International Consensus on Use of Continuous Glucose Monitoring

The Glucose Management Indicator: Time to Change Course?

Laboratory measurement of hemoglobin A1c (HbA1c) has, for decades, been the standard approach to monitoring glucose control in people with diabetes. Continuous glucose monitoring (CGM) is a revolutionary technology that can also aid in the monitoring of glucose control. However, there is uncertainty in how best to use CGM technology and its resulting data to improve control of glucose and prevent complications of diabetes. The glucose management indicator, or GMI, is an equation used to estimate HbA1c based on CGM mean glucose. GMI was originally proposed to simplify and aid in the interpretation of CGM data and is now provided on all standard summary reports (i.e., average glucose profiles) produced by different CGM manufacturers. This Perspective demonstrates that GMI performs poorly as an estimate of HbA1c and suggests that GMI is a concept that has outlived its usefulness, and it argues that it is preferable to use CGM mean glucose rather than converting glucose to GMI or an estimate of HbA1c. Leaving mean glucose in its raw form is simple and reinforces that glucose and HbA1c are distinct. To reduce patient and provider confusion and optimize glycemic management, mean CGM glucose, not GMI, should be used as a complement to laboratory HbA1c testing in patients using CGM systems.

Glucagon-like Peptide-1 analogues and delipidation of coronary atheroma in statin-treated type 2 diabetic patients with coronary artery disease: The prespecified sub-analysis of the OPTIMAL randomized clinical trial

Background and aims

Randomized clinical trials have demonstrated the ability of glucagon-like peptide-1 analogues (GLP-1RAs) to reduce atherosclerotic cardiovascular disease events in patients with type 2 diabetes (T2D). How GLP-1RAs modulate diabetic atherosclerosis remains to be determined yet.

Methods

The OPTIMAL study was a prospective randomized controlled study to compare the efficacy of 48-week continuous glucose monitoring- and HbA1c-guided glycemic control on near infrared spectroscopty (NIRS)/intravascular ultrasound (IVUS)-derived plaque measures in 94 statin-treated patients with T2D (jRCT1052180152, UMIN000036721). Of these, 78 patients with evaluable serial NIRS/IVUS images were analyzed to compare plaque measures between those treated with (n = 16) and without GLP-1RAs (n = 72).

Results

All patients received a statin, and on-treatment LDL-C levels were similar between the groups (66.9 ± 11.6 vs. 68.1 ± 23.2 mg/dL, p = 0.84). Patients receiving GLP-1RAs demonstrated a greater reduction of HbA1c [-1.0 (-1.4 to -0.5) vs. -0.4 (-0.6 to -0.2)%, p = 0.02] and were less likely to demonstrate a glucose level >180 mg/dL [-7.5 (-14.9 to -0.1) vs. 1.1 (-2.0 - 4.2)%, p = 0.04], accompanied by a significant decrease in remnant cholesterol levels [-3.8 (-6.3 to -1.3) vs. -0.1 (-0.8 - 1.1)mg/dL, p = 0.008]. On NIRS/IVUS imaging analysis, the change in percent atheroma volume did not differ between the groups (-0.9 ± 0.25 vs. -0.2 ± 0.2%, p = 0.23). However, GLP-1RA treated patients demonstrated a greater frequency of maxLCBI4mm regression (85.6 ± 0.1 vs. 42.0 ± 0.6%, p = 0.01). Multivariate analysis demonstrated that the GLP-1RA use was independently associated with maxLCBI4mm regression (odds ratio = 4.41, 95%CI = 1.19-16.30, p = 0.02).

Conclusions

In statin-treated patients with T2D and CAD, GLP-1RAs produced favourable changes in lipidic plaque materials, consistent with its stabilization.

Plant-Based Meat Analogs and Their Effects on Cardiometabolic Health: An 8-Week Randomized Controlled Trial Comparing Plant-Based Meat Analogs With Their Corresponding Animal-Based Foods

BACKGROUND

With the growing popularity of plant-based meat analogs (PBMAs), an investigation of their effects on health is warranted in an Asian population.

OBJECTIVES

This research investigated the impact of consuming an omnivorous animal-based meat diet (ABMD) compared with a PBMAs diet (PBMD) on cardiometabolic health among adults with elevated risk of diabetes in Singapore.

METHODS

In an 8-wk parallel design randomized controlled trial, participants (n = 89) were instructed to substitute habitual protein-rich foods with fixed quantities of either PBMAs (n = 44) or their corresponding animal-based meats (n = 45; 2.5 servings/d), maintaining intake of other dietary components. Low-density lipoprotein (LDL) cholesterol served as primary outcome, whereas secondary outcomes included other cardiometabolic disease-related risk factors (e.g. glucose and fructosamine), dietary data, and within a subpopulation, ambulatory blood pressure measurements (n = 40) at baseline and postintervention, as well as a 14-d continuous glucose monitor (glucose homeostasis-related outcomes; n = 37).

RESULTS

Data from 82 participants (ABMD: 42 and PBMD: 40) were examined. Using linear mixed-effects model, there were significant interaction (time × treatment) effects for dietary trans-fat (increased in ABMD), dietary fiber, sodium, and potassium (all increased in PBMD; P-interaction <0.001). There were no significant effects on the lipid-lipoprotein profile, including LDL cholesterol. Diastolic blood pressure (DBP) was lower in the PBMD group (P-interaction=0.041), although the nocturnal DBP dip markedly increased in ABMD (+3.2% mean) and was reduced in PBMD (-2.6%; P-interaction=0.017). Fructosamine (P time=0.035) and homeostatic model assessment for β-cell function were improved at week 8 (P time=0.006) in both groups. Glycemic homeostasis was better regulated in the ABMD than PBMD groups as evidenced by interstitial glucose time in range (ABMD median: 94.1% (Q1:87.2%, Q3:96.7%); PBMD: 86.5% (81.7%, 89.4%); P = 0.041). The intervention had no significant effect on the other outcomes examined.

CONCLUSIONS

An 8-wk PBMA diet did not show widespread cardiometabolic health benefits compared with a corresponding meat based diet. Nutritional quality is a key factor to be considered for next generation PBMAs. This trial was registered at https://clinicaltrials.gov/as NCT05446753.

The development of an EU-wide nutrition and physical activity expert knowledge base to support a personalised mobile application across various EU population groups

A healthy lifestyle comprising regular physical activity and an adequate diet is imperative for the prevention of non-communicable diseases such as hypertension and some cancers. Advances in information computer technology offer the opportunity to provide personalised lifestyle advice directly to the individual through devices such as smartphones or tablets. The overall aim of the PROTEIN project (Wilson-Barnes et al., 2021) was to develop a smartphone application that could provide tailored and dynamic nutrition and physical activity advice directly to the individual in real time. However, to create this mobile health (m-health) smartphone application, a knowledge base of reference ranges for macro-/micronutrient intake, anthropometry, biochemical, physiological and sleep parameters was required to underpin the parameters of the recommender systems. Therefore, the principal aim of this emerging research paper is to describe the process by which experts in nutrition and physiology from the PROTEIN consortium collaborated to develop the nutritional and physical activity requirements, based upon existing recommendations, for 10 separate population groups living within the EU including, but not limited to healthy adults, adults with type 2 diabetes mellitus, cardiovascular disease, excess weight, obesity and iron deficiency anaemia. A secondary aim is to describe the development of a library of 24-h meal plans appropriate for the same groups and also encompassing various dietary preferences and allergies. Overall, the consortium devised an extensive nutrition and physical activity knowledge base that is pertinent to 10 separate EU user groups, is available in 7 different languages and is practically implemented via a library of culturally appropriate, 24-h meal plans.

Recommendations for management of diabetes and its complications during Hajj (Muslim Pilgrimage) - 2024 update

Hajj is an obligatory duty for all healthy adult Muslims once in the lifetime subjected to the ability. Considering the 10.5 % global prevalence of diabetes coupled with the numbers of Muslims performing the Hajj, ∼ 1.8 million in 2023, it is estimated that Muslims with diabetes performing Hajj may exceed 340,000 this year. During Hajj the pattern and amount of their meal, fluid intake and physical activity are markedly altered. Many people with diabetes insist on doing the Hajj duty, thereby creating a medical challenge for themselves and their health care providers. It is therefore important that medical professionals be aware of the potential risks that may be associated with Hajj. People with diabetes may face many health hazards during Hajj including but not limited to the killer triad which might occur during Hajj: Hypoglycemia, Foot injury and Infections. Many precautions should be taken to prevent and treat these potentially serious complications. Risk stratification, medication adjustments, proper clinical assessment, and education before doing Hajj are crucial.

Clinically relevant stratification of patients with type 2 diabetes by using continuous glucose monitoring data

AIM

The wealth of data generated by continuous glucose monitoring (CGM) provides new opportunities for revealing heterogeneities in patients with type 2 diabetes mellitus (T2DM). We aimed to develop a method using CGM data to discover T2DM subtypes and investigate their relationship with clinical phenotypes and microvascular complications.

METHODS

The data from 3119 patients with T2DM who wore blinded CGM at an academic medical centre was collected, and a glucose symbolic pattern (GSP) metric was created that combined knowledge-based temporal abstraction with numerical vectorization. The k-means clustering was applied to GSP to obtain subgroups of patients with T2DM. Clinical characteristics and the presence of diabetic retinopathy and albuminuria were compared among the subgroups. The findings were validated in an independent population comprising 773 patients with T2DM.

RESULTS

By using GSP, four subgroups were identified with distinct features in CGM profiles and parameters. Moreover, the clustered subgroups differed significantly in clinical phenotypes, including indices of pancreatic β-cell function and insulin resistance (all p < .001). After adjusting for confounders, group C (the most insulin resistant) had a significantly higher risk of albuminuria (odds ratio = 1.24, 95% confidence interval: 1.03-1.39) relative to group D, which had the best glucose control. These findings were confirmed in the validation set.

CONCLUSION

Subtyping patients with T2DM using CGM data may help identify high-risk patients for microvascular complications and provide insights into the underlying pathophysiology. This method may help refine clinically meaningful stratification of patients with T2DM and inform personalized diabetes care.

