Behavior Modification in Prediabetes and Diabetes: Potential Use of Real-Time Continuous Glucose Monitoring

Continuous glucose monitoring for glycaemic control and cardiovascular risk reduction in patients with type 2 diabetes not on insulin therapy: A clinical trial

AIM

To evaluate the impact of the Dexcom G6 continuous glucose monitoring (CGM) device on glycaemic control and cardiometabolic risk in patients with type 2 diabetes mellitus (T2DM) at high cardiovascular risk who are not on insulin therapy.

MATERIALS AND METHODS

Adults with T2DM with glycated haemoglobin (HbA1c) >7% and body mass index (BMI) ≥30 kg/m2 not using insulin were enrolled in a two-phase cross-over study. In phase 1, CGM data were blinded, and participants performed standard glucose self-monitoring. In phase 2, the CGM data were unblinded, and CGM, demographic and cardiovascular risk factor data were collected through 90 days of follow-up and compared using paired tests.

RESULTS

Forty-seven participants were included (44% women; 34% Black; mean age 63 years; BMI 37 kg/m2; HbA1c 8.4%; 10-year predicted atherosclerotic cardiovascular disease risk 24.0%). CGM use was associated with a reduction in average glucose (184.0 to 147.2 mg/dl, p < .001), an increase in time in range (57.8 to 82.8%, p < .001) and a trend towards lower glucose variability (26.2 to 23.8%). There were significant reductions in HbA1c, BMI, triglycerides, blood pressure, total cholesterol, diabetes distress and 10-year predicted risk for atherosclerotic cardiovascular disease (p < .05 for all) and an increase in prescriptions for sodium-glucose cotransporter 2 inhibitors (36.2 to 83.0%) and glucagon-like peptide-1 receptor agonists (42.5 to 87.2%, p < .001 for both).

CONCLUSIONS

Dexcom G6 CGM was associated with improved glycaemic control and cardiometabolic risk in patients with T2DM who were not on insulin. CGM can be a safe and effective tool to improve diabetes management in patients at high risk for adverse cardiovascular outcomes.

Innovative solution or cause for concern? The use of continuous glucose monitors in people not living with diabetes: A narrative review

AIMS

Continuous glucose monitors (CGMs) have expanded their scope beyond indicated uses for diabetes management and are gaining traction among people not living with diabetes (PNLD). CGMs track in time glucose levels and are proposed as tools for the early detection of abnormal glucose and a potential solution for its normalisation through behavioural change, particularly, diet personalisation and motivation of physical activity. This becomes relevance given the growing incidence of metabolic conditions, such as type 2 diabetes mellitus (T2DM). Clinical guidelines, however, do not recommend CGMs in contexts outside type 1 diabetes (T1DM) or insulin-treated T2DM. Therefore, there is a visible disconnect between the indicated and real-world usage of these medical devices. While the commercial market for CGMs in PNLD is expanding rapidly, a comprehensive and evidence-based evaluation of the devices' utility in this population has not been done. Therefore, this review aims to formulate a working model for CGM utility in PNLD as proposed by the 'health and wellness' market that advertises and distributes it to these individuals.

METHODS

We aim to critically analyse the available research addressing components of the working model, that is (1) detection of abnormal glucose; (2) behavioural change, and (3) metabolic health improvement.

RESULTS

We find a lack of consistent and high-quality evidence to support the utility of CGMs for these purposes. We identify significantly under-reserved areas including clinical benchmarks and scoring procedures for CGM measures, device acceptability, and potential adverse effects of CGMs on eating habits in PNLD. We also raise concerns about the robustness of available CGM research.

CONCLUSION

In the face of these research gaps, we urge for the commercial claims suggesting the utility of the device in PNLD to be labelled as misleading. We argue that there is a regulatory inadequacy that fuels 'off-label' CGM distribution and calls for the strengthening of post-market clinical follow-up oversight for CGMs. We hope this will help to avert the continued misinformation risk to PNLD and 'off-label' exacerbation of health disparities.

Polymeric Microneedles for Health Care Monitoring: An Emerging Trend

Bioanalyte collection by blood draw is a painful process, prone to needle phobia and injuries. Microneedles can be engineered to penetrate the epidermal skin barrier and collect analytes from the interstitial fluid, arising as a safe, painless, and effective alternative to hypodermic needles. Although there are plenty of reviews on the various types of microneedles and their use as drug delivery systems, there is a lack of systematization on the application of polymeric microneedles for diagnosis. In this review, we focus on the current state of the art of this field, while providing information on safety, preclinical and clinical trials, and market distribution, to outline what we believe will be the future of health monitoring.

Adding a Brief Continuous Glucose Monitoring Intervention to the National Diabetes Prevention Program: A Multimethod Feasibility Study

The National Diabetes Prevention Program (DPP) promotes lifestyle changes to prevent diabetes. However, only one-third of DPP participants achieve weight loss goals, and changes in diet are limited. Continuous glucose monitoring (CGM) has shown potential to raise awareness about the effects of diet and activity on glucose among people with diabetes, yet the feasibility of including CGM in behavioral interventions for people with prediabetes has not been explored. This study assessed the feasibility of adding a brief CGM intervention to the Arizona Cooperative Extension National DPP. Extension DPP participants were invited to participate in a single CGM-based education session and subsequent 10-day CGM wear period, during which participants reflected on diet and physical activity behaviors occurring prior to and after hyperglycemic events. Following the intervention, participants completed a CGM acceptability survey and participated in a focus group reflecting on facilitators and barriers to CGM use and its utility as a behavior change tool. A priori feasibility benchmarks included opt-in participation rates ≥ 50%, education session attendance ≥ 80%, acceptability scores ≥ 80%, and greater advantages than disadvantages of CGM emerging from focus groups, as analyzed using the Key Point Summary (KPS) method. Thirty-five DPP members were invited to participate; 27 (77%) consented, and 24 of 27 (89%) attended the brief CGM education session. Median survey scores indicated high acceptability of CGM (median = 5, range = 1-5), with nearly all (n = 23/24, 96%) participants believing that CGM should be offered as part of the DPP. In focus groups, participants described how CGM helped them make behavior changes to improve their glucose (e.g., reduced portion sizes, increased activity around eating events, and meditation). In conclusion, adding a single CGM-based education session and 10-day CGM wear to the DPP was feasible and acceptable. Future research will establish the efficacy of adding CGM to the DPP on participant health outcomes and behaviors.

