glucoseiAUC0-2 h for standardized meals was 3.7% (IQR: 1.7%-7.1%) for intrabrand device and 12.5% (IQR: 5.1%-24.8%) for interbrand device comparisons. Similar estimates were observed for ad libitum meals, with intrabrand and interbrand device CVs of glucoseiAUC0-2 h of 4.1% (IQR: 1.8%-7.1%) and 16.6% (IQR: 5.5%-30.7%), respectively. Kendall τ rank correlation showed glucoseiAUC0-2h-derived meal rankings were agreeable between paired CGM devices (intrabrand: 0.9; IQR: 0.8-0.9; interbrand: 0.7; IQR: 0.5-0.8). Paired CGMs also showed strong concordance for TIRADA with a intrabrand device CV of 4.8% (IQR: 1.9%-9.8%) and an interbrand device CV of 3.2% (IQR: 1.1%-6.2%).

CONCLUSIONS

Our data demonstrate strong concordance of CGM devices in monitoring glycemic responses and suggest their potential use in personalized nutrition.This trial was registered at clinicaltrials.gov as NCT03479866.

Glucose Concentrations from Continuous Glucose Monitoring Devices Compared to Those from Blood Plasma during an Oral Glucose Tolerance Test in Healthy Young Adults

Continuous glucose monitoring devices measure glucose in interstitial fluid. The devices are effective when used by patients with type 1 and 2 diabetes but are increasingly being used by researchers who are interested in the effects of various behaviours of glucose concentrations in healthy participants. Despite their more frequent application in this setting, the devices have not yet been validated for use under such conditions. A total of 124 healthy participants were recruited to a ten-day laboratory study. Each participant underwent four oral glucose tolerance tests, and a total of 3315 out of a possible 4960 paired samples were included in the final analysis. Bland-Altman plots and mean absolute relative differences were used to determine the agreement between the two methods. Bland-Altman analyses revealed that the continuous glucose monitoring devices had proportional bias (R = 0.028, p < 0.001) and a mean bias of -0.048 mmol/L, and device measurements were more variable as glucose concentrations increased. Ninety-nine per cent of paired values were in Zones A and B of the Parkes Error Grid plot, and there was an overall mean absolute relative difference of 16.2% (±15.8%). There was variability in the continuous glucose monitoring devices, and this variability was higher when glucose concentrations were higher. If researchers were to use continuous glucose monitoring devices to measure glucose concentrations during an oral glucose tolerance test in healthy participants, this variability would need to be considered.

Personalized Approach for the Management of Exercise-Related Glycemic Imbalances in Type 1 Diabetes: Comparison with Reference Method

BACKGROUND

One of the most frequently adopted strategies to counterbalance the risk of exercise-induced hypoglycemia in patients with type 1 diabetes is carbohydrates supplement. Nevertheless, the estimation of its amount is still challenging. We investigated the efficacy of the personalized Exercise Carbohydrate Requirement Estimation System (ECRES) method compared to a tabular approach to estimate the glucose supplement needed for the prevention of exercise-related glycemic imbalances.

METHOD

Twenty-six patients performed two one-hour constant intensity exercises one week apart; the amount of extra carbohydrates was estimated, in random order, by the personalized ECRES method or through the tabular approach; glycemia was determined every 30 minutes. Continuous glucose monitoring (CGM) metrics were calculated over the 48 hours preceding, and the afternoon and night following the trials.

RESULTS

Applying the personalized ECRES method, a significantly lower amount of carbohydrates was administered to the active patients compared to the tabular approach, median (interquartile range): 9.0 (0.5-21.0) g vs 23.0 (21.0-25.0) g; P < .01; the two methods were similar for the sedentary patients, 18 (13.5-36.0) g vs 23.0 (21.0-27.0) g; P = NS. After overlapping CGM metrics before the exercises, both methods avoided hypoglycemia and resulted in similar glucose levels throughout them. The ECRES method led to CGM metrics within the guidelines for either the afternoon and the night just following the trials, whereas the tabular approach resulted in a significantly greater time below range in the afternoon (11.8% ± 18.2%; P < .05) and time above range during the night (39.3% ± 29.8%; P < .05).

CONCLUSIONS

The results support the validity of the personalized ECRES method: although the estimated amounts of carbohydrates were lower, patients' glycemia was maintained within safe clinical limits.

Continuous glucose monitoring in patients with type 2 diabetes on hemodialysis

Diabetic kidney disease is the leading cause of end-stage kidney disease in high-income countries. The strict control of glycemic oscillations is the principal therapeutic target, but this could be hard to achieve in uremic patients due to their unpredictable insulin sensitivity. Currently, the evaluation of the glycemic profile relies on serum markers (glycated hemoglobin HbA1c, glycated albumin, and fructosamine), capillary glucose blood control (self-monitoring of blood glucose), and interstitial glucose control (continue glucose monitoring). We conducted a systematic review of published articles on continue glucose monitoring in hemodialysis patients with type 2 diabetes, which included 12 major articles. Four studies found significant fluctuations in glucose levels during hemodialysis sessions. All studies reported a higher mean amplitude of glucose variations on the hemodialysis day. Three studies agreed that continue glucose monitoring is better than glycated hemoglobin in detecting these abnormalities. Moreover, continue glucose monitoring was more accurate and perceived as easier to use by patients and their caregivers. In patients with type 2 diabetes on hemodialysis, glucose levels show different variation patterns than the patients on hemodialysis without diabetes. Considering manageability, accuracy, and cost-effectiveness, continue glucose monitoring could be the ideal diagnostic tool for the patient with diabetes on hemodialysis.