A strategy based on integer programming for optimal dosing and timing of preventive hypoglycemic treatments in type 1 diabetes management

BACKGROUND AND OBJECTIVES

One of the major problems related to type 1 diabetes (T1D) management is hypoglycemia, a condition characterized by low blood glucose levels and responsible for reduced quality of life and increased mortality. Fast-acting carbohydrates, also known as hypoglycemic treatments (HT), can counteract this event. In the literature, dosage and timing of HT are usually based on heuristic rules. In the present work, we propose an algorithm for mitigating hypoglycemia by suggesting preventive HT consumption, with dosages and timing determined by solving an optimization problem.

METHODS

By leveraging integer programming and linear inequality constraints, the algorithm can bind the amount of suggested carbohydrates to standardized quantities (i.e., those available in "off-the-shelf" HT) and the minimal distance between consecutive suggestions (to reduce the nuisance for patients).

RESULTS

The proposed method was tested in silico and compared with competitor algorithms using the UVa/Padova T1D simulator. At the cost of a slight increase of HT consumed per day, the proposed algorithm produces the lowest median and interquartile range of the time spent in hypoglycemia, with a statistically significant improvement over most competitor algorithms. Also, the average number of hypoglycemic events per day is reduced to 0 in median.

CONCLUSIONS

Thanks to its positive performances and reduced computational burden, the proposed algorithm could be a candidate tool for integration in a DSS aimed at improving T1D management.

Improving glycemic control: transitioning from dulaglutide to tirzepatide in patients with type 2 diabetes undergoing hemodialysis

Background: Tirzepatide-a dual glucose-dependent insulinotropic peptide and glucagon-like peptide-1 receptor agonist-is used to treat type 2 diabetes. However, the efficacy and safety of tirzepatide in patients undergoing hemodialysis remain unclear. Methods: We conducted a single-center retrospective study of patients with type 2 diabetes undergoing hemodialysis who were transitioned from dulaglutide to tirzepatide. We continuously monitored glucose levels in patients undergoing hemodialysis before and after switching from dulaglutide to tirzepatide. Results: Fourteen patients (mean age: 61.9 ± 9.9 years, male: female = 11:3) were included in this study. After switching to tirzepatide, time in range increased to 50.8% from 42.7% (p = 0.02), time above range decreased to 37.8% from 48.4% (p = 0.02), and mean glucose levels decreased to 137.4 mg/dL from 156.6 mg/dL (p = 0.006). In contrast, there was no significant difference in time below range before and after tirzepatide administration (11.3% and 8.9%) (p = 0.75). Three patients experienced dyspepsia (21.4%), and one patient experienced nausea (7.1%); however, no critical adverse events were reported. Conclusion: Transitioning from dulaglutide to tirzepatide improved glycemic control without increasing hypoglycemia in patients undergoing hemodialysis for type 2 diabetes.

Generalization of a Deep Learning Model for Continuous Glucose Monitoring-Based Hypoglycemia Prediction: Algorithm Development and Validation Study

Background

Predicting hypoglycemia while maintaining a low false alarm rate is a challenge for the wide adoption of continuous glucose monitoring (CGM) devices in diabetes management. One small study suggested that a deep learning model based on the long short-term memory (LSTM) network had better performance in hypoglycemia prediction than traditional machine learning algorithms in European patients with type 1 diabetes. However, given that many well-recognized deep learning models perform poorly outside the training setting, it remains unclear whether the LSTM model could be generalized to different populations or patients with other diabetes subtypes.

Objective

The aim of this study was to validate LSTM hypoglycemia prediction models in more diverse populations and across a wide spectrum of patients with different subtypes of diabetes.

Methods

We assembled two large data sets of patients with type 1 and type 2 diabetes. The primary data set including CGM data from 192 Chinese patients with diabetes was used to develop the LSTM, support vector machine (SVM), and random forest (RF) models for hypoglycemia prediction with a prediction horizon of 30 minutes. Hypoglycemia was categorized into mild (glucose=54-70 mg/dL) and severe (glucose<54 mg/dL) levels. The validation data set of 427 patients of European-American ancestry in the United States was used to validate the models and examine their generalizations. The predictive performance of the models was evaluated according to the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).

Results

For the difficult-to-predict mild hypoglycemia events, the LSTM model consistently achieved AUC values greater than 97% in the primary data set, with a less than 3% AUC reduction in the validation data set, indicating that the model was robust and generalizable across populations. AUC values above 93% were also achieved when the LSTM model was applied to both type 1 and type 2 diabetes in the validation data set, further strengthening the generalizability of the model. Under different satisfactory levels of sensitivity for mild and severe hypoglycemia prediction, the LSTM model achieved higher specificity than the SVM and RF models, thereby reducing false alarms.

Conclusions

Our results demonstrate that the LSTM model is robust for hypoglycemia prediction and is generalizable across populations or diabetes subtypes. Given its additional advantage of false-alarm reduction, the LSTM model is a strong candidate to be widely implemented in future CGM devices for hypoglycemia prediction.

Development of a Multivariable Risk Prediction Tool to Predict Adverse Outcomes among Children with Type 1 Diabetes: A Pilot Study

Background

Children and adolescents with type 1 diabetes mellitus (T1DM) are frequently hospitalised for severe hypoglycaemia, hyperglycaemia, and diabetic ketoacidosis (DKA). While several risk factors have been recognised, clinically identifying these children at high risk of acute decompensation remains challenging.

Objective

To develop a risk prediction model to accurately estimate the risk of acute healthcare utilisation due to severe hypoglycaemia, hyperglycaemia, and DKA in children and adolescents with T1DM.

Materials and Methods

Using a retrospective dataset, baseline demographic and clinical data were collected from patients (<18 years) seen at a regional paediatric diabetes clinic from 1 January 2018 to 1 January 2020. The outcome was the number of emergency department presentations or hospital admissions for severe hypoglycaemia, hyperglycaemia, and DKA across the study period. Variables that were significant in univariate analysis were entered into a multivariable model. Receiver operator characteristic (ROC) curves assessed the model's discrimination and generated cut-offs for risk group stratification (low, medium, and high). Kaplan-Meier survival analysis measured time to acute healthcare utilisation across the risk groups.

Results

Our multivariable risk prediction model consisted of five predictors (continuous glucose monitoring device, previous acute healthcare utilisation, missed appointments, and child welfare services involvement and socioeconomic status). The model exhibited good discrimination (area under the ROC = 0.81), accurately stratified children into low-, medium-, and high-risk groups, and demonstrated significant differences between median time to healthcare utilisation.

Conclusion

Our model identified patients at an increased risk of acute healthcare utilisation due to severe hypoglycaemia, hyperglycaemia, and DKA.

Clinical perspectives on the frequency of hypoglycemia in treat-to-target randomized controlled trials comparing basal insulin analogs in type 2 diabetes: a narrative review

The objective of this review was to comprehensively present and summarize trends in reported rates of hypoglycemia with one or two times per day basal insulin analogs in individuals with type 2 diabetes to help address and contextualize the emerging theoretical concern of increased hypoglycemic risk with once-weekly basal insulins.Hypoglycemia data were extracted from treat-to-target randomized clinical trials conducted during 2000-2022. Published articles were identified on PubMed or within the US Food and Drug Administration submission documents. Overall, 57 articles were identified: 44 assessed hypoglycemic outcomes in participants receiving basal-only therapy (33 in insulin-naive participants; 11 in insulin-experienced participants), 4 in a mixed population (insulin-naive and insulin-experienced participants) and 9 in participants receiving basal-bolus therapy. For the analysis, emphasis was placed on level 2 (blood glucose <3.0 mmol/L (<54 mg/dL)) and level 3 (or severe) hypoglycemia.Overall, event rates for level 2 or level 3 hypoglycemia across most studies ranged from 0.06 to 7.10 events/person-year of exposure (PYE) for participants receiving a basal-only insulin regimen; the rate for basal-bolus regimens ranged from 2.4 to 13.6 events/PYE. Rates were generally lower with second-generation basal insulins (insulin degludec or insulin glargine U300) than with neutral protamine Hagedorn insulin or first-generation basal insulins (insulin detemir or insulin glargine U100). Subgroup categorization by sulfonylurea usage, end-of-treatment insulin dose or glycated hemoglobin reduction did not show consistent trends on overall hypoglycemia rates. Hypoglycemia rates reported so far for once-weekly basal insulins are consistent with or lower than those reported for daily-administered basal insulin analogs.

Day-to-Day Glycemic Variability Using Continuous Glucose Monitors in Endurance Athletes

OBJECTIVES

The application of continuous glucose monitors (CGMs) to measure interstitial glucose in athletic populations is limited by the lack of accepted athlete-specific reference values. The aim of this study was to develop athlete-specific reference ranges for glycemic variability under standardized diet and exercise conditions.

METHODS

A total of 12 elite racewalkers (n = 7 men, 22.4 ± 3.5 years, VO2max 61.6 ± 7.3 mL kg-1 min-1) completed two 4-d trials separated by 4-d. Athletes were provided a high-energy, high-carbohydrate diet (225 ± 1.6 kJ kg-1 day-1, 8.4 ± 0.3 g kg-1 day-1 carbohydrate) and completed standardized daily exercise. The timing of food consumed and exercise undertaken were matched each day across the 4-d trials. Interstitial glucose data were collected via Freestyle Libre 2 CGMs. Glycemic variability was calculated as the mean amplitude of glycemic excursions (MAGEs), mean of daily differences (MODD), and standard deviation (SD).

RESULTS

Twenty-four hour MODD, MAGE, and SD for interstitial glucose were 12.6 ± 1.8 mg/dL (0.7 ± 0.1 mmol/L), 36.0 ± 5.4 mg/dL (2.0 ± 0.3 mmol/L), and 16.2 ± 1.8 mg/dL (0.9 ± 0.1 mmol/L), respectively. Twenty-four hour mean glucose (MG; 102.6 ± 5.4 mg/dL [5.7 ± 0.3 mmol/L]) was higher than overnight (91.8 ± 5.4 mg/dL [5.1 ± 0.3 mmol/L]; P < .0001) and was lower in women than men (99.0 ± 3.6 mg/dL [5.5 ± 0.2 mmol/L] vs 104.4 ± 3.6 mg/dL [5.8 ± 0.2 mmol/L]; P = .059, d = 1.4).

CONCLUSIONS

This study provides reference indices under standardized diet and exercise conditions for glycemic variability derived from CGMs in endurance athletes which are similar than previously reported for healthy individuals, despite strenuous daily training and a high daily energy and carbohydrate diet.