Glucose levels measured with continuous glucose monitoring in uncomplicated pregnancies

INTRODUCTION

To characterize glucose levels during uncomplicated pregnancies, defined as pregnancy with a hemoglobin A1c <5.7% (<39 mmol/mol) in early pregnancy, and without a large-for-gestational-age birth, hypertensive disorders of pregnancy, or gestational diabetes mellitus (ie, abnormal oral glucose tolerance test).

RESEARCH DESIGN AND METHODS

Two sites enrolled 937 pregnant individuals aged 18 years and older prior to reaching 17 gestational weeks; 413 had an uncomplicated pregnancy (mean±SD body mass index (BMI) of 25.3±5.0 kg/m2) and wore Dexcom G6 continuous glucose monitoring (CGM) devices throughout the observed gestational period. Mealtimes were voluntarily recorded. Glycemic levels during gestation were characterized using CGM-measured glycemic metrics.

RESULTS

Participants wore CGM for a median of 123 days each. Glucose levels were nearly stable throughout all three trimesters in uncomplicated pregnancies. Overall mean±SD glucose during gestation was 98±7 mg/dL (5.4±0.4 mmol/L), median per cent time 63-120 mg/dL (3.5-6.7 mmol/L) was 86% (IQR: 82-89%), median per cent time <63 mg/dL (3.5 mmol/L) was 1.8%, median per cent time >120 mg/dL (6.7 mmol/L) was 11%, and median per cent time >140 mg/dL (7.8 mmol/L) was 2.5%. Mean post-prandial peak glucose was 126±22 mg/dL (7.0±1.2 mmol/L), and mean post-prandial glycemic excursion was 36±22 mg/dL (2.0±1.2 mmol/L). Higher mean glucose levels were low to moderately associated with pregnant individuals with higher BMIs (103±6 mg/dL (5.7±0.3 mmol/L) for BMI ≥30.0 kg/m2 vs 96±7 mg/dL (5.3±0.4 mmol/L) for BMI 18.5-<25 kg/m2, r=0.35).

CONCLUSIONS

Mean glucose levels and time 63-120 mg/dL (3.5-6.7 mmol/L) remained nearly stable throughout pregnancy and values above 140 mg/dL (7.8 mmol/L) were rare. Mean glucose levels in pregnancy trend higher as BMI increases into the overweight/obesity range. The glycemic metrics reported during uncomplicated pregnancies represent treatment targets for pregnant individuals.

Lifestyle Intervention With Smartphone App and isCGM for People at High Risk of Type 2 Diabetes: Randomized Trial

AIMS

Although conventional interventions for people at high risk of developing type 2 diabetes are usually conducted face-to-face, such interventions are burdensome for health care providers. We developed a lifestyle intervention program combining lifestyle coaching via a smartphone application augmented by intermittently scanned continuous glucose monitoring without burdening health care providers. Its effectiveness for glycemic control and body weight reduction in people at risk of type 2 diabetes was investigated.

MATERIALS AND METHODS

For this 12-week randomized unblinded trial with offline recruitment, participants with a hemoglobin A1c level of 5.6% to 6.4% or a fasting blood glucose of 110 to 125 mg/dL and body mass index (BMI) >23 kg/m2 but <40 kg/m2 were randomly assigned to the intervention group (App) and control group (C). The primary endpoint was the difference in time in range of blood glucose between 70 and 140 mg/dL (3.9-7.8 mmol/L) before and after the study period between the 2 groups.

RESULTS

Among 168 patients (mean age, 48.1 years; mean BMI, 26.6 kg/m2; and male, 80.4%), 82 and 86 were assigned to the App group and C group, respectively. After 12 weeks, time in range of blood glucose at 70 to 140 mg/dL significantly improved in the App group compared with the C group (-2.6 minutes/day vs +31.5 minutes/day, P = .03). Changes in time above range did not differ, whereas time below range (blood glucose <70 mg/dL; +23.5 minutes/day vs -8.9 minutes/day, P = .02) improved in the App group. BMI (-0.26 vs -0.59, P = .017) was reduced in the App group compared with the C group.

CONCLUSION

Intervention with a smartphone app and intermittently scanned continuous glucose monitoring increased glycemic control accompanied by decreased carbohydrate intake and weight loss. Further trials are needed to confirm whether these interventions can reduce incident type 2 diabetes.

Effectiveness of a culturally tailored diabetes education curriculum with real-time continuous glucose monitoring in a Latinx population with type 2 diabetes: the CUT-DM with CGM for Latinx randomised controlled trial study protocol

INTRODUCTION

The prevalence of type 2 diabetes (T2D) is increasing in the Latinx community. Despite telehealth and technology becoming more available, these resources are not reaching the Latinx population. Diabetes education is a cornerstone of treatment; however, access to culturally tailored content is a barrier to the Latinx population. Real-time continuous glucose monitoring (RT-CGM) is a patient-empowering tool that can improve glycaemic control, but it is not readily available for Latinx patients with T2D. We aim to evaluate a culturally tailored diabetes self-management education and support (DSMES) curriculum, using a team-based approach to improve glycaemic control, promote healthy behaviours and enhance patient access with the use of telehealth in Latinx individuals. The primary aim of the study is to evaluate the additive effectiveness of RT-CGM on glycaemia and behavioural changes among Latinx patients undergoing a culturally tailored DSMES. A sub aim of the study is to evaluate family members' change in behaviours.