Technological innovation of Continuous Glucose Monitoring (CGM) as a tool for commercial aviation pilots with insulin-treated diabetes and stakeholders/regulators: A new chance to improve the directives?

Civil aviation pilots who develop insulin-treated diabetes and want to renew a Commercial Pilot License (CPL) represent a medical, social and regulatory problem. This depends on justified concerns about hypoglycemia, the most threatening event for people who carry out jobs requiring a high level of concentration and reliability. This negatively affects social and working aspects of pilots' lives, who have a high profile and a high-cost professional qualification. It could be possible now to revise this attitude thanks to the availability of Continuous Glucose Monitoring (CGM) devices. CGM clearly showed to prevent hypoglycemic events in insulin-treated diabetic patients by allowing strict monitoring and trend prediction of glucose levels. By systematizing available data on such devices and present regulations in CPL issuance worldwide, our review can be used as handy tool for a fruitful discussion among the scientific community, national and international civil aviation regulators, stakeholders and pilots, aimed at evaluating the evidence-based opportunity to revise CPL issuance criteria for insulin-treated diabetic pilots. For the above-mentioned reasons, there are, among the regulatory administrations of Civil Aviation around the globe, several different approaches and limitations set for the subjects with insulin-treated diabetes who want to obtain, or renew, a CPL.

Disordered eating in women with type 1 diabetes: Continuous glucose monitoring reveals the complex interactions of glycaemia, self-care behaviour and emotion

OBJECTIVES

Glycaemia in people with type 1 diabetes and disordered eating is not well characterised. We explored the glycaemia, self-care behaviour and emotional state of women with type 1 diabetes and disordered eating.

RESEARCH DESIGN AND METHODS

In all, 13 women with and 10 without disordered eating and type 1 diabetes participated in this case-control study. We used a mixed-methods approach with a 7-day blinded continuous glucose monitoring and real-time record of non-prompted capillary glucose (CG), emotion, activity and physical symptoms on a diabetes diary using a smartphone application (mySugr®). We compared groups using Mann-Whitney U test or Fisher's exact test. We conducted thematic analyses of free-text diary entries (NVivo®) and quantitative analysis of emotion/symptom tags.

RESULTS

People with type 1 diabetes and disordered eating spent longer time above range in level 2 hyperglycaemia (>13.9 mmol/L, Median [interquartile range]: 21% [16,60] vs 5% [2,17], p = 0.015). They had lower time in range and similar time below range compared to those without disordered eating. The standard deviation of CG was significantly higher in the disordered eating group (4.7 mmol/L [4.5, 6.1] vs 3 [2.8, 3.2], p = 0.018). The median of the percentage of rising sensor glucose trends was three times higher in the disordered eating group. They also had higher negative emotional and physical symptoms associated with high blood glucose (>15 mmol/L).

CONCLUSIONS

Disordered eating has a significant impact on the glycaemia and emotion of a person with type 1 diabetes.

Performance of the Intermittently Scanned Continuous Glucose Monitoring (isCGM) System during a High Oral Glucose Challenge in Adults with Type 1 Diabetes-A Prospective Secondary Outcome Analysis

To assess intermittently scanned continuous glucose monitoring (isCGM) performance for different rates of change in plasma glucose (RCPG) during glycemic challenges in type 1 diabetes (T1D). Nineteen people with T1D (7 females; age 35 ± 11 years; HbA_1c 7.3 ± 0.6% (56 ± 7 mmol/mol)) performing two glycemic challenges (OGTT) were included. During OGTTs, plasma glucose was compared against sensor glucose for timepoints 0 min (pre-OGTT), +15 min, +30 min, +60 min, +120 min, +180 min, and +240 min by means of median absolute (relative) difference (MARD and MAD) and Clarke Error Grid (CEG), then was stratified for RCPG and glycemic ranges. Overall, MARD was 8.3% (4.0–14.8) during hypoglycemia level 1 18.8% (15.8–22.0), euglycemia 9.5% (4.3–15.1), hyperglycemia level 1 9.4% (4.0–17.2), and hyperglycemia level 2 7.1% (3.3–11.9). The MARD was associated with the RCPG (p < 0.0001), detailing significant differences in comparison of low, moderate, high, and very high RCPG (p = 0.014). Overall, CEG resulted in 88% (212 values) of comparison points in zone A, 12% (29 values) in zone B, and 0.4% (1 value) in zone D. The isCGM system was accurate during OGTTs. Its performance was dependent on the RCPG and showed an overestimation of the actual reference glucose during hypoglycemia.

