Diet-induced differences in estimated plasma glucose concentrations in healthy, non-diabetic adults are detected by continuous glucose monitoring-a randomized crossover trial

Continuous glucose monitoring as an objective measure of meal consumption in individuals with binge-spectrum eating disorders: A proof-of-concept study

OBJECTIVE

Going extended periods of time without eating increases risk for binge eating and is a primary target of leading interventions for binge-spectrum eating disorders (B-EDs). However, existing treatments for B-EDs yield insufficient improvements in regular eating and subsequently, binge eating. These unsatisfactory clinical outcomes may result from limitations in assessment and promotion of regular eating in therapy. Detecting the absence of eating using passive sensing may improve clinical outcomes by facilitating more accurate monitoring of eating behaviours and powering just-in-time adaptive interventions. We developed an algorithm for detecting meal consumption (and extended periods without eating) using continuous glucose monitor (CGM) data and machine learning.

METHOD

Adults with B-EDs (N = 22) wore CGMs and reported eating episodes on self-monitoring surveys for 2 weeks. Random forest models were run on CGM data to distinguish between eating and non-eating episodes.

RESULTS

The optimal model distinguished eating and non-eating episodes with high accuracy (0.82), sensitivity (0.71), and specificity (0.94).

CONCLUSIONS

These findings suggest that meal consumption and extended periods without eating can be detected from CGM data with high accuracy among individuals with B-EDs, which may improve clinical efforts to target dietary restriction and improve the field's understanding of its antecedents and consequences.

Continuous Glucose Profiles in Healthy People With Fixed Meal Times and Under Everyday Life Conditions

BACKGROUND

The increased use of continuous glucose monitoring (CGM) and automated insulin delivery systems raises the question about therapeutic targets for glucose profiles in people with diabetes. This study aimed to assess averaged pre- and postprandial glucose profiles in people without diabetes to provide guidance for normal glucose patterns in clinical practice. For that, number and timing of meal intake were predefined.

MATERIAL AND METHODS

To assess glucose traces in 36 participants without diabetes (mean age = 23.7 ± 5.7 years), CGM was performed for up to 14 days, starting with a run-in phase (first 3 days, excluded from analysis) followed by 4 days with fixed meal times at 8:00 am, 1:00 pm, and 6:00 pm and the remaining 7 days spent under everyday life conditions. Data from two simultaneously worn CGM sensors were averaged and adjusted to capillary plasma-equivalent glucose values. Glucose data were evaluated through descriptive statistics.

RESULTS

Median glucose concentration on days with fixed meal times and under everyday life conditions was 95.0 mg/dL (91.6-99.1 mg/dL, interquartile range) and 98.1 mg/dL (93.7-100.8 mg/dL), respectively. On days with fixed meal times, mean premeal glucose was 92.8 ± 9.4 mg/dL, and mean peak postmeal glucose was 143.3 ± 23.5 mg/dL.

CONCLUSIONS

By defining the time of meal intake, a clear pattern of distinct postprandial glucose excursions in participants without diabetes could be demonstrated and analyzed. The presented glucose profiles might be helpful as an estimate for adequate clinical targets in people with diabetes.

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.

Individual Postprandial Glycemic Responses to Meal Types by Different Carbohydrate Levels and Their Associations with Glycemic Variability Using Continuous Glucose Monitoring

This study aimed to investigate individual postprandial glycemic responses (PPGRs) to meal types with varying carbohydrate levels and examine their associations with 14-day glycemic variability using continuous glucose monitoring (CGM) in young adults. In a two-week intervention study with 34 participants connected to CGM, four meal types and glucose 75 g were tested. PPGRs were recorded for up to 2 h with a 15 min interval after meals. Data-driven cluster analysis was used to group individual PPGRs for each meal type, and correlation analysis was performed of 14-day glycemic variability and control with related factors. Participants had a mean age of 22.5 years, with 22.8% being male. Four meal types were chosen according to carbohydrate levels. The mean glucose excursion for all meal types, except the fruit bowl, exhibited a similar curve with attenuation. Individuals classified as high responders for each meal type exhibited sustained peak glucose levels for a longer duration compared to low responders, especially in meals with carbohydrate contents above 50%. A meal with 45% carbohydrate content showed no correlation with either 14-day glycemic variability or control. Understanding the glycemic response to carbohydrate-rich meals and adopting a meal-based approach when planning diets are crucial to improving glycemic variability and control.