METHODS

We propose a randomised controlled trial of blinded versus RT-CGM with 100 Latinx participants with T2D who will receive DSMES via telemedicine over 12 weeks (n=50 per group). The study will be conducted at a single large federally qualified health centre system. The control group will receive culturally tailored DSMES and blinded CGM. The intervention group will receive DSMES and RT-CGM. The DSMES is conducted by community health educators weekly over 12 weeks in Spanish or English, based on participant's language preference. Patients in the RT-CGM group will have cyclical use with a goal of 50 days wear time. The primary outcomes are changes in haemoglobin A1c and CGM-derived metrics at 3 and 6 months. The secondary outcomes include participants' self-management knowledge and behaviour and household members' change in lifestyle.

ETHICS AND DISSEMINATION

The study proposal was approved by the University of Washington ethics/institutional review board (IRB) Committee as minimal risk (IRB ID: STUDY00014396) and the Sea Mar IRB committee.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov identifier: NCT05394844.

Use of Continuous Glucose Monitors by People Without Diabetes: An Idea Whose Time Has Come?

BACKGROUND

Continuous glucose monitor (CGM) systems were originally intended only for people with diabetes. Recently, there has been interest in monitoring glucose concentrations in a variety of other situations. As data accumulate to support the use of CGM systems in additional states unrelated to diabetes, the use of CGM systems is likely to increase accordingly.

METHODS

PubMed and Google Scholar were searched for articles about the use of CGM in individuals without diabetes. Relevant articles that included sufficient details were queried to identify what cohorts of individuals were adopting CGM use and to define trends of use.

RESULTS

Four clinical user cases were identified: (1) metabolic diseases related to diabetes with a primary dysregulation of the insulin-glucose axis, (2) metabolic diseases without a primary pathophysiologic derangement of the insulin-glucose axis, (3) health and wellness, and (4) elite athletics. Seven trends in the use of CGM systems in people without diabetes were idenfitied which pertained to both FDA-cleared medical grade products as well as anticipated future products, which may be regulated differently based on intended populations and indications for use.

CONCLUSIONS

Wearing a CGM has been used not only for diabetes, but with a goal of improving glucose patterns to avoid diabetes, improving mental or physical performance, and promoting motivate healthy behavioral changes. We expect that clinicians will become increasingly aware of (1) glycemic patterns from CGM tracings that predict an increased risk of diabetes, (2) specific metabolic glucotypes from CGM tracings that predict an increased risk of diabetes, and (3) new genetic and genomic biomarkers in the future.

Continuous glucose monitoring in individuals undergoing gestational diabetes screening

BACKGROUND

Among guidelines on gestational diabetes mellitus, there is an incongruity about the threshold of maternal hyperglycemia to diagnose gestational diabetes mellitus.

OBJECTIVE

This study aimed to ascertain the association between continuous glucose monitoring metrics and adverse outcomes among individuals undergoing gestational diabetes mellitus screening.

STUDY DESIGN

This was a prospective study (from June 2020 to January 2022) of individuals who underwent 2-step gestational diabetes mellitus screening at ≤30 weeks of gestation. The participants wore a blinded continuous glucose monitoring device (Dexcom G6 Pro; Dexcom, Inc, San Diego, CA) for 10 days starting when they took the 50-g glucose challenge test. The primary outcome was a composite of adverse neonatal outcomes (large for gestational age, shoulder dystocia or neonatal injury, respiratory distress, need for intravenous glucose treatment for hypoglycemia, or fetal or neonatal death). The secondary neonatal outcomes included preterm birth, neonatal intensive care unit admission, hypoglycemia, mechanical ventilation or continuous positive airway pressure, hyperbilirubinemia, and hospital length of stay. The secondary maternal outcomes included weight gain during pregnancy, hypertensive disorders of pregnancy, induction of labor, cesarean delivery, and postpartum complications. Time within the target range (63-140 mg/dL), time above the target range (>140 mg/dL) expressed as a percentage of all continuous glucose monitoring readings, and mean glucose level were analyzed. The Youden index was used to choose the threshold of ≥10% for the time above the target range and association with adverse outcomes.

RESULTS

Of 136 participants recruited, data were available from 92 individuals (67.6%). The 2-step method diagnosed gestational diabetes mellitus in 2 individuals (2.2%). Continuous glucose monitoring indicated that 17 individuals (18.5%) had time above the target range of ≥10%. Individuals with time above the target range of ≥10% had a significantly higher likelihood of composite adverse neonatal outcomes than individuals with time above the target range of <10% (63% vs 18%; P=.001). Furthermore, compared with neonates born to individuals with time above the target range of <10%, neonates born to individuals with time above the target range of ≥10% had an increased likelihood for hypoglycemia (14.5% vs 47%; P=.009) and had a longer length of stay (2 vs 4 days; P=.03). No difference in maternal outcomes was noted between the groups.

CONCLUSION

In this prospective study of individuals undergoing gestational diabetes mellitus screening, a cutoff of the time above the target range of ≥10% using continuous glucose monitoring was associated with a higher rate of neonatal adverse outcomes. A randomized trial of continuous glucose monitoring vs 2-step screening for gestational diabetes mellitus to lower the rate of adverse outcomes is underway (identification number: NCT05430204).

Predicting Immunological Risk for Stage 1 and Stage 2 Diabetes Using a 1-Week CGM Home Test, Nocturnal Glucose Increments, and Standardized Liquid Mixed Meal Breakfasts, with Classification Enhanced by Machine Learning

Background: Predicting the risk for type 1 diabetes (T1D) is a significant challenge. We use a 1-week continuous glucose monitoring (CGM) home test to characterize differences in glycemia in at-risk healthy individuals based on autoantibody presence and develop a machine-learning technology for CGM-based islet autoantibody classification. Methods: Sixty healthy relatives of people with T1D with mean ± standard deviation age of 23.7 ± 10.7 years, HbA1c of 5.3% ± 0.3%, and body mass index of 23.8 ± 5.6 kg/m2 with zero (n = 21), one (n = 18), and ≥2 (n = 21) autoantibodies were enrolled in an National Institutes of Health TrialNet ancillary study. Participants wore a CGM for a week and consumed three standardized liquid mixed meals (SLMM) instead of three breakfasts. Glycemic outcomes were computed from weekly, overnight (12:00-06:00), and post-SLMM CGM traces, compared across groups, and used in four supervised machine-learning autoantibody status classifiers. Classifiers were evaluated through 10-fold cross-validation using the receiver operating characteristic area under the curve (AUC-ROC) to select the best classification model. Results: Among all computed glycemia metrics, only three were different across the autoantibodies groups: percent time >180 mg/dL (T180) weekly (P = 0.04), overnight CGM incremental AUC (P = 0.005), and T180 for 75 min post-SLMM CGM traces (P = 0.004). Once overnight and post-SLMM features are incorporated in machine-learning classifiers, a linear support vector machine model achieved the best performance of classifying autoantibody positive versus autoantibody negative participants with AUC-ROC ≥0.81. Conclusion: A new technology combining machine learning with a potentially self-administered 1-week CGM home test can help improve T1D risk detection without the need to visit a hospital or use a medical laboratory. Trial registration: ClinicalTrials.gov registration no. NCT02663661.