Ultra rapid lispro improves postprandial glucose control versus lispro in combination with basal insulin: a study based on CGM in type 2 diabetes in China

AIM

To evaluate the efficacy and safety of URLi (ultra rapid lispro insulin) compared to insulin lispro as bolus insulin with basal insulin using CGM in the individuals with type 2 diabetes(T2D) in China.

METHODS

This was a double-blind, randomized, parallel, prospective, phase 3 study. Subjects with uncontrolled T2D were recruited and randomized 1:2 into the insulin lispro and URLi groups. Subjects received a consistent basal insulin regimen during the study and self-administered insulin lispro or URLi before each meal throughout the treatment period. Subjects underwent a 3-day continuous glucose monitoring (CGM) at the baseline and endpoint respectively, and then CGM data were analyzed. The primary endpoint was to compare the difference in postprandial glucose (PPG) control using CGM between the two groups.

RESULTS

A total of 57 subjects with T2D completed the study. Our CGM data showed that postprandial glucose excursions after breakfast (BPPGE) in the URLi group was lower than that in the insulin lispro group (1.59 ± 1.57 mmol/L vs 2.51 ± 1.73 mmol/L, p = 0.046). 1-hour PPG was observed to decrease more in the URLi group than that in the insulin lispro group (-1.37 ± 3.28 mmol/L vs 0.24 ± 2.58 mmol/L, p = 0.047). 2-hour PPG was observed to decrease more in the URLi group than that in the insulin lispro group (-1.12 ± 4.00 mmol/L vs 1.22 ± 2.90 mmol/L, p = 0.021). The mean HbA1c level decreased by 1.1% in the URLi group and 0.99% in the insulin lispro group, with no treatment difference (p = 0.642). In the CGM profile, TBR was not significantly different between the two groups (p = 0.743). The weight gain also did not differ between the two groups (p = 0.303).

CONCLUSION

URLi can control breakfast PPG better than insulin lispro in adults with T2D in China, while it is non-inferior in improving HbA1c. The incidence of hypoglycemic and weight gain were similar between the two groups.

Feasibility of continuous glucose monitoring in patients with type 1 diabetes at two district hospitals in Neno, Malawi: a randomised controlled trial

OBJECTIVES

To assess the feasibility and change in clinical outcomes associated with continuous glucose monitoring (CGM) use among a rural population in Malawi living with type 1 diabetes.

DESIGN

A 2:1 open randomised controlled feasibility trial.

SETTING

Two Partners In Health-supported Ministry of Health-run first-level district hospitals in Neno, Malawi.

PARTICIPANTS

45 people living with type 1 diabetes (PLWT1D).

INTERVENTIONS

Participants were randomly assigned to Dexcom G6 CGM (n=30) use or usual care (UC) (n=15) consisting of Safe-Accu glucose monitors and strips. Both arms received diabetes education.

OUTCOMES

Primary outcomes included fidelity, appropriateness and severe adverse events. Secondary outcomes included change in haemoglobin A1c (HbA1c), acceptability, time in range (CGM arm only) SD of HbA1c and quality of life.

RESULTS

Participants tolerated CGM well but were unable to change their own sensors which resulted in increased clinic visits in the CGM arm. Despite the hot climate, skin rashes were uncommon but cut-out tape overpatches were needed to secure the sensors in place. Participants in the CGM arm had greater numbers of dose adjustments and lifestyle change suggestions than those in the UC arm. Participants in the CGM arm wore their CGM on average 63.8% of the time. Participants in the UC arm brought logbooks to clinic 75% of the time. There were three hospitalisations all in the CGM arm, but none were related to the intervention.

CONCLUSIONS

This is the first randomised controlled trial conducted on CGM in a rural region of a low-income country. CGM was feasible and appropriate among PLWT1D and providers, but inability of participants to change their own sensors is a challenge.

TRIAL REGISTRATION NUMBER

PACTR202102832069874.

Comparison of efficacy and safety of insulin degludec/liraglutide and insulin glargine U-100/lixisenatide in individuals with type 2 diabetes mellitus using professional continuous glucose monitoring

AIM/INTRODUCTION

Insulin glargine U100/lixisenatide and insulin degludec/liraglutide are fixed-ratio combinations containing basal insulin and a glucagon-like peptide-1 receptor agonist capable of reducing both fasting and postprandial blood glucose levels with a single formulation. This study aimed to compare the time in range (TIR) and the time below range (TBR) level 1 using professional continuous glucose monitoring and to establish criteria for the differential use of the fixed-ratio combinations.

MATERIALS AND METHODS

Thirty-six outpatients with type 2 diabetes mellitus (24 men and 12 women; average age, 62.1 years) were randomly assigned to the groups. At 0 and 18 weeks, a device was worn to compare the TIR and TBR level 1. The correlation between the C-peptide index at baseline and TIR at 18 weeks was assessed.

RESULTS

The TIR and TBR level 1 showed no significant differences between the two groups. Both groups showed significant positive correlations between the C-peptide index and the TIR (P = 0.002, r = 0.679; P = 0.002, r = 0.681, respectively). The changes in glycemic variability, therapeutic indices, and body mass index were not significantly different among the groups (P > 0.05). The receiver operating curve analysis revealed that the cut-off values of the C-peptide index to achieve TIR of >70% at 18 weeks were 1.258 (sensitivity, 77.8%; specificity, 100%) and 1.099 (sensitivity, 57.1%; specificity, 90.9%) in the insulin glargine U100/lixisenatide and insulin degludec/liraglutide groups, respectively.

CONCLUSIONS

A TIR of >70% was achieved for both fixed-ratio combinations without significant differences.

Bedtime Prediction of Nocturnal Hypoglycemia in Insulin-Treated Type 2 Diabetes Patients

BACKGROUND AND AIMS

Hypoglycemia may lead to anxiety, poor adherence, and hypoglycemia unawareness and is especially a threat during the night in patients with insulin-treated type 2 diabetes (T2D). It would therefore be beneficial to warn patients at risk of hypoglycemia at bedtime so they can react accordingly and avoid the episode. Hence, the aim of the present study was to develop a model for predicting nocturnal hypoglycemia.

METHODS

Continuous glucose monitoring (CGM), mealtime, and insulin data were collected from 67 insulin-treated patients with T2D (NCT01819129). Data were structured into 24-hour periods and labeled as nocturnal hypoglycemia or not depending on whether 15 consecutive minutes were spent below 3.0 mmol/L (54 mg/dL) during the following night. Each period was divided into "last night," "morning," "day," and "evening" for feature extraction purposes, and 72 potential features were extracted for every period. A five-fold cross-validation was used to select features by forward selection and for training and validating a model based on logistic regression.

RESULTS

The prediction model was based on 30 patients with 60/496 periods resulting in nocturnal hypoglycemia. Forward selection revealed that the best features were based on CGM and involved the last value and mean value during the evening, as well as the relative difference in maximum value during the day between the present period and previous periods. The model obtained a mean area under the receiver operating characteristics curve (AUC) of 0.82 with an accuracy of 0.79.

CONCLUSIONS

The model was able to predict nocturnal hypoglycemia with an acceptable accuracy and could therefore prevent such cases.

Continuous Glucose Monitor Metrics Are Associated with Emergency Department Visits and Hospitalizations for Hypoglycemia and Hyperglycemia, but Have Low Predictive Value

Objective: Determine whether continuous glucose monitor (CGM) metrics can provide actionable advance warning of an emergency department (ED) visit or hospitalization for hypoglycemic or hyperglycemic (dysglycemic) events. Research Design and Methods: Two nested case-control studies were conducted among insulin-treated diabetes patients at Kaiser Permanente, who shared their CGM data with their providers. Cases included dysglycemic events identified from ED and hospital records (2016-2021). Controls were selected using incidence density sampling. Multiple CGM metrics were calculated among patients using CGM >70% of the time, using CGM data from two lookback periods (0-7 and 8-14 days) before each event. Generalized estimating equations were specified to estimate odds ratios and C-statistics. Results: Among 3626 CGM users, 108 patients had 154 hypoglycemic events and 165 patients had 335 hyperglycemic events. Approximately 25% of patients had no CGM data during either lookback; these patients had >2 × the odds of a hypoglycemic event and 3-4 × the odds of a hyperglycemic event. While several metrics were strongly associated with a dysglycemic event, none had good discrimination. Conclusion: Several CGM metrics were strongly associated with risk of dysglycemic events, and these can be used to identify higher risk patients. Also, patients who are not using their CGM device may be at elevated risk of adverse outcomes. However, no CGM metric or absence of CGM data had adequate discrimination to reliably provide actionable advance warning of an event and thus justify a rapid intervention.

Comparing Continuous Glucose Monitoring and Blood Glucose Monitoring in Adults With Inadequately Controlled, Insulin-Treated Type 2 Diabetes (Steno2tech Study): A 12-Month, Single-Center, Randomized Controlled Trial

OBJECTIVE

To compare the 12-month effects of continuous glucose monitoring (CGM) versus blood glucose monitoring (BGM) in adults with insulin-treated type 2 diabetes.

RESEARCH DESIGN AND METHODS

This is a single-center, parallel, open-label, randomized controlled trial including adults with inadequately controlled, insulin-treated type 2 diabetes from the outpatient clinic at Steno Diabetes Center Copenhagen, Denmark. Inclusion criteria were ≥18 years of age, insulin-treated type 2 diabetes, and HbA1c ≥7.5% (58 mmol/mol). Participants were randomly assigned (1:1) to 12 months of either CGM or BGM. All participants received a diabetes self-management education course and were followed by their usual health care providers. Primary outcome was between-group differences in change in time in range (TIR) 3.9-10.0 mmol/L, assessed at baseline, after 6 and 12 months by blinded CGM. The prespecified secondary outcomes were differences in change in several other glycemic, metabolic, and participant-reported outcomes.

RESULTS

The 76 participants had a median baseline HbA1c of 8.3 (7.8, 9.1)% (67 [62-76] mmol/mol), and 61.8% were male. Compared with BGM, CGM usage was associated with significantly greater improvements in TIR (between-group difference 15.2%, 95% CI 4.6; 25.9), HbA1c (-0.9%, -1.4; -0.3 [-9.4 mmol/mol, -15.2; -3.5]), total daily insulin dose (-10.6 units/day, -19.9; -1.3), weight (-3.3 kg, -5.5; -1.1), and BMI (-1.1 kg/m2, -1.8; -0.3) and greater self-rated diabetes-related health, well-being, satisfaction, and health behavior.