Simple Post-Processing of Continuous Glucose Monitoring Measurements Improves Endpoints in Clinical Trials

BACKGROUND

Continuous glucose monitoring (CGM) is a powerful tool to be considered both in clinical practice and clinical trials. However, CGM has been criticized for being inaccurate for many reasons including a physiological delay. This study sought to investigate the current delay issue and propose a simple post-processing procedure.

METHOD

More than a million hours of the Dexcom G4 CGM from 472 subjects investigated in a state-of-the-art clinical trial were analyzed by time shifting the CGM measurements and comparing them to plasma glucose (PG) measurements. The resultant CGM measurements were then assessed in relation to real-world clinical research endpoints.

RESULTS

A CGM time shift of -9 minutes was optimal and reduced mean absolute relative difference (MARD) statistically significantly with 1.0% point. The MARD reduction resulted in better clinical research endpoints of hypoglycemia and postprandial glucose increments.

CONCLUSIONS

The delay in CGM is still an issue. The delay in this study was identified to be 9 minutes compared to PG. With a simple post-processing approach of time shifting the CGM measurements with -9 minutes, it was possible to obtain a statistically significantly lower MARD and subsequently obtain clinical research endpoints of improved validity.

Comparison of oral glucose tolerance test and ambulatory glycaemic profiles in pregnant women in Uganda with gestational diabetes using the FreeStyle Libre flash glucose monitoring system

BACKGROUND

The diagnosis of hyperglycaemia in sub-Saharan Africa (SSA) is challenging. Blood glucose levels obtained during oral glucose tolerance test (OGTT) may not reflect home glycaemic profiles. We compare OGTT results with home glycaemic profiles obtained using the FreeStyle Libre continuous glucose monitoring device (FSL-CGM).

METHODS

Twenty-eight women (20 with gestational diabetes [GDM], 8 controls) were recruited following OGTT between 24 and 28 weeks of gestation. All women wore the FSL-CGM device for 48-96 h at home in early third trimester, and recorded a meal diary. OGTT was repeated on the final day of FSL-CGM recording. OGTT results were compared with ambulatory glycaemic variables, and repeat OGTT was undertaken whilst wearing FSL-CGM to determine accuracy of the device.

RESULTS

FSL-CGM results were available for 27/28 women with mean data capture 92.8%. There were significant differences in the ambulatory fasting, post-prandial peaks, and mean glucose between controls in whom both primary and secondary OGTT was normal (n = 6) and those with two abnormal OGTTs or "true" GDM (n = 7). There was no difference in ambulatory mean glucose between these controls and the 13 women who had an abnormal primary OGTT and normal repeat OGTT. These participants had significantly lower body mass index (BMI) than the true GDM group (29.0 Vs 36.3 kg/m2, p-value 0.014). Paired OGTT/FSL-CGM readings revealed a Mean Absolute difference (MAD) -0.58 mmol/L and Mean Absolute Relative Difference (MARD) -11.9%. Bland-Altman plot suggests FSL-CGM underestimated blood glucose by approximately 0.78 mmol/L.

CONCLUSION

Diagnosis of GDM on a single OGTT identifies a proportion of women who do not have a significantly higher home glucose levels than controls. This raises questions about factors which may affect the reproducibility of OGTT in this population, including food insecurity and atypical phenotypes of diabetes. More investigation is needed to understand the suitability of the OGTT as a diagnostic test in sub-Saharan Africa.

Blood Glucose Estimation From Voice: First Review of Successes and Challenges

The possibility to estimate glucose value from voice would make a breakthrough in diabetes treatment: namely, remove the delay in the nonintrusive instantaneous blood glucose estimation, relieve medical budgets and significantly improve wellbeing of diabetics. In this review, different approaches have been described and systematized, in order to provide an objective snapshot of the state of the art. Since nonintrusive glucose estimation is notoriously difficult, we included a Transparence and Reproducibility Score aimed at revealing the biases in the primary research articles. The review is completed with the discussion on future research pathways.

Accuracy of the Dexcom G6 Glucose Sensor during Aerobic, Resistance, and Interval Exercise in Adults with Type 1 Diabetes

The accuracy of continuous glucose monitoring (CGM) sensors may be significantly impacted by exercise. We evaluated the impact of three different types of exercise on the accuracy of the Dexcom G6 sensor. Twenty-four adults with type 1 diabetes on multiple daily injections wore a G6 sensor. Participants were randomized to aerobic, resistance, or high intensity interval training (HIIT) exercise. Each participant completed two in-clinic 30-min exercise sessions. The sensors were applied on average 5.3 days prior to the in-clinic visits (range 0.6–9.9). Capillary blood glucose (CBG) measurements with a Contour Next meter were performed before and after exercise as well as every 10 min during exercise. No CGM calibrations were performed. The median absolute relative difference (MARD) and median relative difference (MRD) of the CGM as compared with the reference CBG did not differ significantly from the start of exercise to the end exercise across all exercise types (ranges for aerobic MARD: 8.9 to 13.9% and MRD: −6.4 to 0.5%, resistance MARD: 7.7 to 14.5% and MRD: −8.3 to −2.9%, HIIT MARD: 12.1 to 16.8% and MRD: −14.3 to −9.1%). The accuracy of the no-calibration Dexcom G6 CGM was not significantly impacted by aerobic, resistance, or HIIT exercise.