Personalized Digital Health Information to Substantiate Human-Delivered Exercise Support for Adults With Type 1 Diabetes

OBJECTIVE

Pilot-test personalized digital health information to substantiate human-delivered exercise support for adults with type 1 diabetes (T1D).

DESIGN

Single-group, 2-week baseline observation, then 10-week intervention with follow-up observation.

SETTING

Community-based sample participating remotely with physician oversight.

PARTICIPANTS

Volunteers aged 18 to 65 years with T1D screened for medical readiness for exercise intervention offerings. N = 20 enrolled, and N = 17 completed all outcomes with 88% to 91% biosensor adherence.

INTERVENTION

Feedback on personalized data from continuous glucose monitoring (CGM), its intersection with other ecological data sets (exercise, mood, and sleep), and other informational and motivational elements (exercise videos, text-based exercise coach, and self-monitoring diary).

MAIN OUTCOME MEASURES

Feasibility (use metrics and assessment completion), safety (mild and severe hypoglycemia, and diabetic ketoacidosis), acceptability (system usability scale, single items, and interview themes), and standard clinical and psychosocial assessments.

RESULTS

Participants increased exercise from a median of 0 (Interquartile range, 0-21) to 64 (20-129) minutes per week ( P = 0.001, d = 0.71) with no severe hypoglycemia or ketoacidosis. Body mass index increased (29.5 ± 5.1 to 29.8 ± 5.4 kg/m 2 , P = 0.02, d = 0.57). Highest satisfaction ratings were for CGM use (89%) and data on exercise and its intersection with CGM and sleep (94%). Satisfaction was primarily because of improved exercise management behavioral skills, although derived motivation was transient.

CONCLUSIONS

The intervention was feasible, safe, and acceptable. However, there is a need for more intensive, sustained support. Future interventions should perform analytics upon the digital health information and molecular biomarkers (eg, genomics) to make exercise support tools that are more personalized, automated, and intensive than our present offerings.

A narrative review of exercise participation among adults with prediabetes or type 2 diabetes: barriers and solutions

Type 2 diabetes (T2D) has been rising in prevalence over the past few decades in the US and worldwide. T2D contributes to significant morbidity and premature mortality, primarily due to cardiovascular disease (CVD). Exercise is a major cornerstone of therapy for T2D as a result of its positive effects on glycemic control, blood pressure, weight loss and cardiovascular risk as well as other measures of health. However, studies show that a majority of people with T2D do not exercise regularly. The reasons given as to why exercise goals are not met are varied and include physiological, psychological, social, cultural and environmental barriers to exercise. One potential cause of inactivity in people with T2D is impaired cardiorespiratory fitness, even in the absence of clinically evident complications. The exercise impairment, although present in both sexes, is greater in women than men with T2D. Women with T2D also experience greater perceived exertion with exercise than their counterparts without diabetes. These physiological barriers are in addition to constructed societal barriers including cultural expectations of bearing the burden of childrearing for women and in some cultures, having limited access to exercise because of additional cultural expectations. People at risk for and with diabetes more commonly experience unfavorable social determinants of health (SDOH) than people without diabetes, represented by neighborhood deprivation. Neighborhood deprivation measures lack of resources in an area influencing socioeconomic status including many SDOH such as income, housing conditions, living environment, education and employment. Higher indices of neighborhood deprivation have been associated with increased risk of all-cause, cardiovascular and cancer related mortality. Unfavorable SDOH is also associated with obesity and lower levels of physical activity. Ideally regular physical activity should be incorporated into all communities as part of a productive and healthy lifestyle. One potential solution to improve access to physical activity is designing and building environments with increased walkability, greenspace and safe recreational areas. Other potential solutions include the use of continuous glucose monitors as real-time feedback tools aimed to increase motivation for physical activity, counseling aimed at improving self-efficacy towards exercise and even acquiring a dog to increase walking time. In this narrative review, we aim to examine some traditional and novel barriers to exercise, as well as present evidence on novel interventions or solutions to overcome barriers to increase exercise and physical activity in all people with prediabetes and T2D.

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

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

Short-term use of CGM in youth onset type 2 diabetes is associated with behavioral modifications

Background

Continuous glucose monitoring (CGM) is beneficial to glycemic control in youth with type 1 diabetes (T1D) and adults with type 2 diabetes (T2D); however, studies in youth with T2D are limited.

Objective

Determine if 10-day trial CGM use in youth with T2D improves glycemic control and behavioral modifications.

Methods

Youth with T2D > 3 months, on insulin, with no prior CGM use were enrolled. Staff placed CGM and provided education. Participants received 5-day and 10-day follow-up phone calls to review CGM data, behavioral modifications, and adjust insulin doses as needed. We compared 5-day to 10-day TIR, and baseline to 3-6 month HbA1c via paired t-test.

Results

Participants (n=41) had median age of 16.2 y, were 61% female, 81% NH Black, median diabetes duration of 0.8 y, and baseline HbA1c of 10.3%. A majority had household income<$50,000 (81%) and parental education level of HS or less (73%). Average 5-day TIR 49% was similar to 10-day TIR 51% (p=0.62). There was no change in HbA1c after 3-6 months (10.2% v 10.3%, p=0.89). Nineteen participants completed full 10-day CGM use; of those, 84% wanted a CGM long-term. Adolescents reported behavioral changes including increased blood sugar checks, increased insulin administration and overall improved diabetes management.