CONCLUSIONS

In adults with inadequately controlled insulin-treated type 2 diabetes, the 12-month impact of CGM was superior to BGM in improving glucose control and other crucial health parameters. The findings support the use of CGM in the insulin-treated subgroup of type 2 diabetes.

Association between extrapolated time in range and large for gestational age infants in pregnant women with type 1 diabetes

AIMS

To evaluate the association between extrapolated time in range (eTIR), measured by self-monitoring of blood glucose (SMBG), and large-for-gestational-age (LGA) infants in pregnancies with type 1 diabetes (T1D).

METHODS

Retrospective cohort analysis including singleton pregnancies with T1D who started antenatal care before 20 gestational weeks and delivered live newborns at a Brazilian hospital between 2010 and 2019, with LGA fetuses as the main outcome. Glycemic records acquired using SMBG were categorized as eTIR, extrapolated time below range (eTBR), and extrapolated time above range (eTAR). Women were divided into two groups (LGA and adequate for gestational age [AGA]) and compared regarding clinical characteristics, obstetric outcomes, and frequencies of eTIR, eTBR, and eTAR. Logistic regression analysis verified the independent predictive variables for LGA infants.

RESULTS

Data from 125 pregnancies were analyzed. For the first, second and third trimesters, each 1 % increase in eTIR was associated with a decreased risk of LGA by 2.9 % (OR: 0.971; 95%CI: 0.945-0.998), 2.5 % (OR: 0.975; 95%CI: 0.951-0.999) and 2.3 % (OR: 0.977; 95%CI: 0.955-0.998) and each 1 % increase in eTAR was associated with an increased risk of LGA by 2.7 % (OR: 1.027; 95%CI: 1.005-1.050), 3.9 % (OR: 1.039; 95%CI: 1.014-1.063) and 4.6 % (OR: 1.046; 95%CI: 1.018-1.075), respectively.

CONCLUSION

The concept of TIR can be extrapolated to patients undergoing SMBG to assess the risk of LGA infants in pregnant women with T1D.

Impact of Glucocorticoid Replacement Therapy on Nocturnal Hypoglycemia in Adrenal Insufficiency: An Analysis of Multiple Case Studies

BACKGROUND AND AIM

Adrenal insufficiency (AI) is a hormonal disorder characterized by insufficient glucocorticoid production. Nocturnal hypoglycemia (NH) occurs in patients with AI. However, the effect of glucocorticoid replacement therapy (GCRT) on AI and NH remains unclear. This study aimed to investigate the relationship between AI and NH by evaluating the impact of GCRT on NH in patients newly diagnosed with AI.

METHODS

The present study was conducted between October 2018 and December 2022 at the Department of Diabetes, Metabolism and Endocrinology of the Tokyo Rosai Hospital, Japan. In total, 15 patients aged ≥18 years with newly diagnosed AI or NH were included in this study. The NH frequency was measured using continuous glucose monitoring (CGM). The primary outcome was the change in NH frequency before and after the GCRT intervention.

RESULTS

GCRT significantly decreased NH frequency. Severe NH frequency and minimum nocturnal glucose levels changed significantly while fasting blood glucose and glycated hemoglobin levels did not change significantly. GCRT intervention improved CGM profiles' time below range, time in range, and average daily risk range.

CONCLUSIONS

 The present study suggests that GCRT can help newly diagnosed patients with AI manage NH. These findings show that CGM can detect NH in patients with newly diagnosed AI, determine the optimal GCRT dosage, and hence prevent an impaired quality of life and even serious adverse effects in these patients. Further large multicenter studies should validate these findings and delve deeper into the mechanistic link between AI and NH.

The effect of ionic redistributions on the microwave dielectric response of cytosol water upon glucose uptake

The sensitivity of cytosol water's microwave dielectric (MD) response to D-glucose uptake in Red Blood Cells (RBCs) allows the detailed study of cellular mechanisms as a function of controlled exposures to glucose and other related analytes like electrolytes. However, the underlying mechanism behind the sensitivity to glucose exposure remains a topic of debate. In this research, we utilize MDS within the frequency range of 0.5-40 GHz to explore how ionic redistributions within the cell impact the microwave dielectric characteristics associated with D-glucose uptake in RBC suspensions. Specifically, we compare glucose uptake in RBCs exposed to the physiological concentration of Ca2+ vs. Ca-free conditions. We also investigate the potential involvement of Na+/K+ redistribution in glucose-mediated dielectric response by studying RBCs treated with a specific Na+/K+ pump inhibitor, ouabain. We present some insights into the MD response of cytosol water when exposed to Ca2+ in the absence of D-glucose. The findings from this study confirm that ion-induced alterations in bound/bulk water balance do not affect the MD response of cytosol water during glucose uptake.

Q-Score Complements the Time in Range in the Evaluation of Short-Term Glycemic Control

BACKGROUND AND AIMS

The Q-Score is a single-number composite metric that is constructed based on the following components: central glycemic tendency, hyperglycemia, hypoglycemia, and intra- and interday variability. Herein, we refined the Q-Score for the screening and analysis of short-term glycemic control using continuous glucose monitoring (CGM) profiles.

METHODS

Continuous glucose monitoring profiles were obtained from noninterventional, retrospective cross-sectional studies. The upper limit of the Q-Score component hyperglycemia' that is, the time above target range (TAR), was adjusted from 8.9 to 10 mmol/L (n = 1562 three-day-sensor profiles). A total of 302 people with diabetes mellitus treated with intermittent CGM for ≥14 days were enrolled. The time to stability was determined via correlation-based analysis.

RESULTS

There was a strong correlation between the Q-Scores of the two TARs, that is, 8.9 and 10 mmol/L (Q-ScoreTAR10 = -0.03 + 1.00 Q-ScoreTAR8.9, r = .997, p < .001). The times to stability of the Q-Score and TIR were 10 and 12 days, respectively. The Q-Score was correlated with fructosamine concentrations, the glucose management indicator (GMI), the time in range (TIR), and the glycemic risk index (GRI) (r = .698, .887, -.874, and .941), respectively. The number of Q-Score components above the target increased as the TIR decreased, from two (1.7 ± 0.9) in CGM profiles with a TIR between 70% and 80% to four (3.9 ± 0.5) in the majority of the CGM profiles with a TIR below 50%. A conversion matrix between the Q-Score and glycemic indices was developed.

CONCLUSIONS

The Q-Score is a tool for assessing short-term glycemic control. The Q-Score can be translated into clinician opinion using the GRI.

Investigation of the hypoglycemic mechanism of the ShenQi compound formula through metabonomics and 16S rRNA sequencing

Introduction: Herbal formulations are renowned for their complex biological activities, acting on multiple targets and pathways, as evidenced by in vitro studies. However, the hypoglycemic effect and underlying mechanisms of Shenqi Compound (SQ), a traditional Chinese herbal formula, remain elusive. This study aimed to elucidate the hypoglycemic effects of SQ and explore its mechanisms of action, focusing on intestinal flora and metabolomics. Methods: A Type 2 diabetes mellitus (T2DM) rat model was established through a high-fat diet, followed by variable glucose and insulin injections to mimic the fluctuating glycemic conditions seen in diabetes. Results: An eight-week regimen of SQ significantly mitigated hyperglycemia, inflammation, and insulin resistance in these rats. Notably, SQ beneficially modulated the gut microbiota by increasing populations of beneficial bacteria, such as Lachnospiraceae_NK4A136_group and Akkermansia, while reducing and inhibiting harmful strains such as Ruminococcus and Phascolarctobacterium. Metabolomics analyses revealed that SQ intervention corrected disturbances in Testosterone enanthate and Glycerophospholipid metabolism. Discussion: Our findings highlight the hypoglycemic potential of SQ and its mechanisms via modulation of the gut microbiota and metabolic pathways, offering a theoretical foundation for the use of herbal medicine in diabetes management.

Hypoglycemia and Hyperglycemia According to Type of Diabetes: Observations During Fully Closed-Loop Insulin Delivery in Adults With Type 1 and Type 2 Diabetes

BACKGROUND

CamAPS HX fully closed-loop (FCL) system, with no user input required at mealtimes, has been shown to be safe and effective in adults with type 1 and type 2 diabetes. We assessed whether time spent in hypoglycemia and hyperglycemia during FCL insulin delivery in adults varied by type of diabetes over the 24-hour period.

METHODS

We retrospectively analyzed eight weeks of data from 52 participants (adults with type 1 diabetes and adults with insulin-treated type 2 diabetes) recruited to two single-center randomized controlled studies using FCL insulin delivery during unrestricted-living conditions. Key outcomes were time spent in hypoglycemia <70 mg/dL and marked hyperglycemia >300 mg/dL by type of diabetes.

RESULTS

The median percentage of time spent in hypoglycemia <70 mg/dL over the 24-hour period was lower for those with type 2 diabetes than for those with type 1 diabetes (median [interquartile range (IQR)] 0.43% [0.20-0.77] vs 0.86%, [0.54-1.46]; mean difference 0.46 percentage points [95% CI 0.23-0.70]; P < .001). Median percentage time in marked hyperglycemia >300 mg/dL was lower for those with type 2 diabetes than for those with type 1 diabetes (median [IQR] 1.8% [0.6-3.5] vs 9.3% [6.9-11.8]; mean difference 7.8 percentage points [95% CI 5.5-10.0]; P < .001).

CONCLUSIONS

Using the FCL system, hypoglycemia and marked hyperglycemia exposure were lower in type 2 diabetes than in type 1 diabetes.

Gastric emptying of a glucose drink is predictive of the glycaemic response to oral glucose and mixed meals, but unrelated to antecedent glycaemic control, in type 2 diabetes

BACKGROUND

Gastric emptying (GE), with wide inter-individual but lesser intra-individual variations, is a major determinant of postprandial glycaemia in health and type 2 diabetes (T2D). However, it is uncertain whether GE of a carbohydrate-containing liquid meal is predictive of the glycaemic response to physiological meals, and whether antecedent hyperglycaemia influences GE in T2D. We evaluated the relationships of (i) the glycaemic response to both a glucose drink and mixed meals with GE of a 75 g glucose drink, and (ii) GE of a glucose drink with antecedent glycaemic control, in T2D.