Improved glycaemic variability and basal insulin dose reduction during a running competition in recreationally active adults with type 1 diabetes-A single-centre, prospective, controlled observational study

INTRODUCTION

To investigate the glycaemic response, macronutrient intake and insulin management in people with type 1 diabetes (T1D) compared to healthy individuals around a running competition.

MATERIAL AND METHODS

This was a single-centre, prospective, controlled observational study performed in individuals with T1D and healthy people. 24 people (12 T1D) were included in this study (age: T1D 41±12 vs. healthy 38±6 years, females: 3 vs. 6, BMI: 25.53.0 vs. 22.9±2.8 kg/m2). Both groups received an intermittently scanned continuous glucose monitoring (isCGM; FreeStyle Libre 1, Abbott, USA) system to assess glycaemia 24 hours before, during and 24 hours after a running competition. During this period, participants recorded their food intake and insulin administration. Data were analysed via ANOVA and mixed model analyses with post-hoc testing (p≤0.05).

RESULTS

For overall glycaemic ranges in comparison of groups, significant differences were found for time in range (T1D 63±21% vs. healthy 89±13%, p = 0.001), time above range (TAR) 1 (T1D 21±15% vs. healthy 0±0%, p<0.001) and TAR 2 (T1D 8 [0-16%] vs. healthy 0±0%, p<0.001). When glycaemic variability was assessed, people with T1D had a higher glycaemic variability compared to healthy individuals (p<0.0001). Basal insulin dose was significantly reduced when compared against the regular pre-study basal insulin dose (pre-study 22±6 vs. pre-competition day 11±9 (-50±41%), p = 0.02; competition day 15±5 (-32± 1%)).

CONCLUSION

People with T1D have impaired glucose responses around a running competition compared to healthy individuals. However, basal insulin dose reductions were sufficient to prevent further dysglycaemia.

CLINICAL TRIAL ID

drks.de; DRKS00019886.

A Prospective, Randomized Trial Testing Different Regimens of Carbohydrate Administration to Prevent Major Reduction in Plasma Glucose Follwing a Standardized Bout of Moderate Physical Activity in Patients with Type 1 Diabetes

AIM/HYPOTHESIS

It was the aim to prospectively study regimes of "preventive" carbohydrate administration to avoid major reduction in plasma glucose during physical activity.

METHODS

24 patients with type 1 diabetes (age 41±12 years; 11 women, 13 men; BMI 26.5±4.7 kg/m²; HbA_1c 9.1±1.5%; insulin dose 0.64±0.22 IU/kg body weight and day) participated in one experiment without physical activity and in three experiments with a 4 km, 60 min hike starting at 2 p.m.. No "preventive" carbohydrates, 2×10 g or 2×20 g carbohydrates (muesli bars) were taken when starting and after 30 min (randomized order). Plasma glucose was determined.

RESULTS

Within 30 min after starting physical activity, plasma glucose fell by approximately 70 mg/dl, making additional carbohydrate intake necessary in 70% of the subjects. This drop was not prevented by any regimens of "preventive" carbohydrate intake. After the nadir, plasma glucose rose faster after the 2×20 g carbohydrate regime (the largest amount tested; p=0.0036). With "preventive" administration of carbohydrates, significantly (p<0.05) less additional "therapeutic" carbohydrates needed to be administered in 6 h following the initiation of the hike.

CONCLUSIONS/INTERPRETATION

In conclusion, in the setting of 2 h postprandial exercise in type 1 diabetes, preventive carbohydrate supplementation alone will not completely eliminate the risk of brisk falls in plasma glucose concentrations or hypoglycaemic episodes. Else, higher amounts or repeated administration of carbohydrates may be necessary.

Assessment of factors that determine the mean absolute relative difference in flash glucose monitoring with reference to plasma glucose levels in Japanese subjects without diabetes

The Abbott FreeStyle Libre flash glucose monitoring system (FGM) is a recently introduced, but widespread continuous glucose monitoring system. While its mean absolute relative difference (MARD) value indicating its accuracy is acceptable with reference to the self-monitoring of blood glucose (SMBG) levels, few reports have examined the MARD in sensor glucose values of FGM (FGM-SG) with reference to plasma glucose (PG) levels and the factors determining it. We performed oral glucose tolerance tests (OGTTs) in 25 Japanese subjects without diabetes. Parkes error grid analyses showed that FGM-SG with either SMBG or PG levels as a reference met International Organization for Standardization criteria. The MARD in FGM-SG with reference to SMBG levels was 10.9 ± 4.1% during OGTTs. Surprisingly, the MARD in FGM-SG with reference to PG levels was 20.3 ± 10.3% during OGTTs, revealing a discrepancy in the accuracy of FGM-SG compared with that of PG levels; moreover, the MARD showed negative correlations with fasting blood sugar level, homeostasis model assessment insulin resistance index, and body mass index (BMI). Multiple regression analyses revealed that BMI contributed the most to the MARD when FGM-SG and PG level were compared, as lean individuals have a greater MARD regardless of glucose levels. Inaccurate FGM data could potentially increase the risk of inappropriate treatment; consideration of such factors is critical to ensure reliable FGM values.