Conclusion

Although 10-day CGM use did not impact short-term or long-term glycemic control in youth with T2D, most participants reported behavioral changes and wanted to continue using CGM. Future studies with longer use of CGM may clarify the potential impact of CGM in youth with T2D.

Discordance Between Glucose Management Indicator and Glycated Hemoglobin in People Without Diabetes

Background: In recent years, continuous glucose monitor (CGM) use is increasing in people without diabetes to promote healthy lifestyle. CGM metrics such as glucose management indicator (GMI), a statistical formula to estimate glycated hemoglobin (HbA1c) from sensor glucose, is commonly used to approximate HbA1c. This study was aimed to evaluate discordance between GMI and HbA1c in people without diabetes. Methods: Children and nonpregnant adults (age ≥6 years) without diabetes (laboratory HbA1c <5.7% and negative islet antibodies) were invited to participate in a multicenter prospective study aimed to evaluate glycemic profiles in nondiabetic individuals. Each participant wore a blinded Dexcom G6 for up to 10 days. GMI was calculated from mean sensor glucose and discordance between GMI and HbA1c was analyzed. Results: Of 201 screened participants, 153 participants (mean age 31.2 ± 21.0 years, 66.0% female, HbA1c 5.1% ± 0.3%) were included in the analysis. Mean GMI was 0.59% higher than laboratory HbA1c in participants without diabetes. The discordance between GMI and HbA1c of 0.4% or greater was 71% in participants without diabetes compared with 39% in the original GMI development cohort. Conclusion: GMI does not accurately estimate HbA1c in healthy people without diabetes. Clinical trial registration number is: NCT00717977.

Effectiveness of Non-Contact Dietary Coaching in Adults with Diabetes or Prediabetes Using a Continuous Glucose Monitoring Device: A Randomized Controlled Trial

We aimed to evaluate the effectiveness of dietary coaching and continuous glucose monitoring (CGM) in patients with diabetes or prediabetes to improve their behavioral skills and health outcomes. A randomized controlled study with pre- and post-testing was conducted. Data were collected between November 2020 and April 2021. Forty-five patients with diabetes or prediabetes who used a CGM device were enrolled and analyzed. Dietary education, individual coaching and group coaching were provided to participants in the experimental group for 4 weeks. After the intervention, the thigh circumference in men significantly differed between the two groups (z = -2.02, p = 0.044). For women, participants in the experimental group showed greater improvement in eating self-efficacy compared with those in the control group (z = -2.66, p = 0.008). Insomnia was negatively related to the change in eating self-efficacy (r = -0.35, p = 0.018) and increase in thigh circumference (r = -0.35, p = 0.017). Even if used within a short intervention period, non-contact dietary coaching programs can help enhance behavioral skills, such as eating self-efficacy and health outcomes, such as thigh circumference. Moreover, the changed variables can indirectly improve other health outcomes in patients with diabetes or prediabetes.

Continuous glucose monitoring for children with hypoglycaemia: Evidence in 2023

In 2023, childhood hypoglycaemia remains a major public health problem and significant risk factor for consequent adverse neurodevelopment. Irrespective of the underlying cause, key elements of clinical management include the detection, prediction and prevention of episodes of hypoglycaemia. These tasks are increasingly served by Continuous Glucose Monitoring (CGM) devices that measure subcutaneous glucose at near-continuous frequency. While the use of CGM in type 1 diabetes is well established, the evidence for widespread use in rare hypoglycaemia disorders is less than convincing. However, in the few years since our last review there have been multiple developments and increased user feedback, requiring a review of clinical application. Despite advances in device technology, point accuracy of CGM remains low for children with non-diabetes hypoglycaemia. Simple provision of CGM devices has not replicated the efficacy seen in those with diabetes and is yet to show benefit. Machine learning techniques for hypoglycaemia prevention have so far failed to demonstrate sufficient prediction accuracy for real world use even in those with diabetes. Furthermore, access to CGM globally is restricted by costs kept high by the commercially-driven speed of technical innovation. Nonetheless, the ability of CGM to digitally phenotype disease groups has led to a better understanding of natural history of disease, facilitated diagnoses and informed changes in clinical management. Large CGM datasets have prompted re-evaluation of hypoglycaemia incidence and facilitated improved trial design. Importantly, an individualised approach and focus on the behavioural determinants of hypoglycaemia has led to real world reduction in hypoglycaemia. In this state of the art review, we critically analyse the updated evidence for use of CGM in non-diabetic childhood hypoglycaemia disorders since 2020 and provide suggestions for qualified use.

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.

Continuous Glucose Monitoring: An Opportunity for Population-Based Diabetes Management

The increasing prevalence of prediabetes and diabetes in the United States poses a serious threat to the health of the population. Closely associated with obesity, hypertension, dyslipidemia, and cardiovascular disease, a diagnosis of diabetes or prediabetes carries with it life-altering demands. Critically important among these is the requirement for frequent glucose level checks-typically performed with blood obtained from a fingerstick. Innovative real-time continuous glucose monitoring (rtCGM) technology makes it possible for patients and their clinicians to receive continuous glucose level measurements around the clock without finger sticks. Accruing evidence shows that rtCGM is an effective tool for patients and their clinicians in managing diabetes (ie, maintaining glucose levels within the recommended target range) and in understanding how lifestyle behaviors directly influence glucose levels. In recent years, a number of large payer organizations (eg, private health insurers, employers) have incorporated rtCGM in their diabetes management programs as a means of addressing the dual challenge of achieving/maintaining control of glucose levels and preventing or delaying the onset of complications. Programmatic integrated approaches have been used successfully and cost-effectively for managing other chronic conditions. Incorporating rtCGM in similar integrated approaches in diabetes management may be of value in improving quality outcomes and reducing costs on a population level. The evidence supports broader adoption and continued study to evaluate models that incorporate the use of rtCGM.

