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

Accuracy of an Off-Label Transmitter and Data Manager Paired With an Intermittent Scanned Continuous Glucose Monitor in Adults With Type 1 Diabetes

BACKGROUND

This work evaluates the accuracy and agreement between the FreeStyle Libre sensor (FSL) and an off-label converted real-time continuous glucose monitor (c-rtCGM) device consisting of the MiaoMiao transmitter and the xDrip+ application which can be coupled to the FSL.

METHODS

Four weeks of glucose data were collected from 21 participants with type 1 diabetes using the c-rtCGM and FSL: two weeks with a single initial calibration (uncalibrated) and two weeks with a daily calibration (calibrated). Accuracy and agreement evaluation included mean absolute relative difference (MARD), the %20/20 rule, Bland-Altman plots, and the Consensus Error Grid analysis.

RESULTS

Values reported by the c-rtCGM system compared with the FSL resulted in an overall MARD of 12.06% and 84.71% of the results falling within Consensus Error Grid Zone A when the device is calibrated. For uncalibrated devices, an overall MARD of 17.49% was obtained. Decreased accuracy was shown in the hypoglycemic range and for rates of change greater than 2 mg/dL/min. The between-device bias also incremented with increasing glucose values.

CONCLUSION

Measurements recorded by the c-rtCGM were found to be accurate when compared with FSL data only when performing daily c-rtCGM device calibrations. High drops in accuracy and agreement between devices occurred when the c-rtCGM was not calibrated.

Flash glucose monitoring system in gestational diabetes: a study of accuracy and usability

PURPOSE

Studies of flash glucose monitoring systems (FGMSs) in pregnancy are insufficient, especially in gestational diabetes (GD). Our aim was to evaluate Freestyle Libre's usability and accuracy (compared to self-monitoring of blood glucose [SMBG]) for GD patients in real-life conditions.

METHODS

This is a prospective study with pregnant women diagnosed with GD (n = 24 for the usability analysis; n = 19 for the accuracy analysis). The study duration was up to 28 days (lifetime of two sensors). Participants executed a minimum of four daily FGMS readings obtained immediately after capillary SMBG. Analytical accuracy was assessed with mean absolute relative difference (MARD) and mean absolute difference (MAD); clinical accuracy was assessed with Surveillance Error Grid (SEG). Usability was evaluated with a user acceptability questionnaire.

RESULTS

The mean pregestational BMI was 25.21 ± 5.15 kg/m2 (mean ± SD), the mean gestational age was 30.31 ± 2.02 weeks, and the mean glucose values were 76.63 ± 7.49 mg/dL. A total of 1339 SMBG-FGMS pairs of values were obtained. Analytical accuracy was good with an overall MARD of 14.07% and an in-target MARD of 13.79%. The number of SMBG-FMGS pairs for above-target values was low (122 of 1339) with an associated MARD of 17.95%. Clinical accuracy of the FGMS was demonstrated, with 94.4% of values in the no-risk or slight, lower risk zones of the SEG. FGMS accuracy was unaffected by pregestational BMI or gestational age. The user acceptability questionnaire showed high levels of satisfaction, with 95.8-100% preferring FGMS to SMBG. No unexpected or severe adverse effects occurred.

CONCLUSION

FGMS showed good performance in GD regarding accuracy and usability. Larger studies are needed to corroborate our results, verify the analytical accuracy of above-target values as this glucose range might lead to initiation or adjustment of pharmacological therapy, and ultimately establish definitive recommendations regarding prescription of FGMS for GD patients.

Saliva sampling strategies affecting the salivary glucose measurement

Characterized by sustained elevated blood glucose levels, diabetes mellitus has become one of the largest global public health concerns by imposing a heavy global burden on socio-economic development. To date, regular blood glucose level check by performing a finger-prick test has been a routine strategy to monitor diabetes. However, the intrusive nature of finger blood prick tests makes it challenging for individuals to maintain consistent testing routines. Recently, salivary glucose measurement (SGM) has increasingly become a non-invasive alternative to traditional blood glucose testing for diabetes. Despite that, further research is needed to standardize the collection methods and address the issues of variability to ensure accurate and reliable SGM. To resolve possible remaining issues in SGM, we here thoroughly explored saliva sampling strategies that could impact the measurement results. Additionally, the effects of supplements taken, mouth washing, gum chewing, and smoking were collectively analyzed, followed by a continuous SGM over a long period, forming the stepping stone for the practical transitional development of SGM in non-invasive diabetes monitoring.

Continuous Glucose Monitoring: A Possible Aid for Detecting Hypoglycemic Events during Insulin Tolerance Tests

The combined pituitary function test evaluates the anterior pituitary gland, while the insulin tolerance test evaluates growth hormone deficiencies. However, successful stimulation requires achieving an appropriate level of hypoglycemia. Close medical supervision for glucose monitoring is required during hypoglycemia induction and the test is often very tedious. In addition, a capillary blood sugar test (BST) and serum glucose levels may differ greatly. An alternative approach may be utilizing a continuous glucose-monitoring (CGM) system. We provide three cases in which CGM was successfully used alongside a standard BST and serum glucose levels during the combined pituitary function test to better detect and induce hypoglycemia. Three participants who were diagnosed with multiple pituitary hormone deficiencies during childhood were re-evaluated in adulthood; a Dexcom G6 CGM was used. The CGM sensor glucose and BST levels were simultaneously assessed for glycemic changes and when adequate hypoglycemia was reached during the combined pituitary function test. The CGM sensor glucose, BST, and serum glucose levels showed similar glucose trends in all three patients. A Bland-Altman analysis revealed that the CGM underestimated the BST values by approximately 9.68 mg/dL, and a Wilcoxon signed-rank test showed that the CGM and BST measurements significantly differed during the stimulation test (p = 0.003). Nevertheless, in all three cases, the CGM sensor mimicked the glycemic variability changes in the BST reading and assisted in monitoring appropriate hypoglycemia nadir. Thus, CGM can be used as a safe aid for clinicians to use during insulin tolerance tests where critical hypoglycemia is induced.

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

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

Non-severe hypoglycemia in type 1 diabetes: a randomized crossover trial comparing two quantities of oral carbohydrates at different insulin-induced hypoglycemia ranges

Aims

Non-severe hypoglycemia (NS-H) is challenging for people living with type 1 diabetes (PWT1D) and often results from relative iatrogenic hyper-insulinemia. Current guidelines recommend a one-size-fits-all approach of 15-20 g of simple carbohydrates (CHO) every 15 min regardless of the triggering conditions of the NS-H event. We aimed to test different amounts of CHO to treat insulin-induced NS-H at various glucose ranges.

Methods

This is a randomized, four-way, crossover study involving PWT1D, testing NS-H treatment outcomes with 16 g vs. 32 g CHO at two plasma glucose (PG) ranges: A: 3.0-3.5 mmol/L and B: <3.0 mmol/L. Across all study arms, participants consumed an additional 16 g of CHO if PG was still <3.0 mmol/L at 15 min and <4.0 mmol/L at 45 min post-initial treatment. Subcutaneous insulin was used in a fasting state to induce NS-H. Participants had frequent venous sampling of PG, insulin, and glucagon levels.