Patent analysis of digital sensors for continuous glucose monitoring

The high need for optimal diabetes management among an ever-increasing number of patients dictates the development and implementation of new digital sensors for continuous glucose monitoring. The purpose of this work is to systematize the global patenting trends of digital sensors for continuous glucose monitoring and analyze their effectiveness in controlling the treatment of diabetes patients of different ages and risk groups. The Lens database was used to build the patent landscape of sensors for continuous glucose monitoring. Retrospective analysis showed that the patenting of sensors for continuous glucose monitoring had positive trend over the analyzed period (2000-2022). Leading development companies are Dexcom Inc., Abbott Diabetes Care Inc., Medtronic Minimed Inc., Roche Diabetes Care Inc., Roche Diagnostics Operations Inc., Roche Diabetes Care Gmbh, and Ascensia Diabetes Care Holdings Ag, among others. Since 2006, a new approach has emerged where digital sensors are used for continuous glucose monitoring, and smartphones act as receivers for the data. Additionally, telemedicine communication is employed to facilitate this process. This opens up new opportunities for assessing the glycemic profile (glycemic curve information, quantitative assessment of the duration and amplitude of glucose fluctuations, and so on), which may contribute to improved diabetes management. A number of digital sensors for minimally invasive glucose monitoring are patented, have received FDA approval, and have been on the market for over 10 years. Their effectiveness in the clinic has been proven, and advantages and disadvantages have been clarified. Digital sensors offer a non-invasive option for monitoring blood glucose levels, providing an alternative to traditional invasive methods. This is particularly useful for patients with diabetes who require frequent monitoring, including before and after meals, during and after exercise, and in other scenarios where glucose levels can fluctuate. However, non-invasive glucose measurements can also benefit patients without diabetes, such as those following a dietary treatment plan, pregnant women, and individuals during fasting periods like Ramadan. The availability of non-invasive monitoring is especially valuable for patients in high-risk groups and across different age ranges. New world trends have been identified in the patenting of digital sensors for non-invasive glucose monitoring in interstitial skin fluid, saliva, sweat, tear fluid, and exhaled air. A number of non-invasive devices have received the CE mark approval, which confirms that the items meet European health, safety, and environmental protection standards (TensorTip Combo-Glucometer, Cnoga Medical Ltd.; SugarBEAT, Nemaura Medical; GlucoTrack, GlucoTrack Inc.), but are not FDA-approved yet. The above-mentioned sensors have characteristics that make them popular in the treatment of diabetes: they do not require implantation, do not cause an organism reaction to a foreign body, and are convenient to use. In the EU, in order to increase clinical safety and the level of transparency about medical devices, manufacturers must obtain certificates in accordance with Regulation (EU) 2017/745, taking into account the transition period. The development of systems, which include digital sensors for continuous glucose monitoring, mobile applications, and web platforms for professional analysis of glycemic control and implementation of unified glycemic assessment principles in mobile healthcare, represent promising approaches for controlling glycaemia in patients.

Low glycaemic index or low glycaemic load diets for people with overweight or obesity

BACKGROUND

The prevalence of obesity is increasing worldwide, yet nutritional management remains contentious. It has been suggested that low glycaemic index (GI) or low glycaemic load (GL) diets may stimulate greater weight loss than higher GI/GL diets or other weight reduction diets. The previous version of this review, published in 2007, found mainly short-term intervention studies. Since then, randomised controlled trials (RCTs) with longer-term follow-up have become available, warranting an update of this review.

OBJECTIVES

To assess the effects of low glycaemic index or low glycaemic load diets on weight loss in people with overweight or obesity.

SEARCH METHODS

We searched CENTRAL, MEDLINE, one other database, and two clinical trials registers from their inception to 25 May 2022. We did not apply any language restrictions.

SELECTION CRITERIA

We included RCTs with a minimum duration of eight weeks comparing low GI/GL diets to higher GI/GL diets or any other diets in people with overweight or obesity.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods. We conducted two main comparisons: low GI/GL diets versus higher GI/GL diets and low GI/GL diets versus any other diet. Our main outcomes included change in body weight and body mass index, adverse events, health-related quality of life, and mortality. We used GRADE to assess the certainty of the evidence for each outcome.

