Time in range: a new parameter to evaluate blood glucose control in patients with diabetes

Using continuous glucose monitoring to measure and improve quality metrics: Updates on the Healthcare Effectiveness Data and Information Set 2024 Glucose Management Indicator measure

Value-based diabetes care is a proactive approach to providing quality care to individuals with diabetes. This approach focuses on improving clinical outcomes rather than the volume of services provided. Implementation of value-based diabetes care requires an established set of standardized quality measures against which all stakeholders can assess and benchmark their performance. The National Committee for Quality Assurance recently added the Glucose Management Indicator to its Healthcare Effectiveness Data and Information Set. The Glucose Management Indicator can be used as a measure of glucose control. This article discusses the benefits of value-based care, the importance of diabetes quality measures, and how the rapidly increasing adoption of continuous glucose monitoring is impacting these measures while improving the lives of individuals with diabetes.

Blood Glucose Prediction from Nutrition Analytics in Type 1 Diabetes: A Review

INTRODUCTION

Type 1 Diabetes (T1D) affects over 9 million worldwide and necessitates meticulous self-management for blood glucose (BG) control. Utilizing BG prediction technology allows for increased BG control and a reduction in the diabetes burden caused by self-management requirements. This paper reviews BG prediction models in T1D, which include nutritional components.

METHOD

A systematic search, utilizing the PRISMA guidelines, identified articles focusing on BG prediction algorithms for T1D that incorporate nutritional variables. Eligible studies were screened and analyzed for model type, inclusion of additional aspects in the model, prediction horizon, patient population, inputs, and accuracy.

RESULTS

The study categorizes 138 blood glucose prediction models into data-driven (54%), physiological (14%), and hybrid (33%) types. Prediction horizons of ≤30 min are used in 36% of models, 31-60 min in 34%, 61-90 min in 11%, 91-120 min in 10%, and >120 min in 9%. Neural networks are the most used data-driven technique (47%), and simple carbohydrate intake is commonly included in models (data-driven: 72%, physiological: 52%, hybrid: 67%). Real or free-living data are predominantly used (83%).

CONCLUSION

The primary goal of blood glucose prediction in T1D is to enable informed decisions and maintain safe BG levels, considering the impact of all nutrients for meal planning and clinical relevance.

What Is the Tech Missing? Nutrition Reporting in Type 1 Diabetes

INTRODUCTION

Type 1 Diabetes (T1D) presents self-management challenges, requiring an additional 180 daily decisions to regulate blood glucose (BG) levels. Despite the potential, T1D-focused applications have a 43% attrition rate. This work delves into the willingness of people living with T1D (PwT1D) to use technology.

METHOD

An online questionnaire investigated the current practices for carbohydrate estimation, nutritional tracking, and attitudes towards technology engagement, along with hypothetical scenarios and preferences regarding technology use.

RESULTS

Thirty-nine responses were collected from PwT1D (n = 33) and caregivers (n = 6). Nutrition reporting preferences varied, with 50% favoring 'type and scroll' while 30% preferred meal photographing. Concerning the timing of reporting, 33% reported before meals, 55% after, and 12% at a later time. Improved Time in Range (TIR) was a strong motivator for app use, with 78% expressing readiness to adjust insulin doses based on app suggestions for optimizing TIR. Meal descriptions varied; a single word was used in 42% of cases, 23% used a simple description (i.e., "Sunday dinner"), 30% included portion sizes, and 8% provided full recipes.

CONCLUSION

PwT1D shows interest in using technology to reduce the diabetes burden when it leads to an improved TIR. For such technology to be ecologically valid, it needs to strike a balance between requiring minimal user input and providing significant data, such as meal tags, to ensure accurate blood glucose management without overwhelming users with reporting tasks.

Impact of the State of Emergency Declaration for Severe Acute Respiratory Syndrome Coronavirus-2 Pandemic Suppression on Individuals with Type 1 Diabetes Mellitus

Objective To examine the impact of lifestyle changes caused by the first emergency declaration issued in 2020 on glycemic control and body weight changes in Japanese individuals with type 1 diabetes mellitus. Methods This study included Japanese individuals with type 1 diabetes mellitus who visited Tokyo Women's Medical University Hospital between January 2019 and September 2020 (n=278). Seasonal changes in glycated hemoglobin (HbA1c) levels and the body mass index (BMI) were compared. A self-administered questionnaire regarding changes in treatment, diet, exercise, sleep, and telecommuting was used to assess lifestyle changes. Results Although HbA1c levels decreased from winter to summer in 2019 and 2020, the annual change was slightly but significantly greater in 2020 than in 2019. Seasonal changes in the BMI between 2019 and 2020 were also significantly different. An increase in the daily insulin dose, overall blood glucose level, diurnal change in blood glucose level, and food intake were significantly associated with increased HbA1c levels. Furthermore, HbA1c levels decreased with increasing moderate physical activity and sleep duration. The change in the BMI increased with increasing insulin dose, overall high blood glucose levels, and food intake. However, an increase in moderate physical activity was associated with a decrease in the BMI. HbA1c levels were significantly lower after the first emergency declaration in individuals with type 1 diabetes mellitus than that before the emergency declaration, even after accounting for seasonal variations. Conclusion Decreased HbA1c levels were associated with a decreased food intake, increased moderate exercise, and increased sleep duration during the state of emergency. The BMI remained relatively unchanged.

Advances of Transition Metal-Based Electrochemical Non-enzymatic Glucose Sensors for Glucose Analysis: A Review

Glucose concentration is a crucial parameter for assessing human health. Over recent years, non-enzymatic electrochemical glucose sensors have drawn considerable attention due to their substantial progress. This review explores the common mechanism behind the transition metal-based electrocatalytic oxidation of glucose molecules through classical electrocatalytic frameworks like the Pletcher model and the Hydrous Oxide-Adatom Mediator model (IHOAM), as well as the redox reactions at the transition metal centers. It further compiles the electrochemical characterization techniques, associated formulas, and their ensuing conclusions pertinent to transition metal-based non-enzymatic electrochemical glucose sensors. Subsequently, the review covers the latest advancements in the field of transition metal-based active materials and support materials used in non-enzymatic electrochemical glucose sensors in the last decade (2014-2023). Additionally, it presents a comprehensive classification of representative studies according to the active metal catalysts components involved.

AdultCarbQuiz for the Portuguese population with type 1 diabetes mellitus: translation, cultural adaptation and validation of its metabolic impact

AIMS

In type 1 diabetes mellitus (T1DM), functional insulin therapy, based on carbohydrate (CH) counting and individualized insulin-to-carbohydrate ratio, is essential to achieve an adequate metabolic control. However, to date, few tools have been validated to assess patients' knowledge about CH counting, with the AdultCarbQuiz questionnaire having proved to be a reliable method in an American cohort. The aim of this study was to translate, culturally adapt and validate the AdultCarbQuiz questionnaire for the Portuguese population.  METHODS: This was a cross-sectional study of patients with T1DM on functional insulin therapy through continuous subcutaneous insulin infusion (CSII). Prior to its application, the AdultCarbQuiz questionnaire was translated and culturally adapted to the Portuguese context. Statistical analyses include descriptive, correlation and intern consistency analysis using IBM® SPSS® Statistics, version 27.

RESULT

One hundred patients were included, 58% of female sex, with a mean age of 31.09 ± 10.77 years. Mean disease duration was 15.04 ± 9.23 years, and mean CSII usage time was 4.02 ± 3.90 years. The average value of glycated haemoglobin (HbA1c), time in range (TIR), time above range (TAR) and time below range was, respectively, 7.32 ± 0.87, 59.75 ± 14.13, 34.38 ± 15.40 and 5.75 ± 6.58%. The average score of the questionnaire was 30.86 points ± 3.58 points, considered high. The Kuder-Richardson 20 coefficient value was 0.63 for the total score, with a Spearman-Brown value for the half-split of 0.63. Individuals with lower HbA1c values scored significantly higher on knowledge about hypoglycaemia prevention and correction (r = - 0.269, p = 0.007) and on the total questionnaire score (r = - 0.205, p = 0.041). A higher TIR and a lower TAR were also associated with a higher total score (r = 0.274, p = 0.007 and r = - 0.274, p = 0.007, respectively).

CONCLUSIONS

In this study, the AdultCarbQuiz questionnaire, translated and culturally adapted to the Portuguese context, proved to be a useful tool in assessing knowledge about CH counting in patients with T1DM, allowing to optimize, individually, the therapeutic strategy in consultation.