Relationships Among Perception of Cognitive Function, Diabetes Self-Management, and Glucose Variability in Older Adults: A Mixed Methods Study

The aim of the current study was to explore relationships among perceived cognitive function, glucose variability, and self-management in older adults with type 2 diabetes mellitus (T2DM). A mixed methods design was used with data from: (a) questionnaires on perceived cognitive function and diabetes self-management; (b) continuous glucose monitoring (CGM) reports; and (c) semi-structured interviews. Thirty adults with T2DM (47% female; mean age = 68.5 [SD = 5.2] years) participated. Those who exercised more days per week had more stable glucose. Those who reported fewer days of diet adherence had more hypoglycemia. Participants who reported higher levels of memory dissatisfaction exhibited higher levels of glucose variability. Findings point to the potential of glucose variability as a target to reduce the effect of diabetes on cognitive function. Instruction in recognition of glucose patterns found via CGM can be integrated into self-management education to improve self-management and subsequent glucose control and cognitive function. [Research in Gerontological Nursing, xx(x), xx-xx.].

Personalised Nutritional Recommendations Based on Individual Post-Prandial Glycaemic Responses Improve Glycaemic Metrics and PROMs in Patients with Type 2 Diabetes: A Real-World Assessment

The recommended first-line therapy in type 2 diabetes (T2D) is lifestyle modification. In many patients, such interventions fail, and disease progresses inexorably to medication requirement. A potential reason for the failure of standard nutritional interventions is the use of generic dietary advice, with no personalisation to account for differences in the effect of food on blood glucose between different individuals. Another is the lack of instant feedback on the impact of dietary modification on glycaemic control, which supports sustained behaviour change. The use of continuous glucose monitoring (CGM) may help address both these shortcomings. We conducted an observational study to explore how personalised nutritional information impacts glycaemic control and patient-reported outcome measures (PROMs) of well-being. Free-living people with T2D eating their normal diet were provided with personalised nutritional recommendations by state-registered nutritionists based on the CGM-enabled analysis of individual post-prandial glycaemic responses (PPGRs). Participants demonstrated considerable inter-individual differences in PPGRs, reductions in post-prandial incremental area under the curve (iAUC) and daytime AUC, and improvements in energy levels, ability to concentrate, and other PROMs. These results suggest a role for personalised nutritional recommendations based on individual-level understanding of PPGRs in the non-pharmaceutical management of T2D.

Continuous Glucose Monitoring in Healthy Adults—Possible Applications in Health Care, Wellness, and Sports

Introduction: Continuous glucose monitoring (CGM) systems were primarily developed for patients with diabetes mellitus. However, these systems are increasingly being used by individuals who do not have diabetes mellitus. This mini review describes possible applications of CGM systems in healthy adults in health care, wellness, and sports. Results: CGM systems can be used for early detection of abnormal glucose regulation. Learning from CGM data how the intake of foods with different glycemic loads and physical activity affect glucose responses can be helpful in improving nutritional and/or physical activity behavior. Furthermore, states of stress that affect glucose dynamics could be made visible. Physical performance and/or regeneration can be improved as CGM systems can provide information on glucose values and dynamics that may help optimize nutritional strategies pre-, during, and post-exercise. Conclusions: CGM has a high potential for health benefits and self-optimization. More scientific studies are needed to improve the interpretation of CGM data. The interaction with other wearables and combined data collection and analysis in one single device would contribute to developing more precise recommendations for users.

The northeast glucose drift: Stratification of post-breakfast dysglycemia among predominantly Hispanic/Latino adults at-risk or with type 2 diabetes

BACKGROUND

There is minimal experience in continuous glucose monitoring (CGM) among underserved racial/ethnic minority populations with or at risk of type 2 diabetes (T2D), and therefore a lack of CGM-driven insight for these individuals. We analyzed breakfast-related CGM profiles of free-living, predominantly Hispanic/Latino individuals at-risk of T2D, with pre-T2D, or with non-insulin treated T2D.

METHODS

Starting February 2019, 119 participants in Santa Barbara, CA, USA, (93 female, 87% Hispanic/Latino [predominantly Mexican-American], age 54·4 [±12·1] years), stratified by HbA_1c levels into (i) at-risk of T2D, (ii) with pre-T2D, and (iii) with non-insulin treated T2D, wore blinded CGMs for two weeks. We compared valid CGM profiles from 106 of these participants representing glucose response to breakfast using four parameters.

FINDINGS

A "northeast drift" was observed in breakfast glucose responses comparing at-risk to pre-T2D to T2D participants. T2D participants had a significantly higher pre-breakfast glucose level, glucose rise, glucose incremental area under the curve (all p < 0·0001), and time to glucose peak (p < 0·05) compared to pre-T2D and at-risk participants. After adjusting for demographic and clinical covariates, pre-breakfast glucose and time to peak (p < 0·0001) were significantly associated with HbA_1c. The model predicted HbA_1c within (0·55 ± 0·67)% of true laboratory HbA_1c values.

INTERPRETATION

For predominantly Hispanic/Latino adults, the average two-week breakfast glucose response shows a progression of dysglycemia from at-risk of T2D to pre-T2D to T2D. CGM-based breakfast metrics have the potential to predict HbA_1c levels and monitor diabetes progression.

FUNDING

US Department of Agriculture (Grant #2018-33800-28404), a seed grant from the industry board fees of the NSF Engineering Research Center for Precise Advanced Technologies and Health Systems for Underserved Populations (PATHS-UP) (Award #1648451), and the Elsevier foundation.

Evolving Use of Continuous Glucose Monitoring Beyond Intensive Insulin Treatment

Numerous studies have demonstrated the clinical benefits of continuous glucose monitoring (CGM) use in individuals with type 1 diabetes and type 2 diabetes (T2D) who are treated with intensive insulin therapy. A growing body of evidence suggests that CGM use may also confer similar glycemic benefits in T2D individuals who are treated with less-intensive therapies. Investigators are also exploring the potential use of CGM as an aid in weight management. This article reviews the continuing evolution of CGM, focusing on how CGM may be used to improve glycemic control and promote adoption of desired health behaviors within broader T2D and prediabetes populations.