MAIN RESULTS

In this updated review, we included 10 studies (1210 participants); nine were newly-identified studies. We included only one study from the previous version of this review, following a revision of inclusion criteria. We listed five studies as 'awaiting classification' and one study as 'ongoing'. Of the 10 included studies, seven compared low GI/GL diets (233 participants) with higher GI/GL diets (222 participants) and three studies compared low GI/GL diets (379 participants) with any other diet (376 participants). One study included children (50 participants); one study included adults aged over 65 years (24 participants); the remaining studies included adults (1136 participants). The duration of the interventions varied from eight weeks to 18 months. All trials had an unclear or high risk of bias across several domains.  Low GI/GL diets versus higher GI/GL diets Low GI/GL diets probably result in little to no difference in change in body weight compared to higher GI/GL diets (mean difference (MD) -0.82 kg, 95% confidence interval (CI) -1.92 to 0.28; I2 = 52%; 7 studies, 403 participants; moderate-certainty evidence). Evidence from four studies reporting change in body mass index (BMI) indicated low GI/GL diets may result in little to no difference in change in BMI compared to higher GI/GL diets (MD -0.45 kg/m2, 95% CI -1.02 to 0.12; I2 = 22%; 186 participants; low-certainty evidence)at the end of the study periods. One study assessing participants' mood indicated that low GI/GL diets may improve mood compared to higher GI/GL diets, but the evidence is very uncertain (MD -3.5, 95% CI -9.33 to 2.33; 42 participants; very low-certainty evidence). Two studies assessing adverse events did not report any adverse events; we judged this outcome to have very low-certainty evidence. No studies reported on all-cause mortality.    For the secondary outcomes, low GI/GL diets may result in little to no difference in fat mass compared to higher GI/GL diets (MD -0.86 kg, 95% CI -1.52 to -0.20; I2 = 6%; 6 studies, 295 participants; low certainty-evidence). Similarly, low GI/GL diets may result in little to no difference in fasting blood glucose level compared to higher GI/GL diets (MD 0.12 mmol/L, 95% CI 0.03 to 0.21; I2 = 0%; 6 studies, 344 participants; low-certainty evidence).  Low GI/GL diets versus any other diet Low GI/GL diets probably result in little to no difference in change in body weight compared to other diets (MD -1.24 kg, 95% CI -2.82 to 0.34; I2 = 70%; 3 studies, 723 participants; moderate-certainty evidence). The evidence suggests that low GI/GL diets probably result in little to no difference in change in BMI compared to other diets (MD -0.30 kg in favour of low GI/GL diets, 95% CI -0.59 to -0.01; I2 = 0%; 2 studies, 650 participants; moderate-certainty evidence). Two adverse events were reported in one study: one was not related to the intervention, and the other, an eating disorder, may have been related to the intervention. Another study reported 11 adverse events, including hypoglycaemia following an oral glucose tolerance test. The same study reported seven serious adverse events, including kidney stones and diverticulitis. We judged this outcome to have low-certainty evidence. No studies reported on health-related quality of life or all-cause mortality. For the secondary outcomes, none of the studies reported on fat mass. Low GI/GL diets probably do not reduce fasting blood glucose level compared to other diets (MD 0.03 mmol/L, 95% CI -0.05 to 0.12; I2 = 0%; 3 studies, 732 participants; moderate-certainty evidence).  AUTHORS' CONCLUSIONS: The current evidence indicates there may be little to no difference for all main outcomes between low GI/GL diets versus higher GI/GL diets or any other diet. There is insufficient information to draw firm conclusions about the effect of low GI/GL diets on people with overweight or obesity. Most studies had a small sample size, with only a few participants in each comparison group. We rated the certainty of the evidence as moderate to very low. More well-designed and adequately-powered studies are needed. They should follow a standardised intervention protocol, adopt objective outcome measurement since blinding may be difficult to achieve, and make efforts to minimise loss to follow-up. Furthermore, studies in people from a wide range of ethnicities and with a wide range of dietary habits, as well as studies in low- and middle-income countries, are needed.