Highlighting the effects of high-intensity interval training on the changes associated with hypertrophy, apoptosis, and histological proteins of the heart of old rats with type 2 diabetes

T2DM is known to cause disturbances in glucose homeostasis and negative changes in the heart muscle, while aging and diabetes are recognized risk factors for CVD. Given this, our study aims to investigate a method for controlling and managing CVDs induced by T2DM in elderly populations. To achieve this, we categorized 40 rats into 5 groups, including HAD (n = 8), HA (n = 8), AD (n = 8), AHT (n = 8), and ADT (n = 8). The exercise protocol consisted of eight weeks of HIIT (three sessions per week) performed at 90-95% of maximal speed. Following cardiac tissue extraction, we assessed the levels of IGF-1, PI3K, and AKT proteins using Western blot technique, and analyzed the histopathological variations of the heart tissue using H&E, Sudan Black, and Masson's trichrome tissue staining. The histological findings from our study demonstrated that T2DM had a significant impact on the development of pathological hypertrophy and fibrosis in the heart tissue of elderly individuals. However, HIIT not only effectively controlled pathological hypertrophy and fibrosis, but also induced physiological hypertrophy in the AHT and ADT groups compared to the HA and AD groups. Results from Sudan Black staining indicated that there was an increase in lipid droplet accumulation in the cytoplasm of cardiomyocytes and their nuclei in the HA and AD groups, while the accumulation of lipid droplets decreased significantly in the AHT and ADT groups. In both the AHT group and the ADT group, a single HIIT session led to a reduction in collagen fiber accumulation and fibrotic frameworks. Our research also revealed that diabetes caused a significant elevation in the levels of IGF-1, PI3K, and AKT proteins, but after eight weeks of HIIT, the levels of these proteins decreased significantly in the training groups. Overall, our findings suggest that HIIT may be a suitable non-pharmacological approach for improving histological and physiological changes in elderly individuals with T2DM. However, we recommend further research to examine the impact of HIIT training on both healthy and diseased elderly populations.

The Health Economics of Automated Insulin Delivery Systems and the Potential Use of Time in Range in Diabetes Modeling: A Narrative Review

Intensive therapy with exogenous insulin is the treatment of choice for individuals living with type 1 diabetes (T1D) and some with type 2 diabetes, alongside regular glucose monitoring. The development of systems allowing (semi-)automated insulin delivery (AID), by connecting glucose sensors with insulin pumps and algorithms, has revolutionized insulin therapy. Indeed, AID systems have demonstrated a proven impact on overall glucose control, as indicated by effects on glycated hemoglobin (HbA1c), risk of severe hypoglycemia, and quality of life measures. An alternative endpoint for glucose control that has arisen from the use of sensor-based continuous glucose monitoring is the time in range (TIR) measure, which offers an indication of overall glucose control, while adding information on the quality of control with regard to blood glucose level stability. A review of literature on the health-economic value of AID systems was conducted, with a focus placed on the growing place of TIR as an endpoint in studies involving AID systems. Results showed that the majority of economic evaluations of AID systems focused on individuals with T1D and found AID systems to be cost-effective. Most studies incorporated HbA1c, rather than TIR, as a clinical endpoint to determine treatment effects on glucose control and subsequent quality-adjusted life year (QALY) gains. Likely reasons for the choice of HbA1c as the chosen endpoint is the use of this metric in most validated and established economic models, as well as the limited publicly available evidence on appropriate methodologies for TIR data incorporation within conventional economic evaluations. Future studies could include the novel TIR metric in health-economic evaluations as an additional measure of treatment effects and subsequent QALY gains, to facilitate a holistic representation of the impact of AID systems on glycemic control. This would provide decision makers with robust evidence to inform future recommendations for health care interventions.

Detection of Hypoglycemia and Hyperglycemia Using Noninvasive Wearable Sensors: Electrocardiograms and Accelerometry

BACKGROUND

Monitoring glucose excursions is important in diabetes management. This can be achieved using continuous glucose monitors (CGMs). However, CGMs are expensive and invasive. Thus, alternative low-cost noninvasive wearable sensors capable of predicting glycemic excursions could be a game changer to manage diabetes.

METHODS

In this article, we explore two noninvasive sensor modalities, electrocardiograms (ECGs) and accelerometers, collected on five healthy participants over two weeks, to predict both hypoglycemic and hyperglycemic excursions. We extract 29 features encompassing heart rate variability features from the ECG, and time- and frequency-domain features from the accelerometer. We evaluated two machine learning approaches to predict glycemic excursions: a classification model and a regression model.

RESULTS

The best model for both hypoglycemia and hyperglycemia detection was the regression model based on ECG and accelerometer data, yielding 76% sensitivity and specificity for hypoglycemia and 79% sensitivity and specificity for hyperglycemia. This had an improvement of 5% in sensitivity and specificity for both hypoglycemia and hyperglycemia when compared with using ECG data alone.

CONCLUSIONS

Electrocardiogram is a promising alternative not only to detect hypoglycemia but also to predict hyperglycemia. Supplementing ECG data with contextual information from accelerometer data can improve glucose prediction.

Enhancement of Ambulatory Glucose Profile for Decision Assistance and Treatment Adjustments

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

To What Extent Is HbA1c Associated with Glycemic Variability in Patients with Type 1 Diabetes? A Retrospective, Noninterventional Study

BACKGROUND

Glycemic variability (GV) is a novel parameter used in evaluating the quality of diabetes management. Current guidelines recommend the use of GV indexes alongside the traditional parameter to evaluate glycemic control: hemoglobin A1c (HbA1c). This study aims to evaluate the extent to which HbA1c explains the GV phenomena in patients with Type 1 diabetes (T1DM).

METHODS

In 147 patients with T1DM, associations between HbA1c and several GV indexes were analyzed.

RESULTS

Patients with an HbA1c < 7% had a lower median standard deviation of glycemia (60 vs. 48; p < 0.001), a lower coefficient of variation (34.1 vs. 38.0; p < 0.001), and a significantly increased median time in range (78 vs. 58; p < 0.001). HbA1c was positively correlated with the coefficient of variation (r = 0.349; p < 0.001) and the standard deviation (r = 0.656; p < 0.001) but reversely correlated with a lower time in range (r = -0.637; p < 0.001).

CONCLUSIONS

HbA1c only partially explains the GV phenomena in patients with T1DM. The HbA1c value is associated more strongly with the time in range and standard deviation than with the coefficient of variation.

Acute Glycemic Variability and Early Outcomes After Cardiac Surgery: A Meta-Analysis

The influence of acute glycemic variability (GV) on early outcomes of patients after cardiac surgery remains not fully determined. We performed a systematic review and meta-analysis to evaluate the association between acute GV and in-hospital outcomes of patients after cardiac surgery. Relevant observational studies were obtained by search of electronic databases including Medline, Embase, Cochrane Library, and Web of Science. A randomized-effects model was selected to pool the data by incorporating the influence of potential heterogeneity. Nine cohort studies involving 16 411 patients after cardiac surgery were included in this meta-analysis. Pooled results showed that a high acute GV was associated with an increased risk of major adverse events (MAE) during hospitalization for patients after cardiac surgery [odds ratio [OR]: 1.29, 95% CI: 1.15 to 1.45, p<0.001, I22=38%]. Sensitivity analysis limited to studies of on-pump surgery and GV evaluated by coefficient of variation of blood glucose showed similar results. Subgroup analysis suggested that a high acute GV was related to an increased incidence of MAE in patients after coronary artery bypass graft, but not for those after isolated valvular surgery (p=0.04), and the association was weakened after adjustment of glycosylated hemoglobin (p=0.01). Moreover, a high acute GV was also related to an increased risk of in-hospital mortality (OR: 1.55, 95% CI: 1.15 to 2.09, p=0.004; I22=0%). A high acute GV may be associated with poor in-hospital outcomes in patients after cardiac surgery.

Analysis of the performances of various controllers adopted in the biomedical field for blood glucose regulation: a case study of the type-1 diabetes

Diabetes remains a critical global health concern that necessitates urgent attention. The contemporary clinical approach to closed-loop care, specifically tailored for insulin-dependent patients, aims to precisely monitor blood glucose levels while mitigating the risks of hyperglycaemia and hypoglycaemia due to erroneous insulin dosing. This study seeks to address this life-threatening issue by assessing and comparing the performance of different controllers to achieve quicker settling and convergence rates with reduced steady-state errors, particularly in scenarios involving meal interruptions. The methodology involves the detection of plasma blood glucose levels, delivery of precise insulin doses to the actuator through a control architecture, and subsequent administration of the calculated insulin dosage to patients based on the control signal. Glucose-insulin dynamics were modelled using kinetics and mass balance equations from the Bergman minimal model. The simulation results revealed that the PID controller exhibited superior performance, maintaining blood glucose concentration around the preferred threshold ∼98.8% of the time, with a standard deviation of 2.50. This was followed by RST with a success rate of 98.5% and standard deviation of 5.00, SPC with a success rate of 58% and standard deviation of 2.99, SFC with a success rate of 55% and standard deviation of 10.08, and finally LCFB with a rate of 10% and significantly higher standard deviation of 64.55.