Continuous Glucose Monitoring in Bariatric Patients Undergoing Laparoscopic Sleeve Gastrectomy and Laparoscopic Roux-En-Y Gastric Bypass

BACKGROUND

Few investigations have been conducted that compared blood glucose in patients with diabetes mellitus (DM2) and morbid obesity who had undergone laparoscopic sleeve gastrectomy (LSG) or gastric bypass (LRYGB). We aimed to compare the effects of these procedures using continuous glucose monitoring (CGM).

METHODS

We prospectively studied patients that had qualified for LSG or LRYGB. The inclusion criteria were DM2 of ≤ 5 years, for which patients were taking oral anti-diabetic drugs, or no glucose metabolism disorder; and morbid obesity. CGM was performed between admission and the 10th postoperative day.

RESULTS

We studied 16 patients with DM2 and 16 without. Eighteen patients underwent LSG and 14 underwent LRYGB. The median hemoglobin A1c was 5.5% (5.4-5.9%) in DM2 patients, which did not differ from control (p = 0.460). Preoperative mean daily glucose concentration was similar between DM2 and control patients (p = 0.622). For patients with DM2, LRYGB was associated with more frequent low glucose status, and these episodes lasted longer than in DM2 patients that underwent LSG (p = 0.035 and 0.049, respectively). DM2 patients that underwent LRYGB demonstrated lower glucose concentrations from third postoperative day than those that underwent LSG. Patients without DM2 did not demonstrate differences in daily mean glucose concentrations, or in incidence nor duration of hypoglycemia throughout the observation period.

CONCLUSION

A significantly larger reduction in interstitial glucose concentration is present from third day in patients with DM2 who undergo LRYGB vs. LSG, accompanied by a lower incidence and shorter duration of low glucose episodes.

Perioperative Considerations for Evolving Artificial Pancreas Devices

Type 1 diabetes mellitus is a lifelong condition. It requires intensive patient involvement including frequent glucose measurements and subcutaneous insulin dosing to provide optimal glycemic control to decrease short- and long-term complications of diabetes mellitus without causing hypoglycemia. Variations in insulin pharmacokinetics and responsiveness over time in addition to illness, stress, and a myriad of other factors make ideal glucose control a challenge. Control-to-range and control-to-target artificial pancreas devices (closed-loop artificial pancreas devices [C-APDs]) consist of a continuous glucose monitor, response algorithm, and insulin delivery device that work together to automate much of the glycemic management for an individual while continually adjusting insulin dosing toward a glycemic target. In this way, a C-APD can improve glycemic control and decrease the rate of hypoglycemia. The MiniMed 670G (Medtronic, Fridley, MN) system is currently the only Food and Drug Administration-cleared C-APD in the United States. In this system, insulin delivery is continually adjusted to a glucose concentration, and the patient inputs meal-time information to modify insulin delivery as needed. Data thus far suggest improved glycemic control and decreased hypoglycemic events using the system, with decreased need for patient self-management. Thus, the anticipated use of these devices is likely to increase dramatically over time. There are limited case reports of safe intraoperative use of C-APDs, but the Food and Drug Administration has not cleared any device for such use. Nonetheless, C-APDs may offer an opportunity to improve patient safety and outcomes through enhanced intraoperative glycemic control. Anesthesiologists should become familiar with C-APD technology to help develop safe and effective protocols for their intraoperative use. We provide an overview of C-APDs and propose an introductory strategy for intraoperative study of these devices.

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

High-quality performance of medical devices for glucose monitoring is important for a safe and efficient usage of this diagnostic option by patients with diabetes. The mean absolute relative difference (MARD) parameter is used most often to characterize the measurement performance of systems for continuous glucose monitoring (CGM). Calculation of this parameter is relatively easy and comparison of the MARD numbers between different CGM systems appears to be straightforward on the first glance. However, a closer look reveals that a number of complex aspects make interpretation of the MARD numbers provided by the manufacturer for their CGM systems difficult. In this review, these aspects are discussed and considerations are made for a systematic and appropriate evaluation of the MARD in clinical trials. The MARD should not be used as the sole parameter to characterize CGM systems, especially when it comes to nonadjunctive usage of such systems.

The Accuracy and Precision of the Continuously Stored Data from Flash Glucose Monitoring System in Type 2 Diabetes Patients during Standard Meal Tolerance Test

BACKGROUND

The purpose of this study was to investigate the accuracy of the continuously stored data from the Abbott FreeStyle Libre flash glucose monitoring (FGM) system in Chinese diabetes patients during standard meal tests when glucose concentrations were rapidly changing. Subjects and Methods. Interstitial glucose levels were monitored for 14 days in 26 insulin-treated patients with type 2 diabetes using the FGM system. Standard meal tests were conducted to induce large glucose swings. Venous blood glucose (VBG) was tested at 0, 30, 60, and 120 min after standard meal tests in one middle day of the first and second weeks, respectively. The corresponding sensor glucose values were obtained from interpolating continuously stored data points. Assessment of accuracy was according to recent consensus recommendations with median absolute relative difference (MARD) and Clarke and Parkes error grid analysis (CEG and PEG).