Impact of catheter ablation and subsequent recurrence of atrial fibrillation on glucose status in patients undergoing continuous glucose monitoring

Although glucose metabolism and atrial fibrillation (AF) have complex interrelationships, the impact of catheter ablation of AF on glucose status has not been well evaluated. Continuous glucose monitoring (CGM) with a FreeStyle Libre Pro (Abbott) was performed for 48 h pre-procedure, during the procedure, and for 72 h post-procedure in 58 non-diabetes mellitus (DM) patients with symptomatic AF and 20 patients with supraventricular or ventricular arrhythmias as a control group. All ablation procedures including pulmonary vein isolation were performed successfully. Glucose levels during procedures consistently increased in the AF and control groups (83.1 ± 16.1 to 110.0 ± 20.5 mg/dL and 83.3 ± 14.7 to 98.6 ± 16.3 mg/dL, respectively, P < 0.001 for both), and Δ glucose levels (max minus min/procedure) were greater in the AF group than control group (P < 0.001). There was a trend toward higher mean glucose levels at 72 h after the procedures compared with those before the procedures in both the AF and control groups (from 103.4 ± 15.6 to 106.1 ± 13.0 mg/dL, P = 0.063 and from 100.2 ± 17.1 to 102.9 ± 16.9 mg/dL, P = 0.052). An acute increase in glucose level at the time of early AF recurrence (N = 9, 15.5%) could be detected by simultaneous CGM and ECG monitoring (89.7 ± 18.0 to 108.3 ± 30.5 mg/dL, P = 0.001). In conclusion, although AF ablation caused a statistically significant increase in the glucose levels during the procedures, it did not result in a pathologically significant change after ablation in non-DM patients. Simultaneous post-procedure CGM and ECG monitoring alerted us to possible acute increases in glucose levels at the onset of AF recurrence.

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.

Advancing understanding of dietary and movement behaviours in an Asian population through real-time monitoring: Protocol of the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA)

Background

Modifiable risk factors for non-communicable diseases, including eating an unhealthy diet and being physically inactive, are influenced by complex and dynamic interactions between people and their social and physical environment. Therefore, understanding patterns and determinants of these risk factors as they occur in real life is essential to enable the design of precision public health interventions.

Objective

This paper describes the protocol for the Continuous Observations of Behavioural Risk Factors in Asia study (COBRA). The study uses real-time data capture methods to gain a comprehensive understanding of eating and movement behaviours, including how these differ by socio-demographic characteristics and are shaped by people's interaction with their social and physical environment.

Methods

COBRA is an observational study in free-living conditions. We will recruit 1500 adults aged 21-69 years from a large prospective cohort study. Real-time data capture methods will be used for nine consecutive days: an ecological momentary assessment app with a global positioning system enabled to collect location data, accelerometers to measure movement, and wearable sensors to monitor blood glucose levels. Participants receive six EMA surveys per day between 8 a.m. and 9.30 p.m. to capture information on behavioural risk factors including eating behaviours and diet composition movement behaviours (physical activity, sedentary behaviour, sleep), and related contextual factors. The second wave of ecological momentary assessment surveys with a global positioning system enabled will be sent 6 months later. Data will be analysed using generalised linear models to examine associations between behavioural risk factors and contextual determinants.

Discussion

Findings from this study will advance our understanding of dietary and movement behaviours as they occur in real-life and inform the development of personalised interventions to prevent chronic diseases.

Dynamics of glucose levels after Billroth I versus Roux-en-Y reconstruction in patients who undergo distal gastrectomy

PURPOSE

Recent studies have highlighted the importance of understanding trends in blood glucose levels. We examined the differences in blood glucose fluctuations according to the reconstruction method used after distal gastrectomy (DG) in patients with non-diabetic gastric cancer (GC).

METHODS

Sixty-one patients who underwent DG followed by either Billroth 1 (B1) or Roux-en-Y (R-Y) reconstruction were enrolled in this study. We used flash continuous glucose monitoring (CGM), a new technique for assessing glycemic control, to document the post-gastrectomy glycemic profile. Immediately before discharge, a CGM sensor was placed subcutaneously to evaluate blood glucose trends for 2 weeks.

RESULTS

The coefficient of variation of glucose levels was significantly higher in the Roux-en-Y (R-Y) group than in the Billroth I (B-I) group (p = 0.0260). The time below range (TBR, glucose levels of < 70 mg/dL) was also significantly higher in the R-Y group (p = 0.0115). Logistic regression analysis revealed that preoperative casual glucose levels of < 100 mg/dL and R-Y reconstruction were independently correlated with risk factors for a postoperative nocturnal TBR of > 30% (p = 0.006 and 0.042, respectively).

CONCLUSION

Our findings provide new insights into the post-DG reconstruction method selected for patients with non-diabetic gastric cancer by assessing postoperative blood glucose fluctuations using flash CGM.