Results

Participants (n = 32; 56% female participants) had a mean (SD) age of 46.1 (17.1) years, had HbA1c at 54.0 (6.8 mmol/mol) [7.1% (0.9%)], and had a diabetes duration of 27.5 (17.0) years; 56% were insulin pump users. We compared NS-H correction parameters between 16 g and 32 g of CHO for range A, 3.0-3.5 mmol/L (n = 32), and range B, <3.0 mmol/L (n = 29). Change in PG at 15 min for A: 0.1 (0.8) mmol/L vs. 0.6 (0.9) mmol/L, p = 0.02; and for B: 0.8 (0.9) mmol/L vs. 0.8 (1.0) mmol/L, p = 1.0. Percentage of participants with corrected episodes at 15 min: (A) 19% vs. 47%, p = 0.09; (B) 21% vs. 24%, p = 1.0. A second treatment was necessary in (A) 50% vs. 15% of participants, p = 0.001; (B) 45% vs. 34% of participants, p = 0.37. No statistically significant differences in insulin and glucagon parameters were observed.

Conclusions

NS-H, in the context of hyper-insulinemia, is difficult to treat in PWT1D. Initial consumption of 32 g of CHO revealed some advantages at the 3.0-3.5 mmol/L range. This was not reproduced at lower PG ranges since participants needed additional CHO regardless of the amount of initial consumption.

Clinical trial registration

ClinicalTrials.gov, identifier NCT03489967.

Comparison of Accuracy of Freestyle Libre Pro and Medtronic iPro2 Continuous Glucose Monitoring Systems in Pregnancy

There are limited data on head-to-head performance of Freestyle Libre Pro (FSL-Pro) and blinded Medtronic iPro2 CGMS in pregnancy. In this prospective observational study, women with hyperglycemia in pregnancy (n=42) underwent simultaneous FSL-Pro and Medtronic iPro2 sensor insertion and SMBG using Contour Plus meter (reference). The overall MARD for iPro2 and FSL-Pro systems were 8.0 ± 9.2% and 19.0 ± 12.8%, respectively. At hypoglycemic range, both sensors performed less accurately (MARD: 18.1% and 16.8%, respectively), while iPro2 showed higher accuracy at euglycemic (8.2% and 19.3%, respectively) and hyperglycemic (6.8% and 18.0%, respectively) ranges. On Bland-Altman analysis, iPro2 and FSL-Pro underestimated glucose by 0.01 and 1.09 mmol/L, respectively. The ISO criteria were fulfilled for 83.4% and 36.2% of all values, respectively. To conclude, iPro2 was more accurate, however, both sensors demonstrated inaccuracy at hypoglycemic range, highlighting the need for refinements in the current generation of sensors to address this problem.

Research progress in the application of time in range: more than a percentage

ABSTRACT

Glucose monitoring is an important part of medical care in diabetes mellitus, which not only helps assess glycemic control and treatment safety, but also assists with treatment adjustment. With the development of continuous glucose monitoring (CGM), the use of CGM has increased rapidly. With the wealth of glucose data produced by CGM, new metrics are greatly needed to optimally evaluate glucose status and guide the treatment. One of the parameters that CGM provides, time in range (TIR), has been recognized as a key metric by the international consensus. Before the adoption of TIR in clinical practice, several issues including the minimum length of CGM use, the setting of the target range, and individualized TIR goals are summarized. Additionally, we discussed the mounting evidence supporting the association between TIR and diabetes-related outcomes. As a novel glucose metric, it is of interest to compare TIR with other conventional glucose markers such as glycated hemoglobin A1c. It is anticipated that the use of TIR may provide further information on the quality of glucose control and lead to improved diabetes management.

Non-invasive method for blood glucose monitoring using ECG signal

Introduction: Tight glucose monitoring is crucial for diabetic patients by using a Continuous Glucose Monitor (CGM). The existing CGMs measure the Blood Glucose Concentration (BGC) from the interstitial fluid. These technologies are quite expensive, and most of them are invasive. Previous studies have demonstrated that hypoglycemia and hyperglycemia episodes affect the electrophysiology of the heart. However, they did not determine a cohort relationship between BGC and ECG parameters.

Material and method: In this work, we propose a new method for determining the BGC using surface ECG signals. Recurrent Convolutional Neural Networks (RCNN) were applied to segment the ECG signals. Then, the extracted features were employed to determine the BGC using two mathematical equations. This method has been tested on 04 patients over multiple days from the D1namo dataset, using surface ECG signals instead of intracardiac signal.

Results: We were able to segment the ECG signals with an accuracy of 94% using the RCNN algorithm. According to the results, the proposed method was able to estimate the BGC with a Mean Absolute Error (MAE) of 0.0539, and a Mean Squared Error (MSE) of 0.1604. In addition, the linear relationship between BGC and ECG features has been confirmed in this paper.

Conclusion: In this paper, we propose the potential use of ECG features to determine the BGC. Additionally, we confirmed the linear relationship between BGC and ECG features. That fact will open new perspectives for further research, namely physiological models. Furthermore, the findings point to the possible application of ECG wearable devices for non-invasive continuous blood glucose monitoring via machine learning.

Evaluation of a Continuous Blood Glucose Monitor: A Novel and Non-Invasive Wearable Using Bioimpedance Technology

BACKGROUND

Frequent blood glucose level (BGL) monitoring is essential for effective diabetes management. Poor compliance is common due to the painful finger pricking or subcutaneous lancet implantation required from existing technologies. There are currently no commercially available non-invasive devices that can effectively measure BGL. In this real-world study, a prototype non-invasive continuous glucose monitoring system (NI-CGM) developed as a wearable ring was used to collect bioimpedance data. The aim was to develop a mathematical model that could use these bioimpedance data to estimate BGL in real time.

METHODS

The prototype NI-CGM was worn by 14 adult participants with type 2 diabetes for 14 days in an observational clinical study. Bioimpedance data were collected alongside paired BGL measurements taken with a Food and Drug Administration (FDA)-approved self-monitoring blood glucose (SMBG) meter and an FDA-approved CGM. The SMBG meter data were used to improve CGM accuracy, and CGM data to develop the mathematical model.

RESULTS

A gradient boosted model was developed using a randomized 80-20 training-test split of data. The estimated BGL from the model had a Mean Absolute Relative Difference (MARD) of 17.9%, with the Parkes error grid (PEG) analysis showing 99% of values in clinically acceptable zones A and B.

CONCLUSIONS

This study demonstrated the reliability of the prototype NI-CGM at collecting bioimpedance data in a real-world scenario. These data were used to train a model that could successfully estimate BGL with a promising MARD and clinically relevant PEG result. These results will enable continued development of the prototype NI-CGM as a wearable ring.