Investigating the value of glucodensity analysis of continuous glucose monitoring data in type 1 diabetes: an exploratory analysis

Introduction

Continuous glucose monitoring (CGM) devices capture longitudinal data on interstitial glucose levels and are increasingly used to show the dynamics of diabetes metabolism. Given the complexity of CGM data, it is crucial to extract important patterns hidden in these data through efficient visualization and statistical analysis techniques.

Methods

In this paper, we adopted the concept of glucodensity, and using a subset of data from an ongoing clinical trial in pediatric individuals and young adults with new-onset type 1 diabetes, we performed a cluster analysis of glucodensities. We assessed the differences among the identified clusters using analysis of variance (ANOVA) with respect to residual pancreatic beta-cell function and some standard CGM-derived parameters such as time in range, time above range, and time below range.

Results

Distinct CGM data patterns were identified using cluster analysis based on glucodensities. Statistically significant differences were shown among the clusters with respect to baseline levels of pancreatic beta-cell function surrogate (C-peptide) and with respect to time in range and time above range.

Discussion

Our findings provide supportive evidence for the value of glucodensity in the analysis of CGM data. Some challenges in the modeling of CGM data include unbalanced data structure, missing observations, and many known and unknown confounders, which speaks to the importance of--and provides opportunities for--taking an approach integrating clinical, statistical, and data science expertise in the analysis of these data.

Relationship between acute glucose variability and cognitive decline in type 2 diabetes: A systematic review and meta-analysis

BACKGROUND

Cognitive decline is one of the most widespread chronic complications of diabetes, which occurs in more than half of the patients with type 2 diabetes (T2DM). Emerging evidences have suggested that glucose variability (GV) is associated with the pathogenesis of diabetic complications. However, the influence of acute GV on cognitive dysfunction in T2DM is still controversial. The aim of the study was to evaluate the association between acute GV and cognitive defect in T2DM, and provide a most recent and comprehensive summary of the evidences in this research field.

METHODS

PubMed, Cochrane library, EMBASE, Web of science, Sinomed, China National Knowledge Infrastructure (CNKI), and Wanfang were searched for articles that reported on the association between acute GV and cognitive impairment in T2DM.

RESULTS

9 eligible studies were included, with a total of 1263 patients with T2DM involved. Results showed that summary Fisher's z value was -0.23 [95%CI (-0.39, -0.06)], suggesting statistical significance (P = 0.006). Summary r value was -0.22 [95%CI (-0.37, -0.06)]. A lower cognitive performance was found in the subjects with greater glucose variation, which has statistical significance. Mean amplitude of glycemic excursions (MAGE) was associated with a higher risk of poor functional outcomes. Fisher's z value was -0.35 [95%CI (-0.43, -0.25)], indicating statistical significance (P = 0.011). Sensitivity analyses by omitting individual studies showed stability of the results.

CONCLUSIONS

Overall, higher acute GV is associated with an increased risk of cognitive impairment in patients with T2DM. Further studies should be required to determine whether targeted intervention of reducing acute GV could prevent cognitive decline.

Glucometrics in the first week of critical illness and its association with mortality

OBJECTIVE

Evaluation of glucometrics in the first week of ICU stay and its association with outcomes.

DESIGN

Prospective observational study.

SETTING

Mixed ICU of teaching hospital.

PATIENTS

Adults initiated on insulin infusion for 2 consecutive blood glucose (BG) readings ≥180mg/dL.

MAIN VARIABLES OF INTEREST

Glucometrics calculated from the BG of first week of admission: hyperglycemia (BG>180mg/dL) and hypoglycemia (BG<70mg/dL) episodes; median, standard deviation (SD) and coefficient of variation (CV) of BG, glycemic lability index (GLI), time in target BG range (TIR). Factors influencing glucometrics and the association of glucometrics to patient outcomes analyzed.

RESULTS

A total of 5762 BG measurements in 100 patients of median age 55 years included. Glucometrics: hyperglycemia: 2253 (39%), hypoglycemia: 28 (0.48%), median BG: 169mg/dL (162-178.75), SD 31mg/dL (26-38.75), CV 18.6% (17.1-22.5), GLI: 718.5 [(mg/dL)²/h]/week (540.5-1131.5) and TIR 57% (50-67). Diabetes and higher APACHE II score were associated with higher SD and CV, and lower TIR. On multivariate regression, diabetes (p=0.009) and APACHE II score (p=0.016) were independently associated with higher SD. Higher SD and CV were associated with less vasopressor-free days; lower TIR with more blood-stream infections (BSI). Patients with higher SD, CV and GLI had a higher 28-day mortality. On multivariate analysis, GLI alone was associated with a higher mortality (OR 2.99, p=0.04).

CONCLUSIONS

Glycemic lability in the first week in ICU patients receiving insulin infusion is associated with higher mortality. Lower TIR is associated with more blood stream infections.

A Systematic Review of Commercial Hybrid Closed-Loop Automated Insulin Delivery Systems

INTRODUCTION

Several different forms of automated insulin delivery systems (AID systems) have recently been developed and are now licensed for type 1 diabetes (T1D). We undertook a systematic review of reported trials and real-world studies for commercial hybrid closed-loop (HCL) systems.

METHODS

Pivotal, phase III and real-world studies using commercial HCL systems that are currently approved for use in type 1 diabetes were reviewed with a devised protocol using the Medline database.

RESULTS

Fifty-nine studies were included in the systematic review (19 for 670G; 8 for 780G; 11 for Control-IQ; 14 for CamAPS FX; 4 for Diabeloop; and 3 for Omnipod 5). Twenty were real-world studies, and 39 were trials or sub-analyses. Twenty-three studies, including 17 additional studies, related to psychosocial outcomes and were analysed separately.

CONCLUSIONS

These studies highlighted that HCL systems improve time In range (TIR) and arouse minimal concerns around severe hypoglycaemia. HCL systems are an effective and safe option for improving diabetes care. Real-world comparisons between systems and their effects on psychological outcomes require further study.

The impact of physical inactivity on glucose homeostasis when diet is adjusted to maintain energy balance in healthy, young males

BACKGROUND & AIMS

It is unclear if dietary adjustments to maintain energy balance during reduced physical activity can offset inactivity-induced reductions in insulin sensitivity and glucose disposal to produce normal daily glucose concentrations and meal responses. Therefore, the aim of the present study was to examine the impact of long-term physical inactivity (60 days of bed rest) on daily glycemia when in energy balance.

METHODS

Interstitial glucose concentrations were measured using Continuous Glucose Monitoring Systems (CGMS) for 5 days before and towards the end of bed rest in 20 healthy, young males (Age: 34 ± 8 years; BMI: 23.5 ± 1.8 kg/m2). Energy intake was reduced during bed rest to match energy expenditure, but the types of foods and timing of meals was maintained. Fasting venous glucose and insulin concentrations were determined, as well as the change in whole-body glucose disposal using a hyperinsulinemic-euglycemic clamp (HIEC).

RESULTS

Following long-term bed rest, fasting plasma insulin concentration increased 40% (p = 0.004) and glucose disposal during the HIEC decreased 24% (p < 0.001). Interstitial daily glucose total area under the curve (tAUC) from pre-to post-bed rest increased on average by 6% (p = 0.041), despite a 20 and 25% reduction in total caloric and carbohydrate intake, respectively. The nocturnal period (00:00-06:00) showed the greatest change to glycemia with glucose tAUC for this period increasing by 9% (p = 0.005). CGMS measures of daily glycemic variability (SD, J-Index, M-value and MAG) were not changed during bed rest.

CONCLUSIONS

Reduced physical activity (bed rest) increases glycemia even when daily energy intake is reduced to maintain energy balance. However, the disturbance to daily glucose homeostasis was much more modest than the reduced capacity to dispose of glucose, and glycemic variability was not negatively affected by bed rest, likely due to positive mitigating effects from the contemporaneous reduction in dietary energy and carbohydrate intake.

CLINICAL TRIALS RECORD

NCT03594799 (registered July 20, 2018) (https://clinicaltrials.gov/ct2/show/NCT03594799).

Use of Continuous Glucose Monitoring in Non-ICU Hospital Settings for People With Diabetes: A Scoping Review of Emerging Benefits and Issues

BACKGROUND

Evidence indicates that poor glycemic control is associated with increased morbidity and length of stay in hospital. There are a wide range of guidelines published, which seek to ensure safe and effective inpatient glycemic control in the hospital setting. However, the implementation of these protocols is limited in practice. In particular, the feasibility of "flash" and continuous glucose monitoring (CGM) remains untested on general wards.

METHOD

Scoping Review.