RESULTS

Among 208 paired sensor-reference values, 100% were falling within zones A and B of the Clarke and Parkes error grid analysis. The overall MARD was 10.7% (SD, 7.8%). Weighted least squares regression analysis resulted in high agreement between the FGM sensor glucose and VBG readings. The overall MTT results showed that FGM was lower than actual VBG, with MAD of 22.1 mg/dL (1.2 mmol/L). At VBG rates of change of -1 to 0, 0 to 1, 1 to 2, and 2 to 3 mg/dl/min, MARD results were 11.4% (SD, 8.7%), 9.4% (SD, 6.5%), 9.9% (SD, 7.5%), and 9.5% (SD, 7.7%). At rapidly changing VBG concentrations (>3 mg/dl/min), MARD increased to 19.0%, which was significantly higher than slow changing BG groups.

CONCLUSIONS

Continuously stored interstitial glucose measurements with the FGM system were found to be acceptable to evaluate VBG in terms of clinical decision during standard meal tests. The continuously stored data from the FGM system appeared to underestimate venous glucose and performed less well during rapid glucose changes.

Performance of the Freestyle Libre flash glucose monitoring (flash GM) system in individuals with type 1 diabetes: A secondary outcome analysis of a randomized crossover trial

AIMS

The efficacy of flash glucose monitoring (flash GM) systems has been demonstrated by improvements in glycaemia; however, during high rates of glucose flux, the performance of continuous glucose monitoring systems was impaired, as detailed in previous studies. This study aimed to determine the performance of the flash GM system during daily-life glycaemic challenges such as carbohydrate-rich meals, bolus insulin-induced glycaemic disturbances and acute physical exercise in individuals with type 1 diabetes.

MATERIALS AND METHODS

This study comprised four randomized trial visits with alternating pre- and post-exercise bolus insulin doses. Throughout the four 14-hour inpatient phases, 19 participants received three carbohydrate-rich meals and performed moderate-intensity exercise. Venous blood glucose and capillary blood glucose during exercise was compared to interstitial glucose concentrations. Flash GM accuracy was assessed by median absolute relative difference (MARD) (interquartile range [IQR]) using the Bland-Altman method and Clark error grid, as well as according to guidelines for integrated CGM approvals (Class II-510(K)).

RESULTS

The overall MARD (IQR) during inpatient phases was 14.3% (6.9%-22.8%), during hypoglycaemia (≤3.9 mmol/L) was 31.6% (16.2%-46.8%), during euglycaemia (4.0 mmol/L - 9.9 mmol/L) was 16.0% (8.5%-24.0%) and during hyperglycaemia (≥10 mmol/L) was 9.4% (5.1%-15.7%). Overall Bland-Altman analysis showed a bias (95% LoA) of 1.26 mmol/L (-1.67 to 4.19 mmol/L). The overall MARD during acute exercise was 29.8% (17.5%-39.8%), during hypoglycaemia was 45.1% (35.2%-51.1%), during euglycaemia was 30.7% (18.7%-39.2%) and during hyperglycaemia was 16.3% (10.0%-22.8%).

CONCLUSION

Flash GM interstitial glucose readings were not sufficiently accurate within the hypoglycaemic range and during acute exercise and require confirmatory blood glucose measurements.

The use of real time continuous glucose monitoring or flash glucose monitoring in the management of diabetes: A consensus view of Italian diabetes experts using the Delphi method

Until recently, in Italy, the use of continuous glucose monitoring (CGM) systems has been limited, but is now rapidly increasing, including the so-called real-time CGM (rtCGM) and the intermittently viewed CGM (iCGM), also called Flash Glucose Monitoring (FGM). These technologies overcome many of the limitations of self-monitoring of blood glucose (SMBG) by fingerprick and allow to go beyond HbA1c to check glucose control in diabetes. However, standardized protocols for applying and interpreting rtCGM and FGM data are lacking. In this paper, we delineate a consensus amongst Italian diabetes physicians on the attributes of rtCGM and FGM technologies, and introduce a consistent approach for their use by Italian healthcare professionals. Most experts consider rtCGM and FGM as two separate categories of interstitial subcutaneous fluid (ISF) sensing technologies, and see them as superior to SMBG. Furthermore, there is strong consensus that rtCGM and FGM reduce hypoglycemia risk, increase the amount of time in the target glucose range and augment treatment satisfaction. However, there is still no agreement on the indication of the FGM for subjects who suffer asymptomatic hypoglycemia. Consensus on the role of education in initiating and optimizing use of rtCGM/FGM and about the interpretation of glucose trends was near unanimous, whereas no consensus was reached on the statement that there are no disadvantages/risks of rtCGM/FGM. Some issues remain in rtCGM/FGM management: a) risk of excessive correction of high or low glucose; b) risk of alert fatigue leading to alert silencing or rtCGM termination; c) allergic reaction to the adhesive keeping rtCGM or FGM sensors in place. The panel almost unanimously agreed that sensor accuracy depends on multiple variables, that alarm setting should be individualized, and that global glycemic profile represent an useful tool in interpreting glucose data. More clinical studies and a wider use of these devices will increase the efficacy and effectiveness of continuous glucose monitoring in Italy.