METHODS

Fifty-five treatment-naive Chinese adults with newly diagnosed T2D consumed standardised meals at breakfast, lunch and dinner with continuous interstitial glucose monitoring. On the subsequent day, a 75 g glucose drink containing 150 mg 13C-acetate was ingested to assess GE (breath test) and plasma glucose response. Serum fructosamine and HbA1c were also measured.

RESULTS

Plasma glucose incremental area under the curve (iAUC) within 2 hours after oral glucose was related inversely to the gastric half-emptying time (T50) (r = -0.34, P = 0.012). The iAUCs for interstitial glucose within 2 hours after breakfast (r = -0.34, P = 0.012) and dinner (r = -0.28, P = 0.040) were also related inversely to the T50 of oral glucose. The latter, however, was unrelated to antecedent fasting plasma glucose, 24-hour mean interstitial glucose, serum fructosamine, or HbA1c.

CONCLUSIONS

In newly diagnosed, treatment-naive, Chinese with T2D, GE of a 75 g glucose drink predicts the glycaemic response to both a glucose drink and mixed meals, but is not influenced by spontaneous short-, medium- or longer-term elevation in glycaemia.

A novel questionnaire for evaluating digital tool use (DTUQ-D) among individuals with type 2 diabetes: exploring the digital landscape

INTRODUCTION

Effective healthcare currently incorporates a patient-centric system and accessible technology for patient self-management. This study aimed to develop and validate a novel questionnaire titled the Digital Tool Use Questionnaire for Diabetes (DTUQ-D) - a screening tool identifying the type, number, and frequency of digital tools used by Type 2 Diabetes Mellitus (T2DM) patients with within HMOs, online, and via applications.

METHODS

The questionnaire was administered to two ethnic groups and both genders. A mixed-methods approach was used. In the qualitative phase, the questionnaire was developed through phone surveys of 29 T2DM patients, two endocrinologists and two technology experts. In the quantitative phase, involving 367 participants, convergent validity, construct validity, and reliability were examined.

RESULTS

Findings indicated that the DTUQ-D is valid and reliable, successfully identifying digital tools utilized by T2DM patients, notwithstanding variations in factor structures between ethnic groups. This questionnaire provides a foundation for future research, offering a standardized approach to evaluating digital tool usage.

DISCUSSION

The study enhances understanding of the role of digital tools in healthcare, especially for T2DM self-management. It also can be easily adapted to assess digital tool use for other illnesses by adjusting instructions and the wording of certain items.

Glycemic variability assessed using continuous glucose monitoring in individuals without diabetes and associations with cardiometabolic risk markers: A systematic review and meta-analysis

BACKGROUND & AIMS

Continuous glucose monitoring (CGM) provides data on short-term glycemic variability (GV). GV is associated with adverse outcomes in individuals with diabetes. Whether GV is associated with cardiometabolic risk in individuals without diabetes is unclear. We systematically reviewed the literature to assess whether GV is associated with cardiometabolic risk markers or outcomes in individuals without diabetes.

METHODS

Searches were performed in PubMed/Medline, Embase and Cochrane from inception through April 2022. Two researchers were involved in study selection, data extraction and quality assessment. Studies evaluating GV using CGM for ≥24 h were included. Studies in populations with acute and/or critical illness were excluded. Both narrative synthesis and meta-analyzes were performed, depending on outcome.

RESULTS

Seventy-one studies were included; the majority were cross-sectional. Multiple measures of GV are higher in individuals with compared to without prediabetes and GV appears to be inversely associated with beta cell function. In contrast, GV is not clearly associated with insulin sensitivity, fatty liver disease, adiposity, blood lipids, blood pressure or oxidative stress. However, GV may be positively associated with the degree of atherosclerosis and cardiovascular events in individuals with coronary disease.

CONCLUSION

GV is elevated in prediabetes, potentially related to beta cell dysfunction, but less clearly associated with obesity or traditional risk factors. GV is associated with coronary atherosclerosis development and may predict cardiovascular events and type 2 diabetes. Prospective studies are warranted, investigating the predictive power of GV in relation to incident disease. GV may be an important risk measure also in individuals without diabetes.

Continuous Glucose Monitoring-Based Metrics and Hypoglycemia Duration in Insulin-Experienced Individuals With Long-standing Type 2 Diabetes Switched From a Daily Basal Insulin to Once-Weekly Insulin Icodec: Post Hoc Analysis of ONWARDS 2 and ONWARDS 4

OBJECTIVE

This post hoc analysis assessed continuous glucose monitoring (CGM)-based metrics and hypoglycemia duration with once-weekly insulin icodec versus once-daily basal insulin analogs in insulin-experienced individuals with long-standing type 2 diabetes from two 26-week phase 3a trials (ONWARDS 2 and ONWARDS 4).

RESEARCH DESIGN AND METHODS

Time in range (TIR) (3.9-10.0 mmol/L), time above range (TAR) (>10.0 mmol/L), and time below range (TBR) (<3.9 mmol/L and <3.0 mmol/L) were assessed during three CGM time periods (switch [weeks 0-4], end of treatment [weeks 22-26], and follow-up [weeks 27-31]) for icodec versus comparators (ONWARDS 2, insulin degludec [basal regimen]; ONWARDS 4, insulin glargine U100 [basal-bolus regimen]) using double-blind CGM data. CGM-derived hypoglycemic episode duration (<3.9 mmol/L) was assessed.

RESULTS

In both trials, there were no statistically significant differences in TIR, TAR, or TBR (<3.0 mmol/L) for icodec versus comparators across all time periods. In the end-of-treatment period, mean TIR was 63.1% (icodec) vs. 59.5% (degludec) in ONWARDS 2 and 66.9% (icodec) vs. 66.4% (glargine U100) in ONWARDS 4. Mean TBR <3.9 mmol/L and <3.0 mmol/L remained within recommended targets (<4% and <1%, respectively) across time periods and treatment arms. Hypoglycemic episode duration (<3.9 mmol/L) was comparable across time periods and treatment arms (median duration ≤40 min).

CONCLUSIONS

In insulin-experienced participants with long-standing type 2 diabetes, CGM-based TIR, TAR, and CGM-derived hypoglycemia duration (<3.9 mmol/L) were comparable for icodec and once-daily basal insulin analogs during all time periods. TBR remained within recommended targets.

Comparator Data Characteristics and Testing Procedures for the Clinical Performance Evaluation of Continuous Glucose Monitoring Systems

Comparing the performance of different continuous glucose monitoring (CGM) systems is challenging due to the lack of comprehensive guidelines for clinical study design. In particular, the absence of concise requirements for the distribution of comparator (reference) blood glucose (BG) concentrations and their rate of change (RoC) that are used to evaluate CGM performance, impairs comparability. For this article, several experts in the field of CGM performance testing have collaborated to propose characteristics of the distribution of comparator measurements that should be collected during CGM performance testing. Specifically, it is proposed that at least 7.5% of comparator BG concentrations are <70 mg/dL (3.9 mmol/L) and >300 mg/dL (16.7 mmol/L), respectively, and that at least 7.5% of BG-RoC combinations indicate fast BG changes with impending hypo- or hyperglycemia, respectively. These proposed characteristics of the comparator data can facilitate the harmonization of testing conditions across different studies and CGM systems and ensure that the most relevant scenarios representing real-life situations are established during performance testing. In addition, a study protocol and testing procedure for the manipulation of glucose levels are suggested that enable the collection of comparator data with these characteristics. This work is an important step toward establishing a future standard for the performance evaluation of CGM systems.

Association between continuous glucose monitoring-derived glycemic control indices and urinary biomarkers of diabetic kidney disease: Hyogo Diabetes Hypoglycemia Cognition Complications study

AIMS

Glomerular damage and proximal tubular damage play an important role in the pathogenesis of diabetic kidney disease. This study aimed to investigate the relationship between the urinary markers of proximal tubular injury, including urinary liver-type fatty acid-binding protein-to-creatinine ratio (uL-FABP/Cr) and urinary N-acetyl-β-D-glucosaminidase-to-creatinine ratio (uNAG/Cr), and glycemic control status.

METHODS

This cross-sectional study included 245 and 39 patients with type 2 diabetes mellitus (T2DM) and non-T2DM (NDM), respectively. The participants of this study were fitted with retrospective CGM, and glycemic control indices, such as time in range (TIR) and glycemia risk index (GRI), were calculated.

RESULTS

The results were presented as medians (interquartile ranges). The uL-FABP/Cr was significantly higher in the microalbuminuria than in the normo-albuminuria group [4.2 (2.7-7.1) and 2.2 (1.4-3.4) μg/gCr, respectively, P < 0.001], while the uNAG/Cr in the normo-albuminuria group [6.3 (4.5-10.1) U/gCr] was significantly higher than that in the NDM group [5.3 (3.8-6.3) U/gCr, P = 0.048] but significantly lower than that in the microalbuminuria group [9.2 (6.4-11.1) U/gCr, P = 0.004]. The multivariate logistic regression analysis indicated that CGM-derived TIR was significantly associated with the urinary albumin-to-creatinine ratio [uAlb/Cr, odds ratio (OR) 0.985, 95% confidence interval (CI) 0.971-0.998, P = 0.029] and uNAG/Cr (OR 0.973, 95% CI 0.957-0.989, P = 0.001) independent of renal function. GRI was similarly associated with uAlb/Cr and uNAG/Cr.

CONCLUSION

The findings of this study indicated that uNAG/Cr was elevated before albuminuria development and was associated with CGM-derived TIR and GRI.

Cost-utility analysis of Dexcom G6 real-time continuous glucose monitoring versus FreeStyle Libre 1 intermittently scanned continuous glucose monitoring in adults with type 1 diabetes in Belgium

AIMS/HYPOTHESIS

The aim of this study was to assess the long-term cost-effectiveness of Dexcom G6 real-time continuous glucose monitoring (rtCGM) with alert functionality compared with FreeStyle Libre 1 intermittently scanned continuous glucose monitoring (isCGM) without alerts in adults with type 1 diabetes in Belgium.

METHODS

The IQVIA CORE Diabetes Model was used to estimate cost-effectiveness. Input data for the simulated baseline cohort were sourced from the randomised ALERTT1 trial (ClinicalTrials.gov.