Artificial intelligence for non-invasive glycaemic-events detection via ECG in a paediatric population: study protocol

Purpose

Paediatric Type 1 Diabetes (T1D) patients are at greater risk for developing severe hypo and hyperglycaemic events due to poor glycaemic control. To reduce the risk of adverse events, patients need to achieve the best possible glycaemic management through frequent blood glucose monitoring with finger prick or Continuous Glucose Monitoring (CGM) systems. However, several non-invasive techniques have been proposed aiming at exploiting changes in physiological parameters based on glucose levels. The overall objective of this study is to validate an artificial intelligence (AI) based algorithm to detect glycaemic events using ECG signals collected through non-invasive device.

Methods

This study will enrol T1D paediatric participants who already use CGM. Participants will wear an additional non-invasive wearable device for recording physiological data and respiratory rate. Glycaemic measurements driven through ECG variables are the main outcomes. Data collected will be used to design, develop and validate the personalised and generalized classifiers based on a deep learning (DL) AI algorithm, able to automatically detect hypoglycaemic events by using few ECG heartbeats recorded with wearable devices.

Results

Data collection is expected to be completed approximately by June 2023. It is expected that sufficient data will be collected to develop and validate the AI algorithm.

Conclusion

This is a validation study that will perform additional tests on a larger diabetes sample population to validate the previous pilot results that were based on four healthy adults, providing evidence on the reliability of the AI algorithm in detecting glycaemic events in paediatric diabetic patients in free-living conditions.

Trial registration

ClinicalTrials.gov identifier: NCT03936634. Registered on 11 March 2022, retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT05278143?titles=AI+for+Glycemic+Events+Detection+Via+ECG+in+a+Pediatric+Population&draw=2&rank=1.

Supplementary information

The online version contains supplementary material available at 10.1007/s12553-022-00719-x.

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

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

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.

Fifteen-minute consultation: Practical use of continuous glucose monitoring

Type 1 diabetes is a self-managed condition. Regular monitoring of blood glucose (BG) levels has been the cornerstone of diabetes management. Finger prick BG testing traditionally has been the standard method employed. More recently, rapid advancements in the development of continuous glucose monitoring devices have led to increased use of technology to help children and young people with diabetes manage their condition. These devices have the potential to improve diabetes control and reduce hypoglycaemia especially if used in conjunction with a pump to automate insulin delivery. This paper aims to provide an update on main CGM devices available and practical considerations for doctors if they come across a child with diabetes who is using one of these devices.

Exercise and Self-Management in Adults with Type 1 Diabetes

PURPOSE OF REVIEW

The purpose of this review paper is to examine the most recent evidence of exercise-related self-management in adults with type 1 diabetes (T1D).

RECENT FINDINGS

This paper reviews the benefits and barriers to exercise, diabetes self-management education, the role of the healthcare provider in assessment and counseling, the use of technology, and concerns for special populations with T1D. Adults with T1D may not exercise at sufficient levels. Assessing current levels of exercise, counseling during a clinical visit, and the use of technology may improve exercise in this population.

Glycaemia dynamics in gestational diabetes mellitus

Pregnant women may develop gestational diabetes mellitus (GDM), a disease of pregnancy characterised by maternal and fetal hyperglycaemia with hazardous consequences to the mother, the fetus, and the newborn. Maternal hyperglycaemia in GDM results in fetoplacental endothelial dysfunction. GDM-harmful effects result from chronic and short periods of hyperglycaemia. Thus, it is determinant to keep glycaemia within physiological ranges avoiding short but repetitive periods of hyper or hypoglycaemia. The variation of glycaemia over time is defined as 'glycaemia dynamics'. The latter concept regards with a variety of mechanisms and environmental conditions leading to blood glucose handling. In this review we summarized the different metrics for glycaemia dynamics derived from quantitative, plane distribution, amplitude, score values, variability estimation, and time series analysis. The potential application of the derived metrics from self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM) in the potential alterations of pregnancy outcome in GDM are discussed.

Continuous Glucose Monitoring in the Management of Neonates With Persistent Hypoglycemia and Congenital Hyperinsulinism

BACKGROUND

Persistent hypoglycemia is common in the newborn and is associated with poor neurodevelopmental outcome. Adequate monitoring is critical in prevention, but is dependent on frequent, often hourly blood sampling. Continuous glucose monitoring (CGM) is increasingly being used in children with type 1 diabetes mellitus, but use in neonatology remains limited. We aimed to introduce real-time CGM to provide insights into patterns of dysglycemia and to support the management of persistent neonatal hypoglycemia.

METHODS

This is a single-center retrospective study of real-time CGM use over a 4-year period in babies with persistent hypoglycemia.

RESULTS

CGMs were inserted in 14 babies: 8 term and 6 preterm infants, 9 with evidence of congenital hyperinsulinism (CHI). A total of 224 days of data was collected demonstrating marked fluctuations in glucose levels in babies with CHI, with a higher sensor glucose SD (1.52 ± 0.79 mmol/L vs 0.77 ± 0.22 mmol/L) in infants with CHI compared with preterm infants. A total of 1254 paired glucose values (CGM and blood) were compared and gave a mean absolute relative difference of 11%.

CONCLUSION

CGM highlighted the challenges of preventing hypoglycemia in these babies when using intermittent blood glucose levels alone, and the potential application of CGM as an adjunct to clinical care.

Time in range, as measured by continuous glucose monitor, as a predictor of microvascular complications in type 2 diabetes: a systematic review

Continuous glucose monitoring (CGM)-derived time in range (TIR) correlates with hemoglobin A1c (A1c) among patients with type 2 diabetes mellitus (T2DM); however, there is a paucity of data evaluating its association with microvascular complications. We conducted this systematic review to examine the association between TIR and microvascular complications of diabetic retinopathy (DR), diabetic nephropathy (DN), and diabetic peripheral neuropathy (DPN). We conducted a comprehensive literature search on PubMed, Scopus, and Web of Science online databases following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Full-text original articles that evaluated the association between CGM-derived TIR and risk of microvascular complications and were published between 2010 and June 2021 were included in our systematic review. The quality of the included studies was evaluated using the National Heart, Lung, and Blood Institute Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. Data were analyzed using qualitative synthesis. Eleven studies on a total of 13 987 patients were included in the systematic review. The median sample size, baseline A1c, and diabetes duration were 466 patients (range: 105-5901), 8.2% (SD 0.5%), and 11.3 years (1.0), respectively. Majority of the studies were conducted in Asia (10 out of 11). Four studies evaluated the relationship between CGM-derived TIR and DR and CGM-derived TIR and DN, while seven studies evaluated the relationship between CGM-derived TIR and DPN. A 10% increase in TIR was associated with a reduction in albuminuria, severity of DR, and prevalence of DPN and cardiac autonomic neuropathy. In addition, an association was observed between urinary albumin to creatinine ratio but not with estimated glomerular filtration rate. This review summarizes recent evidence supporting an association between CGM-derived TIR and microvascular complications among patients with T2DM. A larger-scale multicenter investigation that includes more diverse participants is warranted to further validate the utility of TIR as a predictor of diabetic microvascular complications.