Measures of Accuracy for Continuous Glucose Monitoring and Blood Glucose Monitoring Devices

Currently, patients with diabetes may choose between two major types of system for glucose measurement: blood glucose monitoring (BGM) systems measuring glucose within capillary blood and continuous glucose monitoring (CGM) systems measuring glucose within interstitial fluid. Although BGM and CGM systems offer different functionality, both types of system are intended to help users achieve improved glucose control. Another area in which BGM and CGM systems differ is measurement accuracy. In the literature, BGM system accuracy is assessed mainly according to ISO 15197:2013 accuracy requirements, whereas CGM accuracy has hitherto mainly been assessed by MARD, although often results from additional analyses such as bias analysis or error grid analysis are provided. The intention of this review is to provide a comparison of different approaches used to determine the accuracy of BGM and CGM systems and factors that should be considered when using these different measures of accuracy to make comparisons between the analytical performance (ie, accuracy) of BGM and CGM systems. In addition, real-world implications of accuracy and its relevance are discussed.

Prediction Quality of Glucose Trend Indicators in Two Continuous Tissue Glucose Monitoring Systems

BACKGROUND

Continuous interstitial glucose monitoring (CGM) systems often provide glucose trend indicators (e.g., arrows) in addition to current glucose values. These indicators are recommended to be used in therapeutic decisions, because they are ascribed predictive qualities by CGM system manufacturers and expert committees. This study assessed how reliably trend indicators match future glucose change, because such information is missing.

METHODS

In a clinical trial, two different CGM systems were used by 20 participants, with two sensors of each system per patient. Participants used the systems for 14 days with three study site visits (48 h each). During study site visits, glucose trend indicators, as displayed by the CGM systems, were recorded at least once per hour during daytime and once at night in a diary. In addition, CGM data were downloaded from the devices. Trend indicators were compared with glucose change calculated from CGM data >30 min after recording the trend indicator.

RESULTS

Approximately 60% of trend indicators matched the glucose change calculated from CGM data. More than 10% of trend indicators differed by at least two trend indicator categories. Focusing on trend indicators recorded around carbohydrate (CHO) intake and insulin deliveries resulted in approximately half of trend indicators matching the calculated glucose change.

CONCLUSIONS

Trend indicators do not always match future glucose change, especially within the first few hours after CHO intake and insulin deliveries. Manufacturers' labeling and recommendations should reflect this, so that CGM users can make informed decisions.

Technology in the management of type 1 diabetes mellitus - current status and future prospects

Type 1 diabetes mellitus (T1DM) represents 5-10% of diabetes cases worldwide. The incidence of T1DM is increasing, and there is no immediate prospect of a cure. As such, lifelong management is required, the burden of which is being eased by novel treatment modalities, particularly from the field of diabetes technologies. Continuous glucose monitoring has become the standard of care and includes factory-calibrated subcutaneous glucose monitoring and long-term implantable glucose sensing. In addition, considerable progress has been made in technology-enabled glucose-responsive insulin delivery. The first hybrid insulin-only closed-loop system has been commercialized, and other closed-loop systems are under development, including dual-hormone glucose control systems. This Review focuses on well-established diabetes technologies, including glucose sensing, pen-based insulin delivery, data management and data analytics. We also cover insulin pump therapy, threshold-based suspend, predictive low-glucose suspend and single-hormone and dual-hormone closed-loop systems. Clinical practice recommendations for insulin pump therapy and continuous glucose monitoring are presented, and ongoing research and future prospects are highlighted. We conclude that the management of T1DM is improved by diabetes technology for the benefit of the majority of people with T1DM, their caregivers and guardians and health-care professionals treating patients with T1DM.

Limits to the Evaluation of the Accuracy of Continuous Glucose Monitoring Systems by Clinical Trials

Systems for continuous glucose monitoring (CGM) are evolving quickly, and the data obtained are expected to become the basis for clinical decisions for many patients with diabetes in the near future. However, this requires that their analytical accuracy is sufficient. This accuracy is usually determined with clinical studies by comparing the data obtained by the given CGM system with blood glucose (BG) point measurements made with a so-called reference method. The latter is assumed to indicate the correct value of the target quantity. Unfortunately, due to the nature of the clinical trials and the approach used, such a comparison is subject to several effects which may lead to misleading results. While some reasons for the differences between the values obtained with CGM and BG point measurements are relatively well-known (e.g., measurement in different body compartments), others related to the clinical study protocols are less visible, but also quite important. In this review, we present a general picture of the topic as well as tools which allow to correct or at least to estimate the uncertainty of measures of CGM system performance.