Continuous Glucose Monitoring (CGM) Is a Tool, Not a Reward: Unjustified Insurance Coverage Criteria Limit Access to CGM

Recent studies have demonstrated the clinical utility of continuous glucose monitoring (CGM) use in type 2 diabetes (T2D) patients who are treated with intensive insulin management. Large retrospective database analyses of T2D patients treated with less-intensive therapies have also shown that CGM use was associated with significant reductions in hemoglobin A1c levels and health resource utilization, including diabetes-related hospitalizations and emergency room care. Despite the growing body of evidence supporting CGM use in the broader T2D population, current eligibility criteria required by public and many private insurers are denying millions of individuals with T2D access to this valuable technology. In this article, we discuss an evidence-based rationale for modifying current eligibility requirements for CGM coverage.

LncRNA SOX2OT alleviates mesangial cell proliferation and fibrosis in diabetic nephropathy via Akt/mTOR-mediated autophagy

Background

Accumulating evidences have demonstrated that long non-coding RNAs (lncRNAs) are involved in the pathophysiology of diabetic nephropathy (DN). lncRNA SOX2OT plays an essential role in many diseases, including diabetes. Herein, we aim to investigate the underlying mechanism of lncRNA SOX2OT in DN pathogenesis.

Methods

Streptozotocin-induced DN mouse models and high glucose-induced mouse mesangial cells were constructed to examine the expression pattern of lncRNA SOX2OT. The activation of autophagy was evaluated using immunohistochemistry, immunofluorescence and western blot analysis, respectively. SOX2OT overexpressing plasmid was applied to further verify the functional role of SOX2OT in DN pathogenesis. CCK-8 and EDU assays were performed to the proliferation of mesangial cells. Additionally, rapamycin, the inhibitor of mTOR signaling, was used to further clarify whether SOX2OT controls DN development through Akt/mTOR pathway.

Results

lncRNA SOX2OT was markedly down-regulated both in streptozotocin-induced DN mice and high glucose-induced mouse mesangial cells. Moreover, overexpression of lncRNA SOX2OT was able to diminish the suppression of autophagy and alleviate DN-induced renal injury. Functionally, CCK-8 and EDU assays indicated that lncRNA SOX2OT overexpression significantly suppressed the proliferation and fibrosis of mesangial cells. Additionally, an obvious inhibition of Akt/mTOR was also observed with lncRNA SOX2OT overexpression, which was then further verified in vivo.

Conclusion

In summary, we demonstrated that lncRNA SOX2OT alleviates the pathogenesis of DN via regulating Akt/mTOR-mediated autophagy, which may provide a novel target for DN therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s10020-021-00310-6.

Intermittent Use of Continuous Glucose Monitoring: Expanding the Clinical Value of CGM

In addition to the continuous use, the intermittent use of continuous glucose monitoring (CGM) is an application of CGM, expanding the typical medical use cases. There are a variety of reasons and occasions that speak in favor of using CGM only for a limited time. To date, these circumstances have not been sufficiently discussed. In this article, we define discontinuous or intermittent CGM use, provide reasons for using it, and expand on the benefits and possibilities of using CGM on a temporary basis. We aim to draw attention to this important topic in the discussion of CGM use and give examples for a different method of CGM use. As well, we would like to foster the allocation of CGM to the right patient groups and indications, especially in cases of limited resources. From a global point of view, intermittent CGM use is more likely to occur than continuous use, primarily for economic reasons.

Effect of Exercise and Meals on Continuous Glucose Monitor Data in Healthy Individuals Without Diabetes

OBJECTIVE

The aim of these analyses was to characterize the effect of exercise and meals on glucose concentrations in healthy individuals without diabetes.

METHODS

Healthy individuals without diabetes (age ≥6 years) with nonobese body mass index were enrolled at 12 centers within the T1D Exchange Clinic Network. Participants wore a blinded Dexcom G6 for up to ten days. Throughout this sensor wear, participants completed a daily log indicating times and type of any exercise and start times of meals and snacks.

RESULTS

A total of 153 participants (age 7-80 years) were included in the analyses. Exercise induced a mean change of -15 ± 18 mg/dL from baseline to nadir sensor glucose level. Mean nadir glucose concentration during nights following exercise days was 82 ± 11 mg/dL compared with 85 ± 11 mg/dL during nights following nonexercise days (P = .05). Mean change from baseline to nadir sensor glucose level during aerobic exercise was -15 ± 18 and -9 ± 12 mg/dL for resistance exercise (P = .25). Overnight nadir glucose during nights following aerobic and resistance exercise was 83 ± 12 and 76 ± 14 mg/dL, respectively (P = .25). Overall mean peak postprandial glucose per participant increased from 93 ± 10 mg/dL premeal to 130 ± 13 mg/dL with an average time to peak glucose per participant of 97 ± 31 minutes. Consumption of alcohol on the day prior did not impact overnight mean or nadir glucose.

CONCLUSION

The present analysis provides important data characterizing the effect of exercise and meals on glucose in healthy individuals without diabetes. These data provide a repository to which future therapies, whether pharmacologic or technologic, can be compared.

Type 2 Diabetes and the Use of Real-Time Continuous Glucose Monitoring

The role of continuous glucose monitoring (CGM) in type 1 diabetes (T1D) is well established in improving glycemic control and reducing hypoglycemia. Type 2 diabetes (T2D) is more prevalent than T1D and management of T2D is more heterogeneous, requiring treatment ranging from lifestyle modification to oral medications to intensive insulin therapy. Recent randomized controlled trials in intensively insulin-treated T2D demonstrated the efficacy and safety of real-time CGM (rtCGM) in reducing glycated hemoglobin without increasing hypoglycemia. Although evidence is limited, early studies have indicated a role for rtCGM in selected patients with non-insulin requiring T2D to improve glycemic control and/or reduce hypoglycemia. Based on literature review, we summarized current data on the use of rtCGM in T2D management and provided future research direction to generate more evidence on the utility of CGM in this population.