RESULTS

If used in the general ward hospital settings, CGM and flash glucose monitoring (FGM) systems could lead to improved glycemic control, decreased length of stay, and reduced risk of severe hypoglycemia or hyperglycemia. Potential problems include lack of experience with this technology and costs of sensors. Rapid analysis of glucose measurements can facilitate clinical decision making and therapy adjustment in the hospital setting. In addition, people with diabetes may be empowered to better self-manage their condition in hospital as they have direct access to their glucose data.

CONCLUSIONS

More studies are required in which the feasibility, benefits and limitations of FGM and CGM in non-intensive care unit hospital settings are elucidated. We need evidence on which types of hospital wards might benefit from the introduction of this technology and the contexts in which they are less useful. We also need to identify the types of people who are most likely to find FGM and CGM useful for self-management and for which populations they have the most benefit in terms of clinical outcomes and length of stay.

Effects of Alternate Insulin Pump Settings in Patients With Type 1 Diabetes During Ramadan: A Randomized Pilot Study

BACKGROUND

Various studies have evaluated the safety and efficacy of using insulin pumps during Ramadan; some of them demonstrated favorable outcomes in reducing hypoglycemia and hyperglycemia. However, there is no consensus on the recommendations for basal insulin adjustments and the utilization of technical features of insulin pumps to improve glycemic control.

OBJECTIVES

We aimed to investigate the effects of different insulin pump settings on time in range in patients with type 1 diabetes during Ramadan.

METHODS

In this randomized pilot study, 30 patients classified to have low to moderate risk for fasting were assigned to either a control group to receive basal insulin adjustments only or an intervention group to use the temporary basal rate and extended bolus features in addition to the basal insulin modifications. The percentage of time spent at different glucose ranges was measured by continuous glucose monitoring.

RESULTS

The percentage of time spent within target (70-180 mg/dL) increased significantly in the intervention group from 63.0 ± 10.7 to 76 ± 16.2% (mean difference, 27% points; P < .001). The percentage of time spent in hyperglycemia level 1 (>180 mg/dL) and level 2 (>250 mg/dL) met the criterion of significance, indicating that the intervention group spent less time in hyperglycemia. However, there was no significant difference in the percentage of time spent in hypoglycemia ranges.

CONCLUSIONS

Incorporating technological approaches of pump therapy with clinical practice guidelines could improve glycemic control during Ramadan.

Effects of accumulated versus continuous individualized exercise on postprandial glycemia in young adults with obesity

BACKGROUND

Elevated postprandial glucose (PPG) is an independent risk factor for cardiovascular disease. Post-meal exercise effectively reduces PPG concentrations. However, the effect of accumulated versus continuous post-meal exercise on PPG control remains unclear. This study aimed to investigate the effects of individualized accumulated or continuous exercise on PPG in young adults with obesity.

METHODS

Twenty young adults with obesity (11 males) completed three 4-h randomized crossover trials with 6-14-day washout periods: (1) sitting (SIT), (2) one 30-min walking bout (CONT), and (3) three 10-min walking bouts separated by 20-min resting (ACCU). Walking was initiated 20 min before individual PPG peak after breakfast, which was predetermined by continuous glucose monitoring. Blood samples were collected at 15-30 min intervals, and the 24-h glucose was monitored via continuous glucose monitoring.

RESULTS

The 4-h PPG incremental area under the curve (iAUC) was 12.1%±30.9% and 21.5%±21.5% smaller after CONT (P = 0.022) and ACCU (P < 0.001), respectively, than after SIT. PPG concentrations were lower during CONT at 30-60 min and during ACCU at 30-105 min after breakfast than during SIT (all P < 0.05). The 4-h plasma insulin and C-peptide iAUC, and mean amplitude of glycemic excursions were lower after CONT and ACCU than after SIT (all P < 0.05).

CONCLUSIONS

Both continuous and accumulated exercises reduced PPG, insulin, and C-peptide concentrations and improved glucose fluctuations. Accumulated exercise maintained lower PPG concentrations for a longer time than continuous exercise in young adults with obesity.

CLINICAL TRIAL INFORMATION

Clinical trial registration No. ChiCTR 2000035064, URL: http://www.chictr.org.cn/showproj.aspx?proj=56584; (registered July 29, 2020).HIGHLIGHTS Both continuous and accumulated walking lowered post-meal glucose, insulin and C-peptide levels and improved glucose fluctuation.Postprandial glucose was kept lower for a longer time in accumulated than continuous walking.Accumulated post-meal exercise (e.g. three 10-min bouts of walking) could be recommended as a feasible and practical alternative protocol for postprandial glucose control, especially for those who have difficulty performing sufficient exercise in one session.

STYLCONNECT Study: An Assessment of Automatic Data Collection Devices by People Living with Diabetes and Using an Insulin Pen

INTRODUCTION

The use of devices to connect insulin pens could facilitate management and improve glycaemic control in people with type 1 (PwT1D) and type 2 diabetes (PwT2D). However, their acceptance seems little studied. We conducted an online survey with the main objective of assessing the level of interest among insulin-treated people with diabetes (PwD) in a device connected to a disposable pen and secondary objectives of assessing the perceived benefits and important features expected of a connected device and identifying factors associated with interest scores.

METHODS

An ad-hoc questionnaire, validated by PwD, was used. Responses from 1798 PwD (975 PwT1D and 823 PwT2D) were analysed.

RESULTS

The mean interest rating was 7.4/10 (PwT1D: 7.2 vs PwT2D: 7.7; p < 0.001). PwD perceived that the device would make it easier to record their diabetes-related information (7.7/10) and keep all insulin and diabetes data in a single location (7.7/10). It was particularly important for PwD that this type of device could integrate data from glucose-measuring devices (7.8/10) and could set an alarm when all insulin in the body had been metabolised (7.7/10).

CONCLUSION

Our study highlighted PwD's strong interest in automating the collection of their insulin therapy data, with significantly more interest among PwT2D than PwT1D, and the importance of interoperability between glucose measurement devices and interchangeability between the different brands of insulin. More generally, for the first time and on a large scale, our study provided a greater understanding of the expectations of PwD regarding these devices.

Glycaemic control and novel technology management strategies in pregestational diabetes mellitus

Introduction

Pregestational diabetes (PGDM) is an increasingly common and complex condition that infers risk to both mother and infant. To prevent serious morbidity, strict glycaemic control is essential. The aim of this review is to review the glucose sensing and insulin delivering technologies currently available for women with PGDM.

Methods

We reviewed online databases for articles relating to technology use in pregnancy using a combination of keywords and MeSH headings. Relevant articles are included below.

Results

A number of technological advancements have improved care and outcomes for women with PGDM. Real time continuous glucose monitoring (rtCGM) offers clear advantages in terms of infants size and neonatal intensive care unit admissions; and further benefits are seen when combined with continuous subcutaneous insulin delivery (insulin pump) and algorithms which continuously adjust insulin levels to glucose targets (hybrid closed loop). Other advancements including flash or intermittent scanning CGM (isCGM) and stand-alone insulin pumps do not confer as many advantages for women and their infants, however they are increasingly used outside of pregnancy and many women enter pregnancy already using these devices.

Discussion

This article offers a discussion of the most commonly used technologies in pregnancy and evaluates their current and future roles.

Flash glucose monitoring system in patients with type 1 diabetes in healthcare center in Brazil: real world data from a short-term prospective study

Objective

To evaluate the alternate use of flash glucose monitoring (FGM) with self-monitoring blood glucose (SMBG), in patients with type 1 diabetes (T1D).

Materials and methods

Two weeks of open FGM (P2), both preceded (P1) and followed by 2 weeks (P3) of SMBG with a blinded FGM system. Mean absolute relative difference (MARD) was calculated by (|FGMi - SMBGi|) / SMBGi, where it was a paired data sample.

Results

In total, 34 patients were evaluated. Time in range (TIR) did not change between P1 and P2. In 12 patients (35.3%), TIR increased from 40% at P1 to 52% at P2 (p = 0.002) and in 22 (64.7%), TIR decreased or did not change. FGM use resulted in decreased % time spent in hypoglycemia (<70 mg/dL) (6.5% vs. 5.0%; p = 0.005), increased % time spent in hyperglycemia (>180 mg/dL) (44.5% to 51%; p = 0.046) with no significant change in % TIR. The proportion of patients who reached sensor-estimated glycated hemoglobin (eA1c) < 7% decreased from 23.5% at P1 to 12.9% at P2, p = 0.028. For the whole sample, the MARD between the two methods was 15.5% (95% CI 14.5-16.6%). For normal glucose range, hyperglycemic levels and hypoglycemic levels MARD were 16.0% (95% CI 15.0-17.0%), 13.3% (95% CI 11.5-15.2%) and 23.4% [95% CI 20.5-26.3%)], respectively.

Conclusion

FGM after usual SMBG decreased the % time spent in hypoglycemia concomitant with an undesired increase in % time spent in hyperglycemia. Lower accuracy of FGM regarding hypoglycemia levels could result in overcorrection of hypoglycemia.