Accuracy of flash glucose monitoring and continuous glucose monitoring technologies: Implications for clinical practice

Continuous glucose monitoring and flash glucose monitoring technologies measure glucose in the interstitial fluid and are increasingly used in diabetes care. Their accuracy, key to effective glycaemic management, is usually measured using the mean absolute relative difference of the interstitial fluid sensor compared to reference blood glucose readings. However, mean absolute relative difference is not standardised and has limitations. This review aims to provide a consensus opinion on assessing accuracy of interstitial fluid glucose sensing technologies. Mean absolute relative difference is influenced by glucose distribution and rate of change; hence, we express caution on the reliability of comparing mean absolute relative difference data from different study systems and conditions. We also review the pitfalls associated with mean absolute relative difference at different glucose levels and explore additional ways of assessing accuracy of interstitial fluid devices. Importantly, much data indicate that current practice of assessing accuracy of different systems based on individualised mean absolute relative difference results has limitations, which have potential clinical implications. Healthcare professionals must understand the factors that influence mean absolute relative difference as a metric for accuracy and look at additional assessments, such as consensus error grid analysis, when evaluating continuous glucose monitoring and flash glucose monitoring systems in diabetes care. This in turn will ensure that management decisions based on interstitial fluid sensor data are both effective and safe.

Practical implementation, education and interpretation guidelines for continuous glucose monitoring: A French position statement

The use by diabetes patients of real-time continuous interstitial glucose monitoring (CGM) or the FreeStyle Libre^® (FSL) flash glucose monitoring (FGM) system is becoming widespread and has changed diabetic practice. The working group bringing together a number of French experts has proposed the present practical consensus. Training of professionals and patient education are crucial for the success of CGM. Also, institutional recommendations must pay particular attention to the indications for and reimbursement of CGM devices in populations at risk of hypoglycaemia. The rules of good practice for CGM are the precursors of those that need to be enacted, given the oncoming emergence of artificial pancreas devices. It is necessary to have software combining user-friendliness, multiplatform usage and average glucose profile (AGP) presentation, while integrating glucose and insulin data as well as events. Expression of CGM data must strive for standardization that facilitates patient phenotyping and their follow-up, while integrating indicators of variability. The introduction of CGM involves a transformation of treatment support, rendering it longer and more complex as it also includes specific educational and technical dimensions. This complexity must be taken into account in discussions of organization of diabetes care.

Venous, Arterialized-Venous, or Capillary Glucose Reference Measurements for the Accuracy Assessment of a Continuous Glucose Monitoring System

BACKGROUND

Different reference methods are used for the accuracy assessment of continuous glucose monitoring (CGM) systems. The effect of using venous, arterialized-venous, or capillary reference measurements on CGM accuracy is unclear.

METHODS

We evaluated 21 individuals with type 1 diabetes using a capillary calibrated CGM system. Venous or arterialized-venous reference glucose samples were taken every 15 min at two separate visits and assessed per YSI 2300 STAT Plus. Arterialization was achieved by heated-hand technique. Capillary samples were collected hourly during the venous reference visit. The investigation sequence (venous or arterialized-venous) was randomized. Effectiveness of arterialization was measured by comparing free venous oxygen pressure (PO2) of both visit days. Primary endpoint was the median absolute relative difference (ARD).

RESULTS

Median ARD using arterialized-venous reference samples was not different from venous samples (point estimated difference 0.52%, P = 0.181). When comparing the three reference methods, median ARD was also not different over the full glycemic range (venous 9.0% [n = 681], arterialized-venous 8.3% [n = 684], and capillary 8.1% [n = 205], P = 0.216), nor over the separate glucose ranges. Arterialization was successful (PO2 venous 5.4 kPa vs. arterialized-venous 8.9 kPa, P < 0.001). Arterialized-venous glucose was significantly higher than venous glucose and numerically higher than capillary glucose (arterialized-venous 142 mg/dL vs. venous 129 mg/dL [P < 0.001] and vs. capillary 134 mg/dL [P = 0.231]). Inconvenience related to arterialization included transient mild edema and redness of the hand in 4 out of 21 (19%) patients.

CONCLUSIONS

The use of venous, arterialized-venous, or capillary reference measurements did not significantly impact CGM accuracy. Venous reference seems preferable due to its ease of operation.

Extensive Assessment of Blood Glucose Monitoring During Postprandial Period and Its Impact on Closed-Loop Performance

BACKGROUND

Closed-loop (CL) systems aims to outperform usual treatments in blood glucose control and continuous glucose monitors (CGM) are a key component in such systems. Meals represents one of the main disturbances in blood glucose control, and postprandial period (PP) is a challenging situation for both CL system and CGM accuracy.

METHODS

We performed an extensive analysis of sensor's performance by numerical accuracy and precision during PP, as well as its influence in blood glucose control under CL therapy.

RESULTS

During PP the mean absolute relative difference (MARD) for both sensors presented lower accuracy in the hypoglycemic range (19.4 ± 12.8%) than in other ranges (12.2 ± 8.6% in euglycemic range and 9.3 ± 9.3% in hyperglycemic range). The overall MARD was 12.1 ± 8.2%. We have also observed lower MARD for rates of change between 0 and 2 mg/dl. In CL therapy, the 10 trials with the best sensor spent less time in hypoglycemia (PG < 70 mg/dl) than the 10 trials with the worst sensors (2 ± 7 minutes vs 32 ± 38 minutes, respectively).

CONCLUSIONS

In terms of accuracy, our results resemble to previously reported. Furthermore, our results showed that sensors with the lowest MARD spent less time in hypoglycemic range, indicating that the performance of CL algorithm to control PP was related to sensor accuracy.