Influence of dipeptidyl peptidase-4 inhibitors on glycemic variability in patients with type 2 diabetes: A meta-analysis of randomized controlled trials

OBJECTIVE

The influence of dipeptidyl peptidase-4 (DPP4) inhibitors on glycemic variability compared to other oral antidiabetic drugs (OADs), measured based on the mean amplitude of glycemic excursions (MAGE), has not been comprehensively analyzed. The aim of the study was to perform a meta-analysis to compare the effects of DPP4 inhibitors on MAGE with other OADs in type 2 diabetes mellitus (T2DM) patients without concurrent insulin treatments.

METHODS

The Medline (PubMed), Embase (Ovid), and CENTER (Cochrane Library) databases were searched for relevant randomized controlled trials (RCTs). Study characteristics and outcome data were independently extracted by two authors. A random-effect model was used to combine the results.

RESULTS

Fourteen studies with 855 patients were included. Compared to other OADs, DPP4 inhibitors significantly reduced MAGE (mean difference [MD]: -0.69 mmol/L, 95% confidence interval [CI]: -0.95 to -0.43, P<0.001) with mild heterogeneity (I^{2 =} 28%). Predefined subgroup analyses suggested that DPP4 inhibitors were more effective in reducing MAGE compared to insulin secretagogues (MD: -0.92 mmol/L, P<0.001) and non-secretagogues (MD: -0.43 mmol/L, P=0.02), as well as compared to sulfonylureas (MD: -0.91 mmol/L, P<0.001) and sodium glucose cotransporter 2 inhibitors (MD: -0.67 mmol/L, P=0.03).

CONCLUSIONS

DPP4 inhibitors may significantly reduce glycemic variability compared to other oral anti-diabetic drugs, as evidenced by MAGE in T2DM patients with no concurrent insulin treatment.

SYSTEMATIC REVIEW REGISTRATION

INPLASY, registration number: INPLASY2021120113.

A comparison of FreeStyle Libre 2 to self-monitoring of blood glucose in children with type 1 diabetes and sub-optimal glycaemic control: a 12-week randomised controlled trial protocol

Purpose

Frequent glucose monitoring is necessary for optimal glycaemic control. Second-generation intermittently scanned glucose monitoring (isCGM) systems inform users of out-of-target glucose levels and may reduce monitoring burden. We aim to compare FreeStyle Libre 2 (Abbott Diabetes Care, Witney, U.K.) to self-monitoring of blood glucose in children with type 1 diabetes and sub-optimal glycaemic control.

Methods

This open-label randomised controlled trial will enrol 100 children (4–13 years inclusive, diagnosis of type 1 diabetes ≥ 6 months, HbA1c 58–110 mmol/mol [7.5–12.2%]), from 5 New Zealand diabetes centres. Following 2 weeks of blinded sensor wear, children will be randomised 1:1 to control or intervention arms. The intervention (duration 12 weeks) includes second-generation isCGM (FreeStyle Libre 2) and education on using interstitial glucose data to manage diabetes. The control group will continue self-monitoring blood glucose. The primary outcome is the difference in glycaemic control (measured as HbA1c) between groups at 12 weeks. Pre-specified secondary outcomes include change in glucose monitoring frequency, glycaemic control metrics and psychosocial outcomes at 12 weeks as well as isCGM acceptability.

Discussion

This research will investigate the effectiveness of the second-generation isCGM to promote recommended glycaemic control. The results of this trial may have important implications for including this new technology in the management of children with type 1 diabetes.

Trial registration

This trial was prospectively registered with the Australian New Zealand Clinical Trials Registry on 19 February 2020 (ACTRN12620000190909p) and the World Health Organization International Clinical Trials Registry Platform (Universal Trial Number U1111-1237-0090).

Effects of Acute Resistance Exercise with and without Whole-Body Electromyostimulation and Endurance Exercise on the Postprandial Glucose Regulation in Patients with Type 2 Diabetes Mellitus: A Randomized Crossover Study

Background: Long hyperglycemic episodes trigger complications in type 2 diabetes mellitus (T2DM) patients. Postprandial glucose excursions can be reduced by acute physical activity. However, it is not yet clear which type of exercise has the best effect on postprandial glucose levels. Methods: Six T2DM patients participated in three 20-min moderate-intensity exercise sessions after breakfast in a randomized order: resistance exercise with whole-body electromyostimulation (WB-EMS), resistance exercise without electromyostimulation (RES) and cycling endurance exercise (END). A continuous glucose monitoring system recorded glucose dynamics. Results: Postprandially-increased glucose levels decreased in all cases. Time to baseline (initial value prior to meal intake) was quite similar for WB-EMS, RES and END. Neither glucose area under the curve (AUC), nor time in range from the start of the experiment to its end (8 h later) differed significantly. A Friedman analysis of variance, however, revealed an overall significant difference for AUC in the post-exercise recovery phase (END seems to have superior effects, but post-hoc tests failed statistical significance). Conclusions: There are no notable differences between the effects of the different types of exercise on glucose levels, especially when comparing values over a longer period of time.

Benefits of a Switch from Intermittently Scanned Continuous Glucose Monitoring (isCGM) to Real-Time (rt) CGM in Diabetes Type 1 Suboptimal Controlled Patients in Real-Life: A One-Year Prospective Study §

The switch from intermittently scanned continuous glucose monitoring (isCGM) to real-time (rt) CGM could improve glycemic management in suboptimal controlled type 1 diabetes patients, but long-term study is lacking. We evaluated retrospectively the ambulatory glucose profile (AGP) in such patients after switching from Free Style Libre 1 (FSL1) to Dexcom G4 (DG4) biosensors over 1 year. Patients (n = 21, 43 ± 15 years, BMI 25 ± 5, HbA1c 8.1 ± 1.0%) had severe hypoglycemia and/or HbA1c ≥ 8%. AGP metrics (time-in-range (TIR) 70–180 mg/dL, time-below-range (TBR) <70 mg/dL or <54 mg/dL, glucose coefficient of variation (%CV), time-above-range (TAR) >180 mg/dL or >250 mg/dL, glucose management indicator (GMI), average glucose) were collected the last 3 months of FSL1 use (M0) and of DG4 for 3, 6 (M6) and 12 (M12) months of use. Values were means ± standard deviation or medians [Q1;Q3]. At M12 versus M0, the higher TIR (50 ± 17 vs. 45 ± 16, p = 0.036), and lower TBR < 70 mg/dL (2.5 [1.6;5.5] vs. 7.0 [4.5;12.5], p = 0.0007), TBR < 54 mg/dL (0.7 [0.4;0.8] vs. 2.3 [0.8;7.0], p = 0.007) and %CV (39 ± 5 vs. 45 ± 8, p = 0.0009), evidenced a long-term effectiveness of the switch. Compared to M6, TBR < 70 mg/dL decreased, %CV remained stable, while the improvement on hyperglycemia exposure decreased (higher GMI, TAR and average glucose). This switch was a relevant therapeutic option, though a loss of benefit on hyperglycemia stressed the need for optimized management of threshold alarms. Nevertheless, few patients attained the recommended values for AGP metrics, and the reasons why some patients are “responders” vs. “non-responders” warrant to be investigated.