Continuous glucose monitoring (CGM) satisfaction and its effect on mental health and glycemic control in adults with type 1 diabetes

Background and aim

A continuous glucose monitoring (CGM) helps the user stay continuously informed about blood glucose levels and reach the right target range. This study aimed to compare glycemic control and mental health of adults with type 1 diabetes with or without CGM and to examine their experiences using it.

Methods

Patients were included in the survey, whether or not they had used a CGM. Standardized questionnaires were used to assess mental health, problems with disease management, hypoglycemia attitudes and behavior, as well as glucose monitoring satisfaction.

Results

277 people participated in the study. CGM users (61.3%) had a more favorable glycemic control than those who were not. No differences were observed between the 2 groups in mental health and in response to hypoglycemic events; however, users reported more disease-related problems. CGM users reported they felt more open and free about diabetes, however, the pain and skin irritation caused by the device was disturbing and it was difficult to cope emotionally with the constant thought and worrying about diabetes.

Conclusions

CGM did not show clear satisfaction among users, however, less fear of hypoglycemia, fewer depression symptomology and improved glycemic control indicate better clinical status, which is one of the most important goals of disease management.

Intelligent Control with Artificial Neural Networks for Automated Insulin Delivery Systems

Type 1 diabetes mellitus is a disease that affects millions of people around the world. Recent progress in embedded devices has allowed the development of artificial pancreas that can pump insulin subcutaneously to automatically regulate blood glucose levels in diabetic patients. In this work, a Lyapunov-based intelligent controller using artificial neural networks is proposed for application in automated insulin delivery systems. The adoption of an adaptive radial basis function network within the control scheme allows regulation of blood glucose levels without the need for a dynamic model of the system. The proposed model-free approach does not require the patient to inform when they are going to have a meal and is able to deal with inter- and intrapatient variability. To ensure safe operating conditions, the stability of the control law is rigorously addressed through a Lyapunov-like analysis. In silico analysis using virtual patients are provided to demonstrate the effectiveness of the proposed control scheme, showing its ability to maintain normoglycemia in patients with type 1 diabetes mellitus. Three different scenarios were considered: one long- and two short-term simulation studies. In the short-term analyses, 20 virtual patients were simulated for a period of 7 days, with and without prior basal therapy, while in the long-term simulation, 1 virtual patient was assessed over 63 days. The results show that the proposed approach was able to guarantee a time in the range above 95% for the target glycemia in all scenarios studied, which is in fact well above the desirable 70%. Even in the long-term analysis, the intelligent control scheme was able to keep blood glucose metrics within clinical care standards: mean blood glucose of 119.59 mg/dL with standard deviation of 32.02 mg/dL and coefficient of variation of 26.78%, all below the respective reference values.

Comparative efficacy and complications of long-acting and intermediate-acting insulin regimens for adults with type 1 diabetes: an individual patient data network meta-analysis

OBJECTIVE

To examine the comparative efficacy and complications of long-acting and intermediate-acting insulin for different patient characteristics for type 1 diabetes mellitus (T1DM).

DESIGN

Systematic review and individual patient data (IPD) network meta-analysis (NMA).

DATA SOURCES

MEDLINE, EMBASE and the Cochrane Central Register of Controlled Trials were searched through June 2015.

ELIGIBILITY CRITERIA

Randomised controlled trials (RCTs) on adults with T1DM assessing glycosylated haemoglobin (A1c) and severe hypoglycaemia in long-acting and intermediate-acting insulin regimens.

DATA EXTRACTION AND SYNTHESIS

We requested IPD from authors and funders. When IPD were not available, we used aggregate data. We conducted a random-effects model, and specifically a one-stage IPD-NMA for those studies providing IPD and a two-stage IPD-NMA to incorporate those studies not providing IPD.

RESULTS

We included 28 RCTs plus one companion report, after screening 6680 titles/abstracts and 205 full-text articles. Of the 28 RCTs, 27 studies provided data for the NMA with 7394 participants, of which 12 RCTs had IPD on 4943 participants. The IPD-NMA for A1c suggested that glargine once daily (mean difference [MD]=-0.31, 95% confidence interval [CI]: -0.48 to -0.14) and detemir once daily (MD=-0.25, 95% CI: -0.41 to -0.09) were superior to neutral protamine Hagedorn (NPH) once daily. NPH once/two times per day improved A1c compared with NPH once daily (MD=-0.30, 95% CI: -0.50 to -0.11). Results regarding complications in severe hypoglycaemia should be considered with great caution due to inconsistency in the evidence network. Accounting for missing data, there was no evidence of inconsistency and long-acting insulin regimens ranked higher regarding reducing severe hypoglycaemia compared with intermediate-acting insulin regimens (two-stage NMA: glargine two times per day SUCRA (Surface Under the Cumulative Ranking curve)=89%, detemir once daily SUCRA=77%; one-stage NMA: detemir once daily/two times per day SUCRA=85%). Using multiple imputations and IPD only, complications in severe hypoglycaemia increased with diabetes-related comorbidities (regression coefficient: 1.03, 95% CI: 1.02 to 1.03).

CONCLUSIONS

Long-acting insulin regimens reduced A1c compared with intermediate-acting insulin regimens and were associated with lower severe hypoglycaemia. Of the observed differences, only glargine once daily achieved a clinically significant reduction of 0.30%. Results should be interpreted with caution due to very low quality of evidence.

PROSPERO REGISTRATION NUMBER

CRD42015023511.

Effect of divergent continuous glucose monitoring technologies on glycaemic control in type 1 diabetes mellitus: A systematic review and meta-analysis of randomised controlled trials

AIMS

We aimed to conduct a systematic review and meta-analysis of randomised controlled clinical trials (RCTs) assessing separately and together the effect of the three distinct categories of continuous glucose monitoring (CGM) systems (adjunctive, non-adjunctive and intermittently-scanned CGM [isCGM]), compared with traditional capillary glucose monitoring, on HbA1c and CGM metrics.

METHODS

PubMed, Web of Science, Scopus and Cochrane Central register of clinical trials were searched. Inclusion criteria were as follows: randomised controlled trials; participants with type 1 diabetes of any age and insulin regimen; investigating CGM and isCGM compared with traditional capillary glucose monitoring; and reporting glycaemic outcomes of HbA1c and/or time-in-range (TIR). Glycaemic outcomes were extracted post-intervention and expressed as mean differences and 95%CIs between treatment and comparator groups. Results were pooled using a random-effects meta-analysis. Risk of bias was assessed using the Cochrane Rob2 tool.

RESULTS

This systematic review was conducted between January and April 2021; it included 22 RCTs (15 adjunctive, 5 non-adjunctive, and 2 isCGM)). The overall analysis of the pooled three categories showed a statistically significant absolute improvement in HbA1c percentage points (mean difference (95% CI): -0.22% [-0.31 to -0.14], I²  = 79%) for intervention compared with comparator and was strongest for adjunctive CGM (-0.26% [-0.36, -0.16]). Overall TIR (absolute change) increased by 5.4% (3.5 to 7.2), I²  = 71% for CGM intervention compared with comparator and was strongest with non-adjunctive CGM (6.0% [2.3, 9.7]).

CONCLUSIONS

For individuals with T1D, use of CGM was beneficial for impacting glycaemic outcomes including HbA1c, TIR and time-below-range (TBR). Glycaemic improvement appeared greater for TIR for newer non-adjunctive CGM technology.

A Reinforcement Learning Based System for Blood Glucose Control without Carbohydrate Estimation in Type 1 Diabetes: In Silico Validation

Type 1 Diabetes (T1D) is a chronic autoimmune disease, which requires the use of exogenous insulin for glucose regulation. In current hybrid closed-loop systems, meal entry is manual which adds cognitive burden to the persons living with T1D. In this study, we proposed a control system based on Proximal Policy Optimisation (PPO) that controls both basal and bolus insulin infusion and only requires meal announcement, thus eliminating the need for carbohydrate estimation. We evaluated the system on a challenging meal scenario, using an open-source simulator based on the UVA/Padova 2008 model and achieved a mean Time in Range value of 65% for the adult subject cohort, while maintaining a moderate hypoglycemic and hyperglycemic risk profile. The approach shows promise and welcomes further research towards the translation to a real-life artificial pancreas. Clinical relevance- This was an in-silico analysis towards the development of an autonomous artificial pancreas system for glucose control. The proposed system show promise in eliminating the need for estimating the carbohydrate content in meals.

Efficacy of once-weekly tirzepatide versus once-daily insulin degludec on glycaemic control measured by continuous glucose monitoring in adults with type 2 diabetes (SURPASS-3 CGM): a substudy of the randomised, open-label, parallel-group, phase 3 SURPASS-3 trial

BACKGROUND

Tirzepatide is a novel dual glucose-dependent insulinotropic polypeptide (GIP) and GLP-1 receptor agonist under development for the treatment of type 2 diabetes. In this study, we used continuous glucose monitoring (CGM) to compare the 24 h glucose profile for participants given tirzepatide compared with those given insulin degludec.