REGISTRATION NO

NCT03772600). The age of the participants was 42.9 ± 14.1 years (mean ± SD), and the baseline HbA1c was 57.8 ± 9.5 mmol/mol (7.4 ± 0.9%). Participants using rtCGM showed a reduction in HbA1c of 3.6 mmol/mol (0.36 percentage points) based on the 6-month mean between-group difference. In the base case, both rtCGM and isCGM were priced at €3.92/day (excluding value-added tax [VAT]) according to the Belgian reimbursement system. The analysis was performed from a Belgian healthcare payer perspective over a lifetime time horizon. Health outcomes were expressed as quality-adjusted life years. Probabilistic and one-way sensitivity analyses were used to account for parameter uncertainty.

RESULTS

In the base case, rtCGM dominated isCGM, resulting in lower diabetes-related complication costs and better health outcomes. The associated main drivers favouring rtCGM were lower HbA1c, fewer severe hypoglycaemic events and reduced fear of hypoglycaemia. The results were robust under a wide range of one-way sensitivity analyses. In models where the price of rtCGM is €5.11/day (a price increase of 30.4%) or €12.34/day (a price increase of 214.8%), rtCGM was cost-neutral or reached an incremental cost-effectiveness ratio of €40,000 per quality-adjusted life year, respectively.

CONCLUSIONS/INTERPRETATION

When priced similarly, Dexcom G6 rtCGM with alert functionality has both economic and clinical benefits compared with FreeStyle Libre 1 isCGM without alerts in adults with type 1 diabetes in Belgium, and appears to be a cost-effective glucose monitoring modality. Trial registration ClinicalTrials.gov NCT03772600.

Continuous Glucose Monitoring Systems in Noninsulin-Treated People with Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Introduction: Continuous glucose monitoring (CGM) has shown favorable outcomes in patients with type 2 diabetes (T2D) who are on insulin therapy. However, the efficacy of CGM in managing glucose levels in noninsulin-treated people with T2D remains controversial. Methods: PubMed, Cochrane, and Embase were searched for randomized controlled trials (RCTs) comparing CGM to self-monitoring of blood glucose (SMBG) in people with T2D not using insulin. We computed weighted mean differences (WMDs) and standard mean differences (SMD) for continuous outcomes, with 95% confidence intervals (CIs). Heterogeneity was assessed using I2 statistics. Statistical analyses were performed using R version 4.2.3. Results: We included six RCTs comprising 407 noninsulin-treated people with T2D of whom 228 were randomized to CGM. Diabetes duration ranged from 5.4 to 13.9 years. The mean age was 57.9 years and the mean body mass index was 30.8 kg/m2. Four trials used real-time CGM (rt-CGM) and two intermittent scanning CGM (is-CGM). Compared with SMBG, CGM significantly reduced the glycated hemoglobin level (WMD -0.31%; 95% CI -0.42 to -0.21; I2 = 0%), glucose level (WMD -11.16 mg/dL; 95% CI -19.94 to -2.39; I2 = 0%), time in hypoglycemia level 2 (WMD -0.28%; 95% CI -0.52 to -0.03; I2 = 91%), glucose time >180 mg/dL (WMD -7.75%; 95% CI -12.04 to -3.45; I2 = 0%), and the standard deviation of glucose variation (WMD -4.00 mg/dL; 95% CI -6.86 to -1.14; I2 = 0%). CGM also increased time in range (WMD 8.63%; 95% CI 4.54-12.71; I2 = 0%) and treatment satisfaction (SMD 0.79; 95% CI 0.54-1.05; I2 = 0%). Conclusion: In this meta-analysis, rt-CGM and is-CGM were associated with improvement in glycemic control in people with T2D not using insulin when compared to SMBG.

Machine Learning and Deep Learning Models for Nocturnal High- and Low-Glucose Prediction in Adults with Type 1 Diabetes

Glucose management at night is a major challenge for people with type 1 diabetes (T1D), especially for those managed with multiple daily injections (MDIs). In this study, we developed machine learning (ML) and deep learning (DL) models to predict nocturnal glucose within the target range (3.9-10 mmol/L), above the target range, and below the target range in subjects with T1D managed with MDIs. The models were trained and tested on continuous glucose monitoring data obtained from 380 subjects with T1D. Two DL algorithms-multi-layer perceptron (MLP) and a convolutional neural network (CNN)-as well as two classic ML algorithms, random forest (RF) and gradient boosting trees (GBTs), were applied. The resulting models based on the DL and ML algorithms demonstrated high and similar accuracy in predicting target glucose (F1 metric: 96-98%) and above-target glucose (F1: 93-97%) within a 30 min prediction horizon. Model performance was poorer when predicting low glucose (F1: 80-86%). MLP provided the highest accuracy in low-glucose prediction. The results indicate that both DL (MLP, CNN) and ML (RF, GBTs) algorithms operating CGM data can be used for the simultaneous prediction of nocturnal glucose values within the target, above-target, and below-target ranges in people with T1D managed with MDIs.

Impact on diabetes control and patient-reported outcomes of a newer implantable continuous glucose monitoring system (Eversense® CGM System): a single-centre retro- and prospective observational study

AIMS OF THE STUDY

The Eversense® CGM System is the first and only continuous glucose monitoring system (CGMS) that uses a fully subcutaneous implanted sensor. This study aimed to evaluate effectiveness, safety and patient-reported outcomes in patients using the Eversense® CGM System in a realistic clinical setting, assessed at a single Swiss diabetes centre (Luzerner Kantonsspital) with prolonged follow-up.

METHODS

This was a prospective and retrospective observational study that included patients with type 1 diabetes mellitus in whom at least one Eversense® glucose sensor was implanted between 2017 and 2022. The primary endpoint was the change in HbA1c levels from the baseline (before implantation of the sensor) to 6 ± 2 and 12 ± 2 months and the last follow-up (newest available value) after implantation. The secondary outcome measures were the number of premature sensor breakdowns, adverse events related to the implantation procedure (infection, bleeding, difficulties with implantation or explantation) and patient-related outcomes (assessed with a questionnaire).

RESULTS

A total of 33 patients participated in this study. The median follow-up time was 50 (IQR 22.3-58.5) months. In total, 178 sensor implantations were performed. Valid HbA1c results were available for 26 participants. Compared to the baseline values, HbA1c levels at 6 and 12 months and the last follow-up changed by -0.25%, -0.45 and -0.2 (p = 0.278, 0.308 and 0.296, respectively). We recorded 16 (9%) premature sensor breakdowns, all occurring between 2019 and 2020. Apart from one late-onset infection and four complicated sensor removals, no major complications were assessed. The results of the questionnaire showed a subjective improvement in hypoglycaemia rates, a better perception of hypoglycaemia and the impression of better diabetes management. Common issues with the device reported by the patients were technical errors (connection problems) and problems with the removal procedure.

CONCLUSIONS

The use of the Eversense® CGM System resulted in changes in HbA1c of between -0.2% and -0.45%. The rate of premature sensor breakdown was low. Major complications following sensor implantation or removal were absent, apart from one case of infection and four cases of complicated removal. Patient-reported outcomes with the Eversense® CGM System showed a subjective positive impact on hypoglycaemia rates, greater confidence in managing hypoglycaemia and diabetes in general, and easy handling of the transmitter and mobile app. Technical issues must be considered but are nowadays, with the use of the newest sensor generation, very rare.

A Machine Learning Model for Week-Ahead Hypoglycemia Prediction From Continuous Glucose Monitoring Data

BACKGROUND

Remote patient monitoring (RPM) programs augment type 1 diabetes (T1D) care based on retrospective continuous glucose monitoring (CGM) data. Few methods are available to estimate the likelihood of a patient experiencing clinically significant hypoglycemia within one week.

METHODS

We developed a machine learning model to estimate the probability that a patient will experience a clinically significant hypoglycemic event, defined as CGM readings below 54 mg/dL for at least 15 consecutive minutes, within one week. The model takes as input the patient's CGM time series over a given week, and outputs the predicted probability of a clinically significant hypoglycemic event the following week. We used 10-fold cross-validation and external validation (testing on cohorts different from the training cohort) to evaluate performance. We used CGM data from three different cohorts of patients with T1D: REPLACE-BG (226 patients), Juvenile Diabetes Research Foundation (JDRF; 355 patients) and Tidepool (120 patients).

RESULTS

In 10-fold cross-validation, the average area under the receiver operating characteristic curve (ROC-AUC) was 0.77 (standard deviation [SD]: 0.0233) on the REPLACE-BG cohort, 0.74 (SD: 0.0188) on the JDRF cohort, and 0.76 (SD: 0.02) on the Tidepool cohort. In external validation, the average ROC-AUC across the three cohorts was 0.74 (SD: 0.0262).

CONCLUSIONS

We developed a machine learning algorithm to estimate the probability of a clinically significant hypoglycemic event within one week. Predictive algorithms may provide diabetes care providers using RPM with additional context when prioritizing T1D patients for review.

Intermittently Scanned Continuous Glucose Monitoring Performance in Patients With Liver Cirrhosis

AIM

To evaluate the use of intermittently scanned continuous glucose monitoring (isCGM) in patients with liver cirrhosis (LC).

METHODS

Observational study including 30 outpatients with LC (Child-Pugh B/C): 10 without diabetes (DM) (G1), 10 with newly diagnosed DM by oral glucose tolerance test (G2), and 10 with a previous DM diagnosis (G3). isCGM (FreeStyle Libre Pro) was used for 56 days (four sensors/patient). Blood tests were performed at baseline and after 28 and 56 days.

RESULTS

No differences were found in the baseline characteristics, except for higher age in G3. There were significant differences between G1, G2 and G3 in glucose management indicator (GMI) (5.28 ± 0.17, 6.03 ± 0.59, 6.86 ± 1.08%, P < .001), HbA1c (4.82 ± 0.39, 5.34 ± 1.26, 6.97 ± 1.47%, P < .001), average glucose (82.79 ± 7.06, 113.39 ± 24.32, 149.14 ± 45.31mg/dL, P < .001), time in range (TIR) (70.89 ± 9.76, 80.2 ± 13.55, 57.96 ± 17.96%, P = .006), and glucose variability (26.1 ± 5.0, 28.21 ± 5.39, 35.31 ± 6.85%, P = .004). There was discordance between GMI and HbA1c when all groups were considered together, with a mean difference of 0.35% (95% SD 0.17, 0.63). In G1, the mean difference was 0.46% (95% SD 0.19, 0.73) and in G2 0.69% (95% SD 0.45, 1.33). GMI and HbA1c were concordant in G3, with a mean difference of -0.10 % (95% SD [-0.59, 0.38]).