Effect of flash glucose monitoring in adults with type 1 diabetes: a nationwide, longitudinal observational study of 14,372 flash users compared with 7691 glucose sensor naive controls

AIMS/HYPOTHESIS

The aim of this work was to evaluate changes in glycaemic control (HbA_1c) and rates of severe hypoglycaemia over a 2 year period after initiation of flash glucose monitoring (FM) in type 1 diabetes.

METHODS

Using data from the Swedish National Diabetes Registry, 14,372 adults with type 1 diabetes with a new registration of FM during 2016-2017 and with continued FM for two consecutive years thereafter, and 7691 control individuals using conventional self-monitoring of blood glucose (SMBG) during the same observation period, were included in a cohort study. Propensity sores and inverse probability of treatment weighting (IPTW) were used to balance FM users with SMBG users. Changes in HbA_1c and events of severe hypoglycaemia were compared.

RESULTS

After the start of FM, the difference in IPTW change in HbA_1c was slightly greater in FM users compared with the control group during the follow-up period, with an estimated mean absolute difference of -1.2 mmol/mol (-0.11%) (95% CI -1.64 [-0.15], -0.75 [-0.07]; p < 0.0001) after 15-24 months. The change in HbA_1c was greatest in those with baseline HbA_1c ≥70 mmol/mol (8.5%), with the estimated mean absolute difference being -2.5 mmol/mol (-0.23%) (95% CI -3.84 [-0.35], -1.18 [-0.11]; p = 0.0002) 15-24 months post index. The change was also significant in the subgroups with initial HbA_1c ≤52 mmol/mol (6.9%) and 53-69 mmol/mol (7.0-8.5%). Risk of severe hypoglycaemic episodes was reduced by 21% for FM users compared with control individuals using SMBG (OR 0.79 [95% CI 0.69, 0.91]; p = 0.0014)].

CONCLUSIONS/INTERPRETATION

In this large cohort, the use of FM was associated with a small and sustained improvement in HbA_1c, most evident in those with higher baseline HbA_1c levels. In addition, FM users experienced lower rates of severe hypoglycaemic events compared with control individuals using SMBG for self-management of glucose control.

Relationship between glycemic intraday variations evaluated in continuous glucose monitoring and HbA1c variability in type 2 diabetes: pilot study

BACKGROUND

HbA1c variability is independent of mean HbA1c, and associated with mortality due to vascular complications. However, the significance of HbA1c variability is unknown at present. In this study, we used flash glucose monitoring (FGM) and evaluated glycemic intraday variations, and then examined the association with HbA1c variability.

METHODS

We conducted a retrospective pilot study of 26 patients treated at the Outpatient department for type 2 diabetes mellitus (T2DM), and evaluated the following items associated with blood glucose levels and their changes/variations using FGM. The primary endpoint was factor(s) associated with standard deviation (SD) HbA1c over a 6-month period. To adjust for the effect of varying numbers of HbA1c measurements, we used the adjusted SD of HbA1c.

RESULTS

There were significant correlations between mean HbA1c and each of glucose management indicator, maximum, percent time at glucose > 180 mg/day, mean of daily difference of blood glucose, and high blood glucose index. Adjusted SD HbA1c correlated significantly with percent time at glucose < 70 mg/dL and low blood glucose index. We estimated the regression coefficient of adjusted SD HbA1c using multivariate linear regression analysis, and noted that the presence of hypoglycemia affected Adjusted SD HbA1c (β = 0.130, SE = 0.044, P = 0.008). Hypoglycemia was noted in 17 patients, and adjusted SD HbA1c was significantly higher (p = 0.001) in the hypoglycemic group (0.22 ± 0.12%), compared with the non-hypoglycemic group (0.08 ± 0.05%). The cut-off value of adjusted SD HbA1c was 0.109% in the hypoglycemic group.

CONCLUSIONS

The results showed that HbA1c variability is associated with hypoglycemia. For patients with high HbA1c variability, we recommend evaluation for the presence of hypoglycemia and reconsideration of their treatment regimen including their glucose-lowering medications. Trial registration The study protocol and opt-out method of informed consent were approved by the ethics committees of the University of Occupational and Environmental Health (Trial registration: H27-186, Registered 25 Dec 2015).

Associations between continuous glucose monitoring-derived metrics and diabetic retinopathy and albuminuria in patients with type 2 diabetes

INTRODUCTION

Preventing the development and progression of diabetic microvascular complications through optimal blood glucose control remains an important challenge. Whether metrics based on continuous glucose monitoring are useful for the management of diabetic microvascular complications is not entirely clear.

RESEARCH DESIGN AND METHODS

This is an exploratory analysis of an ongoing prospective, multicenter, 5-year follow-up observational study. Study participants included 999 outpatients with type 2 diabetes who underwent continuous glucose monitoring at baseline. Associations between continuous glucose monitoring-derived metrics and the severity of diabetic retinopathy or albuminuria were investigated using multivariable proportional odds models.

RESULTS

The overall prevalence of diabetic retinopathy was 22.2%. Multivariate analysis with proportional odds models demonstrated that continuous glucose monitoring-derived metrics related to intraday and interday glucose variability are significantly associated with the severity of diabetic retinopathy, even after adjusting for various possible risk factors. However, significant relationships were not observed after adjusting for hemoglobin A1c (HbA1c) levels. The prevalence of microalbuminuria and macroalbuminuria was 20.3% and 6.7%, respectively. Similarly, multivariate analysis demonstrated that those metrics are significantly associated with the severity of albuminuria. These relationships remained significant even after further adjusting for HbA1c levels.

CONCLUSIONS

Continuous glucose monitoring-derived metrics related to intraday and interday glucose variability are significantly associated with the severity of diabetic retinopathy or albuminuria in patients with type 2 diabetes. Thus, evaluating these metrics might possibly be useful for risk assessment of diabetic microvascular complications.Trial registration number UMIN000032325.

Flash Continuous Glucose Monitoring: A Practical Guide and Call to Action for Pharmacists

Despite advances in diabetes technology, the proportion of patients with type 2 diabetes achieving recommended glycemic goals remains suboptimal. There is a growing interest in flash continuous glucose monitoring (CGM) among patients, pharmacists and providers. Pharmacists are well positioned to collaborate with patients and providers in ambulatory care or community-based settings to allow a greater number of patients with diabetes to harness the benefits of flash CGM. The purpose of this narrative review is to provide pharmacists with a background on flash CGM technology, review the data supporting pharmacist-driven flash CGM services, and address common questions that arise in pharmacy practice surrounding flash CGM.