METHODS

This substudy of the open-label, parallel-group, phase 3 SURPASS-3 trial, was done at 45 sites across six countries (Hungary, Poland, Romania, Spain, Ukraine, and the USA). Eligible participants in the main study were adults with type 2 diabetes, a baseline HbA_1c of 7·0-10·5% (53-91 mmol/mol), and a BMI of 25 kg/m² or more, who were insulin-naive, and treated with metformin alone or in combination with a SGLT2 inhibitor for at least 3 months before screening. Participants in the main study were randomly assigned (1:1:1:1) to receive once-weekly subcutaneous injection of tirzepatide 5 mg, 10 mg, or 15 mg, or once-daily subcutaneous injection of titrated insulin degludec (100 U/mL), using an interactive web-response system. Participants were stratified by country, HbA_1c concentration, and concomitant oral antihyperglycaemic medication. A subset of these patients with a normal wake-sleep cycle were enrolled into this substudy, and interstitial glucose values were collected by CGM for approximately 7 days at baseline, 24 weeks, and 52 weeks. The primary outcome was to compare pooled participants assigned to 10 mg and 15 mg tirzepatide versus insulin degludec for the proportion of time that CGM values were in the tight target range (71-140 mg/dL) at 52 weeks, assessed in all randomly assigned participants who received at least one dose of study drug and had an evaluable CGM session at either baseline or after baseline. The secondary outcomes were to compare tirzepatide (5 mg, 10 mg, and 15 mg) versus insulin degludec for the proportion and duration of time in tight target range at 24 and 52 weeks. This was a substudy of the trial registered with ClinicalTrials.gov, NCT03882970, and is complete.

FINDINGS

From April 1 to Nov 27, 2019, 313 participants were screened for eligibility, 243 of whom were enrolled in CGM substudy (tirzepatide 5 mg, n=64; tirzepatide 10 mg, n=51; tirzepatide 15 mg, n=73; and insulin degludec, n=55). Patients given once-weekly tirzepatide (pooled 10 mg and 15 mg groups) had a greater proportion of time in tight target range compared with patients given insulin degludec (estimated treatment difference 25% [95% CI 16-33]; p<0·0001). Participants assigned to tirzepatide spent significantly more time in tight target range at 52 weeks compared with those assigned to insulin degludec (5 mg 12% [1-22], p=0·031; 10 mg 24% [13-35], p<0·0001; and 15 mg 25% [14-35], p<0·0001). Participants assigned to tirzepatide 10 mg and 15 mg, but not to tirzepatide 5 mg, spent significantly more time in tight target range at 24 weeks compared with insulin degludec (10 mg 19% [8-30], p=0·0008; 15 mg 21% [11-31], p<0·0001).

INTERPRETATION

Once-weekly treatment with tirzepatide showed superior glycaemic control measured using CGM compared with insulin degludec in participants with type 2 diabetes on metformin, with or without a SGLT2 inhibitor. These new data provide additional evidence to the effect of tirzepatide and potential for achieving glycaemic targets without increase of hypoglycaemic risk compared with a basal insulin.

FUNDING

Eli Lilly and Company.

CunO/Au heterostructure dendrimer anchored on Cu foam as dual functional catalytic nanozyme for glucose sensing by enzyme mimic cascade reaction

Multifunctional catalytic performance plays a crucial role in bio-applications through the diversity and durability of artificial nanozymes. An effective synergy with sufficient accessible active sites and high specific surface area is a challenge for composite catalysts, especially to avoid uncontrollable aggregation and structural instability. Here, we fabricated a Cu_nO/Au heterostructure dendrimer on copper foam (Cu_nO/Au HD/CF) as dual functional catalytic nanozyme to achieve enzyme mimic cascade reactions for efficient colorimetric analysis. A highly porous CF skeleton-based CuO nanowire array (CuO NWA) with a large specific surface area supported an efficient load capacity to assemble sufficient Cu_nO/Au HD by electrodeposition. The bimetallic Au-Cu nanozyme successfully achieved an oxidase-like and peroxidase-like cascade catalysis by a target-responsive sensing mechanism. Due to the confirmed catalytic performance of selectivity, anti-interference ability, and reproducibility, a Cu_nO/Au HD/CF-based quantitative analytical method was developed for glucose detection with a wide linear range and considerable detection limit of 8.4 μM. The robust nonenzymatic catalytic strategy for colorimetric detection not only confirmed the dual functional catalytic activity of Cu_nO/Au HD/CF, but also showed great potential for applications in clinical diagnostics and biochemical analysis.

Expert Opinion: Optimum Clinical Approach to Combination-Use of SGLT2i + DPP4i in the Indian Diabetes Setting

The Asian-Indian phenotype of type 2 diabetes mellitus is uniquely characterized for cardio-metabolic risk. In the context of implementing patient-centric holistic cardio-metabolic risk management as a priority, the choice of various combinations of antidiabetic agents should be individualized. Combined therapy with two classes of antidiabetic agents, namely, dipeptidyl peptidase 4 inhibitors and sodium-glucose co-transporter-2 inhibitors, target several pathophysiological pathways. The wide-ranging clinical outcomes associated with this combination, including improvement of glycemia and adiposity, reduction of metabolic and vascular risk, safety, and simplicity for sustainable compliance, are extremely relevant to the Asian Indian patient population living with T2DM. In this review we describe the available evidence in detail and present a rational practical guidance for the optimum clinical use of this combination in this patient population.

Gradient variability coefficient: a novel method for assessing glycemic variability and risk of hypoglycemia

OBJECTIVE

Despite the clinical importance of glycemic variability and hypoglycemia, thus far, there is no consensus on the optimum method for assessing glycemic variability and risk of hypoglycemia simultaneously.

RESEARCH DESIGN AND METHODS

A novel metric, the gradient variability coefficient (GVC), was proposed for characterizing glycemic variability and risk of hypoglycemia. A total of 208 daily records of CGM encompassing 104 patients with T1DM and 2380 daily records from 1190 patients with T2DM were obtained in our study. Simulated CGM waveforms were used to assess the ability of GVC and other metrics to capture the amplitude and frequency of glucose fluctuations. In addition, the association between GVC and the risk of hypoglycemia was evaluated by receiver operating characteristic (ROC) curve.

RESULTS

The results of simulated CGM waveforms indicated that, compared with the widely used metrics of glycemic variability including standard deviation of sensor glucose (SD), coefficient of variation (CV), and mean amplitude of glycemic excursion (MAGE), GVC could reflect both the amplitude and frequency of glucose oscillations. In addition, the area under the curve (AUC) of ROC was 0.827 in T1DM and 0.873 in T2DM, indicating good performance in predicting hypoglycemia.

CONCLUSIONS

The proposed GVC might be a clinically useful tool in characterizing glycemic variability and the assessment of hypoglycemia risk in patients with diabetes.

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.

The role of continuous glucose monitoring in pregnancy

The risks associated with diabetes in pregnancy include congenital anomalies, stillbirth and miscarriage, and correlate with glycaemia. The optimisation of diabetes during pregnancy is therefore both challenging and essential. Technology has revolutionised how clinicians and patients manage diabetes. This review article focuses on the role of continuous glucose monitoring (CGM) in pregnancy, assessing the evidence available and providing an update on current guidance.

The Gut Microbiome of Adults With Type 1 Diabetes and Its Association With the Host Glycemic Control

OBJECTIVE

Previous studies have demonstrated an association between gut microbiota composition and type 1 diabetes (T1D) pathogenesis. However, little is known about the composition and function of the gut microbiome in adults with longstanding T1D or its association with host glycemic control.

RESEARCH DESIGN AND METHODS

We performed a metagenomic analysis of the gut microbiome obtained from fecal samples of 74 adults with T1D, 14.6 ± 9.6 years following diagnosis, and compared their microbial composition and function to 296 age-matched healthy control subjects (1:4 ratio). We further analyzed the association between microbial taxa and indices of glycemic control derived from continuous glucose monitoring measurements and blood tests and constructed a prediction model that solely takes microbiome features as input to evaluate the discriminative power of microbial composition for distinguishing individuals with T1D from control subjects.

RESULTS

Adults with T1D had a distinct microbial signature that separated them from control subjects when using prediction algorithms on held-out subjects (area under the receiver operating characteristic curve = 0.89 ± 0.03). Linear discriminant analysis showed several bacterial species with significantly higher scores in T1D, including Prevotella copri and Eubacterium siraeum, and species with higher scores in control subjects, including Firmicutes bacterium and Faecalibacterium prausnitzii (P < 0.05, false discovery rate corrected for all). On the functional level, several metabolic pathways were significantly lower in adults with T1D. Several bacterial taxa and metabolic pathways were associated with the host's glycemic control.