CONCLUSION

Disagreements were found between the GMI and HbA1c levels in patients with LC. isCGM was able to detect abnormalities in glycemic control that would not be detected by monitoring with HbA1c, suggesting that isCGM can be useful in assessing glycemic control in patients with LC.

Determination of Time in Range Associated With HbA1c ≤7% in a Prospective Cohort of Patients With Type 1 Diabetes Using Continuous Glucose Monitoring for Three Months

INTRODUCTION

Finding a goal of time in range (%TIR) that defines good glycemic control is necessary. Previous retrospective studies suggest good concordance between HbA1c ≤7% with a TIR >70%; however, the studies that included the largest number of patients used blood glucose measurement data with a follow-up time of less than 90 days. This study defined the TIR value that best discriminates HbA1c ≤7%.

METHODS

We performed a prospective study of diagnostic tests based on a cohort of patients with type 1 diabetes (T1D) treated with a hybrid closed loop (HCL) followed for three months. The ability of %TIR to distinguish patients with HbA1c ≤7% was evaluated through receiver operating characteristic curve analysis. We determined the %TIR cutoff point with the best operating characteristics.

RESULTS

A total of 118 patients were included (58.1% women, 47% overweight or obese, and 33% with high glycemic variability). A moderate negative correlation (R = -.54, P < .001) was found between %TIR and HbA1c. The discrimination ability was moderate, with an area under the curve of 0.7485 (95% confidence interval = 0.6608-0.8363). The cutoff point that best predicted HbA1c ≤7% was %TIR ≥75.5 (sensitivity 70%, specificity 67%). The findings were similar among those with a coefficient of variation (CV%) ≥36%.

CONCLUSIONS

Our data suggest that the %TIR adequately identifies patients with HbA1c ≤7%. A target of TIR ≥75%, rather than the currently recommended TIR ≥70%, may be a more suitable value for optimal glycemic control.

Future of Time-in-Range Goals in the Era of Advanced Hybrid Closed-Loop Automated Insulin Delivery Systems

The concept of maintaining blood glucose levels within the 70-180 mg/dL range, known as time-in-range, has raised questions regarding its representation of true physiological euglycemia. Some have speculated that focusing on the time spent within the 70-140 mg/dL range, introduced as time in tight range (TITR) through the International Consensus statement, could serve as a more precise metric for assessing normoglycemia in individuals with type 1 diabetes. This article delves into the current status of TITR as an emerging marker and explores how advanced hybrid closed-loop systems may offer a promising avenue for achieving this higher level of glycemic control.

Is It Time to Move Beyond TIR to TITR? Real-World Data from Over 20,000 Users of Continuous Glucose Monitoring in Patients with Type 1 and Type 2 Diabetes

The growing use of continuous glucose monitoring (CGM) has been supported by expert consensus and clinical guidelines on glycemic management in diabetes with time in range (TIR 70-180 mg/dL) representing a key CGM-derived glucose metric. Time in tight range (TITR) has also been proposed for clinical use, spanning largely normal glucose levels of 70-140 mg/dL. However, keeping such narrow glucose ranges can be challenging, and understanding the factors modulating TITR can help achieve these tight glycemic targets. Our real-life study aimed to evaluate the relationship between average glucose (AG) and TIR/TITR in a large cohort (n = 22,006) of CGM users, divided into four groups: self-identified as having type 1 diabetes (T1D) treated with insulin using multiple daily injections (MDI) or pumps; type 2 diabetes (T2D) on MDI or insulin pumps; T2D on basal insulin only; and T2D not on insulin treatment. The T2D groups, regardless of treatment type, displayed the highest TIR and TITR values, associated with lowest glycemic variability measured as glucose coefficient of variation (CV; 23-30%). The T1D group showed the lowest TIR and TITR, associated with the highest CVs (36-38%). Overall, higher CV was associated with lower TIR and TITR for AG values below 180 and 140 mg/dL, respectively, with the reverse holding true for AG values above these thresholds. The discordance between AG and TIR/TITR was less pronounced in T2D compared with T1D, attributed to lower CV in the former group. It was also observed that TITR has advantages over TIR for assessing glycemia status and progress toward more stringent A1C, particularly when approaching normal glucose levels. The data detail how CV affects the AG relationship with TIR/TITR, which has implications for CGM interpretation. In many instances TITR, rather than TIR, may be preferable to employ once AG falls below 140 mg/dL and near-normal glucose levels are required clinically.

You may delay, but time will not. Beta cells lost are never found again: a case for timely initiation of basal insulin in type 2 diabetes

Since its first use just over a century ago, insulin treatment has evolved dramatically, such that the molecules are physiologic in nature, and treatment can now closely resemble the natural hormone response over 24 hours. Newer, longer-acting basal insulin analogs have provided insulin therapies with improved characteristics and, therefore, ease of use, and can readily be incorporated as part of routine treatment for type 2 diabetes (T2D), but evidence suggests that insulin remains underused in people with T2D. We review the barriers to initiation of basal insulin and the education needed to address these barriers, and we provide practical pointers, supported by evidence, for primary care physicians and advanced practice providers to facilitate timely initiation of basal insulin in the people with T2D who will benefit from such treatment.

Impact of Preoperative Diabetes Mellitus on Postoperative Outcomes in Elective Pancreatic Surgery and Its Implications for Prehabilitation Practice

OBJECTIVES

Patients with pancreatic disease(s) have a high risk of developing diabetes mellitus (DM). Diabetes mellitus is associated with adverse postoperative outcomes. This study aimed to investigate the prevalence and effects of DM on postoperative outcomes in pancreatic surgery.

METHODS

Subgroup analysis of a prospective cohort study conducted at an academic hospital. Patients undergoing pancreatoduodenectomy between January 2019 and November 2022 were included and screened for DM preoperatively using glycated hemoglobin (HbA1c). New-onset DM was diagnosed based on HbA1c ≥ 6.5% (48 mmol/mol). Postoperative outcomes were compared between patients with and without DM.

RESULTS

From 117 patients, 29 (24.8%) were given a diagnosis of DM, and of those, 5 (17.2%) were diagnosed with new-onset DM, and 15 (51.8%) displayed poorly controlled preoperative DM (HbA 1c ≥ 7% [53 mmol/mol]). The incidence of surgical site infections (48.3% vs 27.3% in the non-DM group; P = 0.04) was higher for patients with DM. This association remained significant after adjusting for confounders (odds ratio, 2.60 [95% confidence interval, 1.03-6.66]; P = 0.04).

CONCLUSIONS

One-quarter of the patients scheduled for pancreatoduodenectomy had DM; over half of them had poor glycemic control. The association between DM status and surgical site infections revealed in this study emphasizes the importance of adequate preoperative glycemic control.

A Systematic Review of the Effects of Provider Bias on Health in Youth and Young Adults with Type 1 Diabetes

PURPOSE OF REVIEW

Although pervasive inequities in the health outcomes of youth and young adults with type 1 diabetes (T1D) exist, the role of provider bias in these inequities is not well-understood. The purpose of this review is to synthesize evidence from existing studies on the associations between patient characteristics, provider bias, and patient health.

RECENT FINDINGS

Fourteen articles were included. Determining the extent of the effects of provider bias on patient health is limited by a lack of consensus on its definition. Experiences of provider bias (e.g., shaming, criticism) negatively affects self-esteem, relationships with medical providers, and depressive symptoms. Provider bias also impacts diabetes technology recommendations, insulin regimen intensity, and risk for life-threatening T1D complications. Future studies are needed to develop questionnaires and interviews that better account for diverse experiences and interpretations of bias in T1D healthcare. More research is also needed to investigate mitigating factors to reduce provider bias as a way to improve psychological and physical health in individuals with T1D.

Short-term glucose variability as a determinant of the healing rate of diabetic foot ulcer: A retrospective study

BACKGROUND

The aim of this study was to describe the clinical characteristics of people with diabetic foot ulcer (DFU) according to glucose variability (GV) and to investigate the relationship between GV and DFU outcome in a population with type 2 diabetes (T2D) and DFU.

METHODS

This is a retrospective study of 300 individuals aged 64.3 years (181 males) treated for DFU in a tertiary-care center with a regular follow-up for 6 months. Laboratory measurements and clinical assessments were collected at baseline. According to the coefficient of variation (CV) cut-off (≥36%), people were divided into two groups (low and high GV).

RESULTS

Compared with low GV group (n = 245), high GV group (n = 55) had significant longer duration of diabetes [low vs high GV, mean ± Standard Deviation (SD), 17.8 ± 11.8 vs 22.4 ± 10.8, P = 0.012], higher levels of glycated haemoglobin [median (IQR), 7.4 (6.6, 8.8) vs 8.2 (7.0, 9.6), P = 0.010] and urinary albumin excretion [25.2 (11.9, 77.0) vs 48.0 (23.2, 106.0), P = 0.031]. Moreover, 10 days self-monitoring of blood glucose-derived glycemic metrics were significantly different between groups. No differences among clinical features were found. The multiple logistic regression analysis identified CV and SD as negative predictors of healing.

CONCLUSIONS

In a population of people with T2D and DFU treated in a tertiary-care center, individuals with high GV had a 3-fold higher risk of healing failure, as compared with those with low GV. CV and SD were related to poor healing within 6 months follow-up.

Glycemic outcomes and patient satisfaction and self-management improves in transition from standard to virtual multidisciplinary care

AIMS

With advances in cloud-based technologies, there has been a rise in remote T1D care. We hypothesized that transitioning T1DM care to a virtual, multidisciplinary clinic could improve measures beyond HbA1c.

METHODS

To assess the impact of transitioning from standard to virtual T1DM care, we evaluated glycemic measures and patient reported outcomes.