Noninvasive Monitoring of Glucose Using Near-Infrared Reflection Spectroscopy of Skin-Constraints and Effective Novel Strategy in Multivariate Calibration

For many years, successful noninvasive blood glucose monitoring assays have been announced, among which near-infrared (NIR) spectroscopy of skin is a promising analytical method. Owing to the tiny absorption bands of the glucose buried among a dominating variable spectral background, multivariate calibration is required to achieve applicability for blood glucose self-monitoring. The most useful spectral range with important analyte fingerprint signatures is the NIR spectral interval containing combination and overtone vibration band regions. A strategy called science-based calibration (SBC) has been developed that relies on a priori information of the glucose signal ("response spectrum") and the spectral noise, i.e., estimates of the variance of a sample population with negligible glucose dynamics. For the SBC method using transcutaneous reflection skin spectra, the response spectrum requires scaling due to the wavelength-dependent photon penetration depth, as obtained by Monte Carlo simulations of photon migration based on estimates of optical tissue constants. Results for tissue glucose concentrations are presented using lip NIR-spectra of a type-1 diabetic subject recorded under modified oral glucose tolerance test (OGTT) conditions. The results from the SBC method are extremely promising, as statistical calibrations show limitations under the conditions of ill-posed equation systems as experienced for tissue measurements. The temporal profile differences between the glucose concentration in blood and skin tissue were discussed in detail but needed to be further evaluated.

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.

Individualization of recommendations from the international consensus on continuous glucose monitoring-derived metrics in Japanese children and adolescents with type 1 diabetes

We assessed the significance of recommendations from the international consensus on continuous glucose monitoring (CGM)-derived metrics in Japanese children and adolescents with type 1 diabetes. Eighty-five patients (age, 13.5 ± 4.7 years) who wore the FreeStyle^® Libre for a 28-day period were enrolled in this study. Seventy-three patients were treated with multiple daily injections of insulin and 12 with insulin pump therapy without using a sensor-augmented pump or a predictive low-glucose suspend-function pump. We evaluated the relationship between CGM-derived metrics: time in range (TIR: 70-180 mg/dL), time below range (TBR: <70 mg/dL), and time above range (TAR: >180 mg/dL), and laboratory-measured HbA1c and estimated HbA1c (eA1c) levels calculated from the mean glucose values. The TIR was 50.7 ± 12.2% (23-75%), TBR was 11.8 ± 5.8% (2-27%), and TAR was 37.5 ± 13.5% (9-69%). The TIR was highly correlated with HbA1c level, eA1c level, and TAR, but not with TBR. An HbA1c level of 7.0% corresponded to a TIR of 55.1% (95% CI: 53.7-56.5%), whereas a TIR of 70% corresponded to an HbA1c level of 6.1% (95% CI: 5.9-6.3%). The results of eA1c levels were similar to those observed for HbA1c levels. From these findings, we conclude that low rates of a recommended TIR of 70% may be due to less use of advanced technology and insufficient comprehensive diabetes care. Ethnic characteristics including lifestyle and eating customs may have contributed to the result. CGM-derived targets must be individualized based on ethnic characteristics, insulin treatment and diabetes care, and needs of individuals with diabetes.

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.

Differences in the effects of Kenyan, Tanzanian, and Ethiopian coffee intake on interstitial glucose levels measured by FreeStyle Libre: A pilot case study

Background

Although generally considered part of a healthy diet, coffee consumption has been suspected to be associated with elevated epinephrine levels and increasing insulin resistance.

Objectives

We studied the effects of the intake of 3 different types of coffee (Tanzanian, Ethiopian, and Kenyan) on postprandial interstitial glucose levels.

Method

Interstitial glucose levels were measured every 15 minutes using the FreeStyle Libre glucose monitoring system (Abbott Diabetes Care Ltd, Witney, United Kingdom) in each individual after drinking coffee compared with when not consuming coffee.

Results

Unlike Tanzanian and Ethiopian coffees, Kenyan coffee suppressed the increase of postprandial interstitial glucose levels. Kenyan coffee beans contain less anhydrous caffeine and more chlorogenic acid than Tanzanian and Ethiopian coffee beans. These findings may explain the different effects of these coffee types on postprandial interstitial glucose levels. Furthermore, Kenyan coffee beans inhibited α-glucosidase activity, which may partially explain why Kenyan coffee reduces postprandial interstitial glucose levels.

Conclusions

Coffee is widely consumed as a beverage worldwide, and our findings suggest that patients with diabetes mellitus may benefit from drinking Kenyan coffee because of its ability to reduce postprandial interstitial glucose levels. (Curr Ther Res Clin Exp. 2020; 81:XXX-XXX).

Comparing effects of continuous glucose monitoring systems (CGMs) and self-monitoring of blood glucose (SMBG) amongst adults with type 2 diabetes mellitus: a systematic review protocol

BACKGROUND

Continuous glucose monitorings (CGMs) have been used to manage diabetes with reasonable glucose control amongst patients with type 2 diabetes (T2D) in recent decades. CGMs measure interstitial fluid glucose levels to provide information about glucose levels, which identify fluctuation that would not have been identified with conventional self-monitoring. Self-monitoring of blood glucose (SMBG) is a classical tool to measure glycaemic changes. However, the effectiveness of glucose control, hypoglycemia, weight change, quality of life and user satisfaction, are needed to evaluate and compare CGMs and SMBG amongst adults with T2D.

METHODS

The review will compare the various forms of CGM systems (i.e flash CGM, real-time CGM, retrospective CGM) versus SMBG or usual intervention regarding diabetes management amongst adults with T2D. The following databases will be searched: Cochrane Library, PubMed, EMBASE, CINAHL, PsycINFO, Scopus and grey literature (ClinicalTrials.gov, PsycEXTRA, ProQuest Dissertations, Google Scholar and Theses Global) for the identification of studies. The studies involving adults (aged ≥ 18 years old) will be included. We will only include and summarise randomised clinical trials (RCTs) with respect to authors, publication type, year, status and type of devices. Studies published in English between February 2010 and March 2020, will be included as the field of CGMs amongst T2D patients has emerged over the last decade. Primary outcomes will be HbA1c (glycosylated haemoglobin level) (mmol/L), body weight (kg), time spent with hypoglycaemia (< 70 mg/dl) or hyperglycaemia (≥ 180 mg/dl), blood pressure (< 140/90 mmHg is considered as good management) and quality of life (understanding and feeling of living situation based on culture and value system). Secondary outcome measures will be user satisfaction (patient or treatment/intervention satisfaction or satisfaction scale) and barriers (physical and mental difficulties or issues). Study selection, data extraction and risk of bias assessment will be conducted independently by at least two reviewers. A third reviewer will determine and resolve discrepancies. Moreover, the quality of the evidence of the review will be assessed according to the Grading of Recommendations Assessment, Development and Evaluation tool (GRADE).