CONCLUSIONS

We identified a distinct gut microbial signature in adults with longstanding T1D and associations between microbial taxa, metabolic pathways, and glycemic control indices. Additional mechanistic studies are needed to identify the role of these bacteria for potential therapeutic strategies.

Efficacy of Flash Glucose Monitoring in Type 1 and Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomised Controlled Trials

Objective

Flash glucose monitoring (FlashGM) is a sensor-based technology that displays glucose readings and trends to people with diabetes. In this meta-analysis, we assessed the effect of FlashGM on glycaemic outcomes including HbA1c, time in range, frequency of hypoglycaemic episodes and time in hypo/hyperglycaemia compared to self-monitoring of blood glucose, using data from randomised controlled trials.

Methods

A systematic search was conducted on MEDLINE, EMBASE and CENTRAL for articles published between 2014 and 2021. We selected randomised controlled trials comparing flash glucose monitoring to self-monitoring of blood glucose that reported change in HbA1c and at least one other glycaemic outcome in adults with type 1 or type 2 diabetes. Two independent reviewers extracted data from each study using a piloted form. Meta-analyses using a random-effects model was conducted to obtain a pooled estimate of the treatment effect. Heterogeneity was assessed using forest plots and the I2 statistic.

Results

We identified 5 randomised controlled trials lasting 10 – 24 weeks and involving 719 participants. Flash glucose monitoring did not lead to a significant reduction in HbA1c. However, it resulted in increased time in range (mean difference 1.16 hr, 95% CI 0.13 to 2.19, I2 = 71.7%) and decreased frequency of hypoglycaemic episodes (mean difference -0.28 episodes per 24 hours, 95% CI -0.53 to -0.04, I2 = 71.4%).

Conclusions

Flash glucose monitoring did not lead to a significant reduction in HbA1c compared to self-monitoring of blood glucose, however, it improved glycaemic management through increased time in range and decreased frequency of hypoglycaemic episodes.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, identifier PROSPERO (CRD42020165688).

A prospective multicentre open label study to assess effect of Teneligliptin on glycemic control through parameters of time in range (TIR) Metric using continuous glucose monitoring (TOP-TIR study)

BACKGROUND AND AIMS

Continuous glucose monitoring (CGM) has been effective in assessing glycemic variability in diabetic patients. This study aims at assessing the effect of Teneligliptin using ambulatory glucose profile (AGP) indicators.

METHODS

A prospective, multicentre, open label study enrolling 59 type 2 diabetes patients between 18 and 65 years age was done between November 2020-May 2021. Patients were administered Teneligliptin 20 mg once daily, in addition to Metformin. The study included pre-treatment and two post-treatment phases. The data on time in range (TIR) and other AGP indicators of glycemic variability were obtained on each patient in all the three study phases and analysed to understand the effect of Teneligliptin on glycemic variability. Safety evaluation was done based on vital and biochemical parameters.

RESULTS

The percent TIR in post-treatment phase I was significantly higher than the pre-treatment phase (p < 0.0001), and was maintained till the end of phase II (p = 0.037). There was significant lowering of time above range (≥180 mg/dL) in the phase I (p = 0.003), which was maintained in phase II (p = 0.043), suggesting better control over hyperglycemic state. The reduction in mean glucose level in phase I and II was also significant compared to baseline (p = 0.003 and p = 0.023 respectively). The glucose variability percent and glucose management indicator also showed significant lowering in both the phases.

CONCLUSIONS

Teneligliptin addition to patients uncontrolled on Metformin monotherapy significantly reduced glycemic variability, as well showed significant glycemic improvement. Since this study was a single arm study, a comparative study with other DPP-4 inhibitors is needed.

Time-in-range and frequency of continuous glucose monitoring: Recommendations for South Asia

BACKGROUND AND AIM

The prevalence of diabetes is on its rise and South Asia bears a huge burden. Several factors such as heterogeneity in genetics, socio-economic factors, diet, and sedentary behavior contribute to the heightened risk of developing diabetes, its rapid progression, and the development of complications in this region. Even though there have been considerable advances in glucose monitoring technologies, diabetes treatments and therapeutics, glycemic control in South Asia remains suboptimal. The successful implementation of treatment interventions and metrics for the attainment of glycemic goals depends on appropriate guidelines that accord with the characteristics of the diabetes population.

METHOD

The data were collected from studies published for more than the last ten years in the electronic databases PubMed and Google Scholar on the various challenges in the assessment and achievement of recommended TIR targets in the SA population using the keywords: Blood glucose, TIR, TAR, TBR, HbA1c, hypoglycemia, CGM, Gestational diabetes mellitus (GDM), and diabetes.

RESULTS

The objective of this recommendation is to discuss the limitations in considering the IC-TIR Expert panel recommendations targets and to propose some modifications in the lower limit of TIR in older/high-risk population, upper limit of TAR, and flexibility in the percentage of time spent in TAR for pregnant women (GDM, T2DM) for the South Asian population.

CONCLUSION

The review sheds insights into some of the major concerns in implementing the IC-TIR recommendations in South Asian population where the prevalence of diabetes and its complications are significantly higher and modifications to the existing guidelines for use in routine clinical practice.

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.

Case Report: Off-Label Liraglutide Use in Children With Wolfram Syndrome Type 1: Extensive Characterization of Four Patients

Aims: Wolfram syndrome type 1 is a rare recessive monogenic form of insulin-dependent diabetes mellitus with progressive neurodegeneration, poor prognosis, and no cure. Based on preclinical evidence we hypothesized that liraglutide, a glucagon-like peptide-1 receptor agonist, may be repurposed for the off-label treatment of Wolfram Syndrome type 1. We initiated an off-label treatment to investigate the safety, tolerability, and efficacy of liraglutide in pediatric patients with Wolfram Syndrome type 1. Methods: Pediatric patients with genetically confirmed Wolfram Syndrome type 1 were offered off-label treatment approved by The Regional Network Coordination Center for Rare Diseases, Pharmacological Research IRCCS Mario Negri, and the internal ethics committee. Four patients were enrolled; none refused nor were excluded or lost during follow-up. Liraglutide was administered as a daily subcutaneous injection. Starting dose was 0.3 mg/day. The dose was progressively increased as tolerated, up to the maximum dose of 1.8 mg/day. The primary outcome was evaluating the safety, tolerability, and efficacy of liraglutide in Wolfram Syndrome type 1 patients. Secondary endpoints were stabilization or improvement of C-peptide secretion as assessed by the mixed meal tolerance test. Exploratory endpoints were stabilization of neurological and neuro-ophthalmological degeneration, assessed by optical coherence tomography, electroretinogram, visual evoked potentials, and magnetic resonance imaging. Results: Four patients aged between 10 and 14 years at baseline were treated with liraglutide for 8-27 months. Liraglutide was well-tolerated: all patients reached and maintained the maximum dose, and none withdrew from the study. Only minor transient gastrointestinal symptoms were reported. No alterations in pancreatic enzymes, calcitonin, or thyroid hormones were observed. At the latest follow-up, the C-peptide area under the curve ranged from 81 to 171% of baseline. Time in range improved in two patients. Neuro-ophthalmological and neurophysiological disease parameters remained stable at the latest follow-up. Conclusions: We report preliminary data on the safety, tolerability, and efficacy of liraglutide in four pediatric patients with Wolfram Syndrome type 1. The apparent benefits both in terms of residual C-peptide secretion and neuro-ophthalmological disease progression warrant further studies on the repurposing of glucagon-like peptide-1 receptor agonists as disease-modifying agents for Wolfram Syndrome type 1.

Design of clinical trials to assess diabetes treatment: Minimum duration of continuous glucose monitoring data to estimate time-in-ranges with the desired precision

AIM

To compute the uncertainty of time-in-ranges, such as time in range (TIR), time in tight range (TITR), time below range (TBR) and time above range (TAR), to evaluate glucose control and to determine the minimum duration of a trial to achieve the desired precision.

MATERIALS AND METHODS

Four formulas for the aforementioned time-in-ranges were obtained by estimating the equation's parameters on a training set extracted from study A (226 subjects, ~180 days, 5-minute Dexcom G4 Platinum sensor). The formulas were then validated on the remaining data. We also illustrate how to adjust the parameters for sensors with different sampling rates. Finally, we used study B (45 subjects, ~365 days, 15-minute Abbott Freestyle Libre sensor) to further validate our results.

RESULTS

Our approach was effective in predicting the uncertainty when time-in-ranges are estimated using n days of continuous glucose monitoring (CGM), matching the variability observed in the data. As an example, monitoring a population with TIR = 70%, TITR = 50%, TBR = 5% and TAR = 25% for 30 days warrants a precision of ±3.50%, ±3.68%, ±1.33% and ±3.66%, respectively.