A digital lifestyle behaviour change intervention for the prevention of type 2 diabetes: a qualitative study exploring intuitive engagement with real-time glucose and physical activity feedback

BACKGROUND

Mobile health technologies have advanced to now allow monitoring of the acute physiological responses to lifestyle behaviours. Our aim was to explore how people engaged with real-time feedback on their physical activity and glucose levels over several weeks.

METHODS

Semi-structured interviews with 26 participants (61.5% female, 56.6 years) at moderate-to-high risk of developing type 2 diabetes were conducted. Interviews were completed after participants took part in an intervention comprising a flash glucose monitor (Freestyle Libre) and a physical activity monitor (Fitbit Charge 2). Purposive sampling ensured representation of ages, genders and group allocations.

RESULTS

Inductive thematic analysis revealed how individuals intuitively used, interpreted and acted on feedback from wearable technologies. Six key themes emerged: triggers of engagement with the technologies, links between behaviour and health, lack of confidence, changes to movement behaviours, changes to diet and barriers to lifestyle behaviour change.

CONCLUSIONS

Our findings demonstrate that accessing behavioural and physiological feedback can increase self-awareness of how lifestyle impacts short-term health. Some participants noticed a link between the feedback presented by the two devices and changed their behaviour but many did not. Training and educational support, as well as efforts to optimize how feedback is presented to users, are needed to sustain engagement and behaviour change. Extensions of this work to involve people with diabetes are also warranted to explore whether behavioural and physiological feedback in parallel can encourage better diabetes self-management.

TRIAL REGISTRATION

ISRCTN Registry, ISRCTN17545949 , 12/05/2017, prospectively registered.

Continuous Glucose Monitoring With Low-Carbohydrate Diet Coaching in Adults With Prediabetes: Mixed Methods Pilot Study

BACKGROUND

Type 2 diabetes mellitus (T2DM) is preventable; however, few patients with prediabetes participate in prevention programs. The use of user-friendly continuous glucose monitors (CGMs) with low-carbohydrate diet coaching is a novel strategy to prevent T2DM.

OBJECTIVE

This study aims to determine the patient satisfaction and feasibility of an intervention combining CGM use and low-carbohydrate diet coaching in patients with prediabetes to drive dietary behavior change.

METHODS

We conducted a mixed methods, single-arm pilot and feasibility study at a suburban family medicine clinic. A total of 15 adults with prediabetes with hemoglobin A_1c (HbA_1c) levels between 5.7% and 6.4% and a BMI >30 kg/m² were recruited to participate. The intervention and assessments took place during 3 in-person study visits and 2 qualitative phone interviews (3 weeks and 6 months after the intervention). During visit 1, participants were asked to wear a CGM and complete a food intake and craving log for 10 days. During visit 2, the food intake and craving log along with the CGM results of the participants were reviewed and the participants received low-carbohydrate diet coaching, including learning about carbohydrates and personalized feedback. A second CGM sensor, with the ability to scan and record glucose trends, was placed, and the participants logged their food intake and cravings as they attempted to reduce their total carbohydrate intake (<100 g/day). During visit 3, the participants reviewed their CGM and log data. The primary outcome was satisfaction with the use of CGM and low-carbohydrate diet. The secondary outcomes included feasibility, weight, and HbA_1c change, and percentage of time spent in hyperglycemia. Changes in attitudes and risk perception of developing diabetes were also assessed.

RESULTS

The overall satisfaction rate of our intervention was 93%. The intervention induced a weight reduction of 1.4 lb (P=.02) and a reduction of HbA_1c levels by 0.71% (P<.001) since enrollment. Although not significantly, the percentage of time above glucose goal and average daily glucose levels decreased slightly during the study period. Qualitative interview themes indicated no major barriers to CGM use; the acceptance of a low-carbohydrate diet; and that CGMs helped to visualize the impact of carbohydrates on the body, driving dietary changes.

CONCLUSIONS

The use of CGMs and low-carbohydrate diet coaching to drive dietary changes in patients with prediabetes is feasible and acceptable to patients. This novel method merits further exploration, as the preliminary data indicate that combining CGM use with low-carbohydrate diet coaching drives dietary changes, which may ultimately prevent T2DM.

Resistance to data loss from the Freestyle Libre: impact on glucose variability indices and recommendations for data analysis

Like many wearables, flash glucose monitoring relies on user compliance and is subject to missing data. As recent research is beginning to utilise glucose technologies as behaviour change tools, it is important to understand whether missing data are tolerable. Complete Freestyle Libre data files were amputed to remove 1-6 h of data both at random and over mealtimes (breakfast, lunch, and dinner). Absolute percent errors (MAPE) and intraclass correlation coefficients (ICC) were calculated to evaluate agreement and reliability. Thirty-two (91%) participants provided at least 1 complete day (24 h) of data (age: 44.8 ± 8.6 years, female: 18 (56%); mean fasting glucose: 5.0 ± 0.6 mmol/L). Mean and continuous overall net glycaemic action (CONGA) (60 min) were robust to data loss (MAPE ≤3%). Larger errors were calculated for standard deviation, coefficient of variation (CV) and mean amplitude of glycaemic excursions (MAGE) at increasing missingness (MAPE: 2%-10%, 2%-9%, and 4%-18%, respectively). ICC decreased as missing data increased, with most indicating excellent reliability (>0.9) apart from certain MAGE ICCs, which indicated good reliability (0.84-0.9). Researchers and clinicians should be aware of the potential for larger errors when reporting standard deviation, CV, and MAGE at higher rates of data loss in nondiabetic populations. But where mean and CONGA are of interest, data loss is less of a concern. Novelty: As research now utilises flash glucose monitoring as behavioural change tools in nondiabetic populations, it is important to consider the influence of missing data. Glycaemic variability indices of mean and CONGA are robust to data loss, but standard deviation, CV, and MAGE are influenced at higher rates of missingness.

Continuous Glucose Monitoring As a Behavior Modification Tool

Real-time continuous glucose monitoring (CGM) use may lead to behavioral modifications in food selection and physical activity, but there are limited data on the utility of CGM in facilitating lifestyle changes. This article describes an 18-item survey developed to explore whether patients currently using CGM believe the technology has caused them to change their behavior.