DISCUSSION

The review will synthesise evidence on the comparison between using CGMs and SMBG. The results will support researchers and health professionals to determine the most effective methods/technologies in the overall diabetes management.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42020149212.

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.

Positioning time in range in diabetes management

Recent upswings in the use of continuous glucose monitoring (CGM) technologies have given people with diabetes and healthcare professionals unprecedented access to a range of new indicators of glucose control. Some of these metrics are useful research tools and others have been welcomed by patient groups for providing insights into the quality of glucose control not captured by conventional laboratory testing. Among the latter, time in range (TIR) is an intuitive metric that denotes the proportion of time that a person's glucose level is within a desired target range (usually 3.9-10.0 mmol/l [3.5-7.8 mmol/l in pregnancy]). For individuals choosing to use CGM technology, TIR is now often part of the expected conversation between patient and healthcare professional, and consensus recommendations have recently been produced to facilitate the adoption of standardised TIR targets. At a regulatory level, emerging evidence linking TIR to risk of complications may see TIR being more widely accepted as a valid endpoint in future clinical trials. However, given the skewed distribution of possible glucose values outside of the target range, TIR (on its own) is a poor indicator of the frequency or severity of hypoglycaemia. Here, the state-of-the-art linking TIR with complications risk in diabetes and the inverse association between TIR and HbA_1c are reviewed. Moreover, the importance of including the amount and severity of time below range (TBR) in any discussions around TIR and, by inference, time above range (TAR) is discussed. This review also summarises recent guidance in setting 'time in ranges' goals for individuals with diabetes who wish to make use of these metrics. For most people with type 1 or type 2 diabetes, a TIR >70%, a TBR <3.9 mmol/l of <4%, and a TBR <3.0 mmol/l of <1% are recommended targets, with less stringent targets for older or high-risk individuals and for those under 25 years of age. As always though, glycaemic targets should be individualised and rarely is that more applicable than in the personal use of CGM and the data it provides.

Precision Medicine and Artificial Intelligence: A Pilot Study on Deep Learning for Hypoglycemic Events Detection based on ECG

Tracking the fluctuations in blood glucose levels is important for healthy subjects and crucial diabetic patients. Tight glucose monitoring reduces the risk of hypoglycemia, which can result in a series of complications, especially in diabetic patients, such as confusion, irritability, seizure and can even be fatal in specific conditions. Hypoglycemia affects the electrophysiology of the heart. However, due to strong inter-subject heterogeneity, previous studies based on a cohort of subjects failed to deploy electrocardiogram (ECG)-based hypoglycemic detection systems reliably. The current study used personalised medicine approach and Artificial Intelligence (AI) to automatically detect nocturnal hypoglycemia using a few heartbeats of raw ECG signal recorded with non-invasive, wearable devices, in healthy individuals, monitored 24 hours for 14 consecutive days. Additionally, we present a visualisation method enabling clinicians to visualise which part of the ECG signal (e.g., T-wave, ST-interval) is significantly associated with the hypoglycemic event in each subject, overcoming the intelligibility problem of deep-learning methods. These results advance the feasibility of a real-time, non-invasive hypoglycemia alarming system using short excerpts of ECG signal.

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.

Monitoring of Pediatric Type 1 Diabetes

Regular self-monitoring of blood glucose levels, and ketones when indicated, is an essential component of type 1 diabetes (T1D) management. Although fingerstick blood glucose monitoring has been the standard of care for decades, ongoing rapid technological developments have resulted in increasingly widespread use of continuous glucose monitoring (CGM). This article reviews recommendations for self-monitoring of glucose and ketones in pediatric T1D with particular emphasis on CGM and factors that impact the accuracy and real-world use of this technology.

Relationship between interstitial glucose variability in ambulatory glucose profile and standardized continuous glucose monitoring metrics; a pilot study

BACKGROUND

Treatment indexes using continuous glucose monitoring (CGM) have become standardized internationally, and the use of ambulatory glucose profile (AGP) is currently recommended. However, the relationship between AGP indexes and standardized CGM metrics has not been investigated. Using flash glucose monitoring (FGM), this retrospective study served to evaluate the association of the inter-quartile range (IQR) of AGP with standardized CGM metrics.

METHODS

The study subjects were 30 patients with type 2 diabetes mellitus (T2DM) and 23 non-diabetic patients (control group). We evaluated average IQR (AIQR) and standardized CGM metrics. The primary endpoint was the relationship between AIQR and Time in range (TIR) in a 24-h period.

RESULTS

In the T2DM group, the AIQR was notably high and correlated negatively with TIR, and positively with Time above range, average interstitial glucose level, standard deviation of interstitial glucose, coefficient of variation of interstitial glucose, and mean of daily difference in blood glucose (MODD). For the T2DM group, the AIQR was notably lower in patients who achieved TIR > 70%, compared to those who did not. The AIQR cutoff value, as determined by ROC analysis, was 28.3 mg/dl for those who achieved TIR > 70%. No association was detected between the presence of hypoglycemia and AIQR.

CONCLUSIONS

Our study is the first to provide the AIQR cutoff value for achieving the TIR target value. The range of interstitial glucose variability in AGP was associated with indexes of intra- and interday variations and hyperglycemia. Our results provide new perspectives in the yet-to-be established methods for evaluation of AGP in practical clinical settings.

Patient self-testing in chronic disease management

Chronic disease poses a major burden to patients and health care systems. This review considers how patient self-testing can contribute to the management of chronic disease. Self-testing can only confer benefit if it occurs in the context of an empowered patient who has the skills and training to translate test results into meaningful actions. The benefits may include improved clinical outcomes, greater patient convenience and improved psychological well-being; separately and together these may contribute to reduced costs of care. As self-testing may be expensive and burdensome to patients, it is important that its use in chronic disease is supported by a robust evidence base confirming its utility and efficacy. The design of studies to assess the impact of self-testing poses challenges for the researcher and the quality of evidence presented is often variable. Randomised controlled trials (RCTs) provide more robust evidence than observational studies; the intervention under study is not just self-testing but includes the educational support to allow patients to use results effectively. This review discusses the evidence base relating to patient self-testing in diabetes, anticoagulant monitoring and in renal transplant patients and in particular highlights the impact of new technology developments such as flash glucose monitoring in diabetes.

Incremental role of glycaemic variability over HbA1c in identifying type 2 diabetic patients with high platelet reactivity undergoing percutaneous coronary intervention

BACKGROUND

Diabetic patients with on-treatment high platelet reactivity (HPR) show an increased risk of thrombotic events. Whether measuring glycated haemoglobin (HbA1c) levels and/or glycaemic variability (GV) may help identifying diabetic patients at higher risk deserving tailored antiplatelet and/or glucose lowering strategies is unknown. We aimed to investigate the relationship between GV, HbA1c levels and platelet reactivity in patients with type 2 diabetes mellitus (DM) undergoing percutaneous coronary intervention (PCI).