CONCLUSIONS

The presented approach can be used to both compute the uncertainty of time-in-ranges and determine the minimum duration of a trial to achieve the desired precision. An online tool to facilitate its implementation is made freely available to the clinical investigator.

Effect of Nutritional Habits on the Glycemic Response to Different Carbohydrate Diet in Children with Type 1 Diabetes Mellitus

Unhealthy eating habits are associated with obesity, metabolic syndrome, and increased insulin resistance in young patients with type 1 diabetes mellitus (T1DM), and may impact the possible benefit from dietary interventions on glycaemic control. This study determines how nutritional patterns influence the quality of dietary intervention with a 30% or 50% carbohydrate diet in terms of glycaemic control measured with continuous glucose monitoring (CGM). Eating habits were obtained with a frequency-of-consumption questionnaire (FFQ-6) before the diet assessment. Altogether, we collected CGM and FFQ-6 data from 30 children (16 boys and 14 girls aged 10-17 years) with T1DM subjected to two consecutive 3-day nutritional plans. From these, 23 patients met the CGM data quality criteria for further analysis. Furthermore, high accuracy achieved in training (95.65%) and V-fold cross-validation (81.67%) suggest a significant impact of food habits in response to introduced nutritional changes. Patients who consumed more vegetables or grains (>4 times per day), more wheat products (>once per day), fewer fats (<1.5 times per day), and ranked fruit juice as the most common selection in the drinks category achieved glycaemic control more often after the introduction of a 30% carbohydrate diet, as opposed to those with different dietary patterns, whose glycaemic control was negatively impacted after switching to this diet. Additionally, the 50% carbohydrate diet was safe for all patients in the context of glycaemic control.

Non-invasive Monitoring of Three Glucose Ranges Based On ECG By Using DBSCAN-CNN

Autonomic nervous system (ANS) can maintain homeostasis through the coordination of different organs including heart. The change of blood glucose (BG) level can stimulate the ANS, which will lead to the variation of Electrocardiogram (ECG). Considering that the monitoring of different BG ranges is significant for diabetes care, in this paper, an ECG-based technique was proposed to achieve non-invasive monitoring with three BG ranges: low glucose level, moderate glucose level, and high glucose level. For this purpose, multiple experiments that included fasting tests and oral glucose tolerance tests were conducted, and the ECG signals from 21 adults were recorded continuously. Furthermore, an approach of fusing density-based spatial clustering of applications with noise and convolution neural networks (DBSCAN-CNN) was presented for ECG preprocessing of outliers and classification of BG ranges based ECG. Also, ECG's important information, which was related to different BG ranges, was graphically visualized. The result showed that the percentages of accurate classification were 87.94% in low glucose level, 69.36% in moderate glucose level, and 86.39% in high glucose level. Moreover, the visualization results revealed that the highlights of ECG for the different BG ranges were different. In addition, the sensitivity of prediabetes/diabetes screening based on ECG was up to 98.48%, and the specificity was 76.75%. Therefore, we conclude that the proposed approach for BG range monitoring and prediabetes/diabetes screening has potentials in practical applications.

Improved Glycemic Control and Variability: Application of Healthy Ingredients in Asian Staples

A reduction in carbohydrate intake and low-carbohydrate diets are often advocated to prevent and manage diabetes. However, limiting or eliminating carbohydrates may not be a long-term sustainable and maintainable approach for everyone. Alternatively, diet strategies to modulate glycemia can focus on the glycemic index (GI) of foods and glycemic load (GL) of meals. To assess the effect of a reduction in glycemic load of a 24 h diet by incorporating innovative functional ingredients (β-glucan, isomaltulose) and alternative low GI Asian staples (noodles, rice)on glycemic control and variability, twelve Chinese men (Age: 27.0 ± 5.1 years; BMI:21.6 ± 1.8kg/m²) followed two isocaloric, typically Asian, 24h diets with either a reduced glycemic load (LGL) or high glycemic load (HGL) in a randomized, single-blind, controlled, cross-over design. Test meals included breakfast, lunch, snack and dinner and the daily GL was reduced by 37% in the LGL diet. Continuous glucose monitoring provided 24 h glycemic excursion and variability parameters: incremental area under the curve (iAUC), max glucose concentration (Max), max glucose range, glucose standard deviation (SD), and mean amplitude of glycemic excursion (MAGE), time in range (TIR). Over 24h, the LGL diet resulted in a decrease in glucose Max (8.12 vs. 6.90 mmol/L; p = 0.0024), glucose range (3.78 vs. 2.21 mmol/L; p = 0.0005), glucose SD (0.78 vs. 0.43 mmol/L; p = 0.0002), mean amplitude of glycemic excursion (2.109 vs. 1.008; p < 0.0001), and increase in 4.5-6.5mmol/L TIR (82.2 vs. 94.6%; p = 0.009), compared to the HGL diet. The glucose iAUC, MAX, range and SD improved during the 2 h post-prandial window of each LGL meal, and this effect was more pronounced later in the day. The current results validate the dietary strategy of incorporating innovative functional ingredients (β-glucan, isomaltulose) and replacing Asian staples with alternative low GI carbohydrate sources to reduce daily glycemic load to improve glycemic control and variability as a viable alternative to the reduction in carbohydrate intake alone. These observations provide substantial public health support to encourage the consumption of staples of low GI/GL to reduce glucose levels and glycemic variability. Furthermore, there is growing evidence that the role of chrononutrition, as reported in this paper, requires further examination and should be considered as an important addition to the understanding of glucose homeostasis variation throughout the day.

Effectiveness of the freestyle libre 2 flash glucose monitoring system on diabetes-self-management practices and glycemic parameters among patients with type 1 diabetes using insulin pump

AIMS

To determine the effectiveness of Freestyle Libre 2 (FSL2) on diabetes-self-management (DSM) practices and glycemic parameters among patients with type 1 diabetes (T1D) using insulin pump.

METHODS

This prospective study was performed among 47 patients with T1D (13-21yrs) who self-tested their glucose levels by the conventional finger-prick method using blood glucose meters (BGM). Data related to glycemic profile i.e., mean time in range (TIR), mean time above range (TAR) mean time below range (TBR), mean glucose level, hemoglobin A1c (HbA1c), total daily dose of insulin (TDDI), frequency of glucose monitoring and DSM responses were collected at baseline and 12 weeks.

RESULTS

The mean TIR was 59.8 ± 12.6%, TAR 32.7 ± 11.6%, TBR 7.5 ± 4.3%, mean glycemic variability, standard deviation 63.2 ± 12.5 mg/dL, and the coefficient of variation 41.3 ± 11.4% at 12 weeks. At baseline, the HbA1c level was 8.3%, and at 12 weeks, it dropped to 7.9% (p = 0.064). Baseline glucose monitoring frequency through BGM was 2.4/day; however, after the patients employed the FSL2, a higher degree of frequency of glucose monitoring was evident at 12 weeks as 8.2/day (p < 0.001). Significant improvements were observed in all the DSM subscales at 12 weeks.

CONCLUSION

Using FSL2 was found to raise the patients' DSM levels and improved metabolic control.

Modeling postmortem ethanol production by C. albicans: Experimental study and multivariate evaluation

In previous research, we modeled the ethanol production by certain bacteria under controlled experimental conditions in an attempt to quantify the production of microbial postmortem ethanol in cases where other alcohols were co-detected. This contribution on the modeling of postmortem ethanol production by Candida albicans is complementary to these previous studies. Τhis work aimed to study ethanol, higher alcohols (1-propanol, isobutanol, 2-methyl-1-butanol and 3-methyl-1-butanol), and 1-butanol production by Candida albicans: (i) in different culture media (Brain Heart Infusion, BHI and, Sabouraud Dextrose Broth, SDB), (ii) under mixed aerobic/anaerobic or strict anaerobic conditions, and (iii) at different temperatures (37 °C, 25 °C and, 4 °C), and develop simple mathematical models, resulted from fungal cultures at 25 °C, to predict the microbially produced ethanol in correlation with the other alcohols. The applicability of the models was tested in the C. albicans cultures in BHI and SDB media at 37 °C, in denatured human blood at 25 °C, acidic and neutral with different concentrations of additional glucose, in acidic denatured blood diluted with dextrose solution and in blood from autopsy cases. The received results indicated that the C. albicans models could apply in cases where yeasts have been activated in blood with elevated glucose levels. Overall, the in vitro ethanol production by C. albicans in blood depended on temperature, time, glucose (or carbohydrate) content, pH of the medium and endogenous changes in the medium composition through time. Our results showed that methyl-butanol is the most significant indicator of fungal ethanol production, followed by the equally important isobutanol and 1-propanol in qualitative and quantitative terms.