METHODS

Platelet reactivity was measured in type 2 DM patients using VerifyNow P2Y12 assay. HPR was defined as P2Y12 Reaction Unit (PRU) > 240. GV was expressed through mean amplitude of glycaemic excursions (MAGE) and coefficient of variance (CV) by using the iPro™ continuous glucose recorder.

RESULTS

Thirty-five patients (age 70 ± 9 years, 86% male, mean HbA1c 7.2 ± 1.0%) on clopidogrel therapy were enrolled. HbA1c was independently associated with HPR (OR 7.25, 95% CI 1.55-33.86, p = 0.012). Furthermore, when factored into the model, GV indexes provided independent (OR 1.094, 95% CI 1.007-1.188, p < 0.034) and additional (p < 0.001) diagnostic significance in identifying diabetic patients with HPR.

CONCLUSIONS

Glyco-metabolic state significantly correlates with HPR in well-controlled type 2 DM patients on clopidogrel therapy. HbA1c identifies patients at higher thrombotic risk but the highest diagnostic accuracy is achieved by combining GV and HbA1c. Whether individualized antithrombotic and glucose-lowering therapies based on the assessment of these parameters may reduce the incidence of thrombotic events in patients undergoing PCI should be further investigated.

Reliability of real-time continuous glucose monitoring in infants

BACKGROUND

Neonatal hypoglycemia is a common and treatable risk factor for neurological impairment. Real-time continuous glucose monitoring (RT-CGM) can show glucose concentration in real time. Using an RT-CGM alarm, physicians can be alerted and intervene in hypoglycemia. No reports, however, have evaluated the reliability of RT-CGM at low glucose levels in infants. This study therefore investigated the difference between blood glucose (BG) and RT-CGM sensor data at low glucose levels and assessed the optimum method of using a hypoglycemic alarm in infants.

METHODS

We enrolled infants whose glycemic management was difficult. We calculated the mean absolute difference (MAD) and mean absolute relative difference (MARD) between BG and RT-CGM sensor data. We compared the MAD and MARD between the low BG fluctuation and high BG fluctuation groups.

RESULTS

We used RT-CGM for 12 patients (29 times) and investigated 448 pairs of BG and RT-CGM sensor data. The MAD between these pairs was 9.3 ± 8.9 mg/dL, and the MARD was 11.5%. The MAD at low glucose was 7.7 ± 6.0 mg/dL, and the MARD was 16.2%. The MAD and MARD were 6.8 ± 5.4 mg/dL and 7.8% in the low fluctuation group and 10.1 ± 9.5 mg/dL and 12.7% in the high fluctuation group, respectively.

CONCLUSIONS

The difference between BG and RT-CGM sensor data changes with the degree of fluctuation in BG. When physicians set the hypoglycemic alarm, consideration of this difference and a change in the alarm setting according to the degree of fluctuation in BG may be useful.

Personal Versus Professional Continuous Glucose Monitoring: When to Use Which on Whom

IN BRIEF With the introduction of intermittently scanned continuous glucose monitoring (CGM) systems to the marketplace, providers and patients now have several options to continuously monitor glucose levels. This article addresses appropriate patient selection criteria for using patient- or practice-based CGM systems and the barriers to achieving optimal benefits from this technology. The authors have developed a flowchart to guide clinicians and patients in decision-making regarding the most appropriate type of CGM to use in various circumstances.

Digital health technology and mobile devices for the management of diabetes mellitus: state of the art

Diabetes mellitus is a disease that can be difficult to manage and requires high levels of health literacy and numeracy, self-monitoring and frequent contact with clinicians. If not optimally controlled, diabetes can lead to kidney failure, blindness and cardiovascular complications, which, in turn, contribute to increasing healthcare costs. Although not yet widely used, mobile health (mHealth) tools have enhanced diabetes management and prevention and are likely to play an increasing role with the growth of smartphone ownership and medical device innovations. Recent mHealth interventions targeting type 1 and type 2 diabetes are diverse in their goals and components, and include insulin management applications, wearable blood glucose meters, automated text messages, health diaries and virtual health coaching. In this paper, we review the modalities and components of various impactful interventions for insulin management, diabetes education, self-management and prevention. More work is needed to investigate how individual demographic, socioeconomic, behavioural and clinical characteristics contribute to patient engagement and the efficacy of mHealth tools for diabetes.

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.

Improving patient self-care using diabetes technologies

Diabetes technologies are an unstoppable phenomenon. They offer opportunities to improve patient self-care through empowerment. However, they can be a challenge for both patients and clinicians. Thus, the use of technology may empower or burden. To understand and benefit from the use of diabetes technologies, one must understand the currently unmet needs in diabetes management. These unmet needs call for perspectives beyond glycated hemoglobin and an evaluation of technology solutions. Optimal use of these technologies is necessary to obtain benefits and achieve cost-effectiveness; this process depends on diabetes education and training. This review evaluates clinician and patient perspectives regarding diabetes technologies, followed by an evaluation of technology solutions. Diabetes technology solutions are evaluated according to available results about their effectiveness and their potential to empower people living with diabetes.

Application and Utility of Continuous Glucose Monitoring in Pregnancy: A Systematic Review

Background: In the past decade, continuous glucose monitoring (CGM) has been proven to have similar accuracy to self-monitoring of blood glucose (SMBG) and yet provides better therapy optimization and detects trends in glucose values due to higher frequency of testing. Even though the feasibility and utility of CGM has been proven successfully in Type 1 and 2 diabetes, there is a lack of knowledge of its application and effectiveness in pregnancy, especially in gestational diabetes mellitus (GDM). In this review, we aimed to summarize and evaluate the updated scientific evidence on the application of CGM in pregnancies complicated with GDM. Methods: A search using keywords related to CGM and GDM on PubMed was conducted and articles were filtered based on full text, year of publication (Jan 1998-Dec 2018), human subject studies, and written in English. Reviews and duplicate articles were removed. A final total of 29 articles were included in this review. Results: In terms of maternal and fetal outcomes, inconsistent evidence was reported. Among GDM patients using CGM and SMBG, two randomized controlled trials (RCTs) found no significant differences in macrosomia, birth weight (BW), and gestational age (GA) at delivery between these two groups, while one prospective cohort found a lower incidence of cesarean section and macrosomia in CGM use subjects. Furthermore, CGM use was consistently found to have increased detection in dysglycemia and glycemic variability compared to SMBG. In terms of clinical utility, CGM use led to more treatment adjustments and lower gestational weight gain (GWG). Lastly, CGM use showed higher postprandial glucose levels in GDM-complicated pregnancies than in normal pregnancies. Conclusion: Current updated evidence suggests that CGM is superior to SMBG among GDM pregnancies in terms of detecting hypoglycemic and hyperglycemic episodes, which might result in an improvement of maternal and fetal outcomes. In addition, CGM detects a wider glycemic variability in GDM mothers than non-GDM controls. Further research with larger sample sizes and complete pregnancy coverage is needed to explore the clinical utility such as screening and predictive values of CGM for GDM.