RESULTS

Sixty-one adults with T1DM were included, with mean age 40.2 ± 13.5 years and diabetes duration 16.9 ± 9.0 years. Most patients were treated with insulin pumps and CGM. The number of annual diabetes care encounters rose from 2.1 ± 4.2 to 12.8 ± 5.5. Baseline HbA1c was 7.9 ± 1.6 %(63 ± 16.9 mmol/mol), declining to 7.3 ± 1.1 %(56 ± 8.5 mmol/mol) and 7.1 ± 1.0 %(54 ± 7.7 mmol/mol) at 6 and 12 months respectively (p < 0.001 for both). In parallel, TIR improved from 63.1 ± 19.3 % to 69.2 ± 13.8 % (p < 0.001) and 67.5 ± 19.4 % (p = 0.03) at 6 and 12 months respectively, while TBR declined. Scores from validated diabetes treatment and self-management questionnaires rose significantly and these rises were associated with a reduction in HbA1c, the latter score was also associated with increased TIR. There was a trend toward a correlation between encounter frequency and improvement in HbA1c and TIR.

CONCLUSIONS

Transitioning from standard to virtual, coordinated, multidisciplinary T1DM care is associated with increased visit frequency, improving glycemic control, treatment satisfaction and self-care behaviors.

Efficacy of a Hybrid Closed-Loop Solution in Patients With Excessive Time in Hypoglycaemia: A Post Hoc Analysis of Trials With DBLG1 System

BACKGROUND

Automated insulin delivery is an efficient treatment for patients with type 1 diabetes. Little is known on its impact on patients with excessive time in hypoglycaemia.

METHODS

We performed a post hoc analysis of three randomized control trials that used the DBLG1 (Diabeloop Generation 1) hybrid closed-loop solution. Patients whose time below 70 mg/dL during baseline, open-loop phase exceeded 5% were selected. The outcomes were the differences between the closed-loop and the open-loop phases in time in various ranges and Glycemia Risk Index (GRI).

RESULTS

We identified 45 patients exhibiting ≥5% of time below 70 mg/dL during the open-loop phase. Under closed-loop, the time in hypoglycaemia (54 to <70 mg/dL) dropped from 7.9% (SD 2.4) to 3.2% (SD 1.6) (difference -4.7% [-5.3; -4.1], P < 10-4). The time below 54 mg/dL decreased from 1.9% (SD 1.3) to 0.8% (SD 0.7) (difference -0.9% [-1.4; -0.8], P < 10-4). The time in range (TIR 70-180 mg/dL) improved from 63.3 (SD 9.5) to 68.2% (SD 8.2) (difference 5.1% [2.9; 7.0], P < 10-4). The GRI improved from 51.2 (SD 12.4) to 38.0 (SD 10.9) (difference 13.2 [10.4; 16.0], P < 10-4).

CONCLUSION

DBLG1 decreased time in hypoglycaemia by more than 50% even in patients with excessive time in hypoglycaemia at baseline, while also improving both TIR and GRI, under real-life conditions. The improvement in GRI (13.2%) exceeded that of the improvement in TIR (5.1%) indicating that in this data set, GRI was more sensitive than TIR to the improvement in glycaemia achieved with closed-loop. These results support the safety and efficacy of this treatment.

Effect of cinnamon spice on continuously monitored glycemic response in adults with prediabetes: a 4-week randomized controlled crossover trial

BACKGROUND

Previous clinical studies showing that cinnamon spice lowers blood glucose concentrations had inconsistent results.

OBJECTIVES

To determine the effect of daily cinnamon spice supplementation in an amount commonly used for seasoning on glucose concentrations in adults with obesity and prediabetes.

METHODS

Following a 2-wk run-in period of maintaining a low polyphenol/fiber diet, 18 participants with obesity and prediabetes underwent a 10-wk randomized, controlled, double-blind, crossover trial (mean age 51.1 y; mean fasting plasma glucose 102.9 mg/dL). The participants were randomly assigned to take cinnamon (4 g/d) or placebo for 4-wk, followed by a 2-wk washout period, and then crossed over to the other intervention for an additional 4-wk. Glucose changes were measured with continuous glucose monitoring. Oral glucose tolerance testing immediately following ingestion of cinnamon or placebo was performed at 4-time points to assess their acute effects both at the baseline and end of each intervention phase. Digestive symptom logs were obtained daily.

RESULTS

There were 694 follow-up days with 66,624 glucose observations. When compared with placebo, 24-h glucose concentrations were significantly lower when cinnamon was administered [mixed-models; effect size (ES) = 0.96; 95 % confidence interval (CI): -2.9, -1.5; P < 0.001]. Similarly, the mean net-area-under-the-curve (netAUC) for glucose was significantly lower than for placebo when cinnamon was given (over 24 h; ES = -0.66; 95 % CI: 2501.7, 5412.1, P = 0.01). Cinnamon supplementation resulted in lower glucose peaks compared with placebo (Δpeak 9.56 ± 9.1 mg/dL compared with 11.73 ± 8.0 mg/dL; ES = -0.57; 95 % CI: 0.8, 3.7, P = 0.027). Glucose-dependent-insulinotropic-polypeptide concentrations increased during oral glucose tolerance testing + cinnamon testing (mixed-models; ES = 0.51; 95 % CI: 1.56, 100.1, P = 0.04), whereas triglyceride concentrations decreased (mixed-models; ES = 0.55; 95 % CI: -16.0, -1.6, P = 0.02). Treatment adherence was excellent in both groups (cinnamon: 97.6 ± 3.4 % compared with placebo: 97.9 ± 3.7 %; ES = -0.15; 95 % CI: -1.8, 0.2, P = 0.5). No differences were found in digestive symptoms (abdominal pain, borborygmi, bloating, excess flatus, and stools/day) between cinnamon and placebo groups.

CONCLUSIONS

Cinnamon, a widely available and low-cost supplement, may contribute to better glucose control when added to the diet in people who have obesity-related prediabetes. This trial was registered at clinicaltrials.gov as NCT04342624.

Assessing the temporal within-day glycemic variability during hospitalization in patients with type 2 diabetes patients using continuous glucose monitoring: a retrospective observational study

AIMS

Frequent and extensive within-day glycemic variability (GV) in blood glucose levels may increase the risk of hypoglycemia and long-term mortality in hospitalized patients with diabetes. We aimed to assess the amplitude and frequency of within-day GV in inpatients with type 2 diabetes and to explore the factors influencing within-day GV.

METHODS

We conducted a single-center, retrospective observational study by analyzing hospital records and 10-day real-time continuous glucose monitoring data. Within-day GV was assessed using the coefficient of variation (%CV). The primary outcome was the amplitude and frequency of within-day GV. The frequency of within-day GV was assessed by the consecutive days (CD) of maintaining within the target %CV range after first reaching it (CD after first reaching the target) and the maximum consecutive days of maintaining within the target %CV range (Max-CD). The target %CV range was less than 24.4%. We evaluated the factors influencing within-day GV using COX regression and Poisson regression models.

RESULTS

A total of 1050 cases were analyzed, of whom 86.57% reduced the amplitude of within-day GV before the sixth day of hospitalization. Of the 1050 hospitalized patients, 66.57% stayed within the target %CV range for less than two days after first reaching the target and 69.71% experienced a Max-CD of fewer than four days. Reducing the average postprandial glucose excursion (hazard ratio [HR]: 0.81, 95% confidence interval [CI]: 0.77-0.85; incidence rate ratios [IRR]: 0.72, 95% CI: 0.69-0.74) and the use of α-glucosidase inhibitors (IRR: 1.1, 95% CI: 1.01-1.18) and glucagon-like peptide-1 agonist (IRR: 1.30, 95% CI: 1.02-1.65) contributed to reducing the amplitude and decreasing the frequency of within-day GV. However, the use of insulin (HR: 0.64, 95% CI: 0.55-0.75; IRR: 0.86, 95% CI: 0.79-0.93) and glinide (HR: 0.47, 95% CI: 0.31-0.73; IRR: 0.84, 95% CI: 0.73-0.97) may lead to an increased frequency of within-day GV.

CONCLUSIONS

An increasing frequency of within-day GV was observed during the hospitalization in patients with type 2 diabetes, despite the effective reduction in the amplitude of within-day GV. Using medications designed to lower postprandial blood glucose could contribute to minimize the risk of frequent within-day GV.

The Discrepancy Between Hemoglobin A1c and Glucose Management Indicators in 26 Patients Treated With Continuous Glucose Monitoring in an Internal Medicine Residency Clinic

We conducted a retrospective observational cohort study between 2020 and 2023 in 26 patients with type 1 and type 2 diabetes mellitus (DM) who were using 3-4 injections per day of insulin and were monitored by continuous glucose monitoring (CGM). The goal of this retrospective observational cohort study is to compare these two metrics in an internal medicine community primary care residency clinic. We used CGM devices, Dexcom G6 and G7, and Freestyle Libre 3. The goal was to compare the patient's hemoglobin A1c (HbA1c) taken during their clinic visit by phlebotomy as a marker for diabetic control with an estimated HbA1c glucose management indicator (GMI) derived from the 30-day CGM readings. HbA1c is derived from the blood, while the GMI value is derived from the interstitial fluid. Both parameters were taken within 30 days of each other. GMI was taken in the last 30 days. We excluded patients with known anemia, chronic kidney disease, polycythemia, cirrhosis of the liver, or metabolic dysfunction associated with steatohepatitis (MASH) because disease states can affect the measured HbA1c. Also, pregnant and African American patients were excluded. We concluded the measured HbA1c was 0.34% (4 mmol/mol) higher than the CGM-derived GMI. The relationship between factors that affect glycemic control was discussed in the article, as well as the future utilization of them in improving diabetic control and management. As the use of CGM continues to grow, addressing differences between laboratory-measured HbA1c and CGM-derived GMI is critical.

Neuromuscular electrical stimulation changes glucose, but not its variability in type 2 diabetes: a randomized clinical trial

Neuromuscular electrical stimulation (NMES) can be an alternative to conventional exercising. This randomized clinical trial evaluated the effect of NMES in type 2 diabetes patients. Twenty-eight individuals with type 2 diabetes were assigned to NMES (n=14) or NMES-placebo (n=14) applied to knee extensor muscles for 60 minutes. Glucose variability, microvascular function and endothelial function were evaluated through continuous glucose monitoring system, near infrared spectroscopy and flow-mediated dilatation, respectively. Glucose levels (mg/dl) decreased 2h (184 ± 11 vs 223 ±15), 3h (179 ± 12 vs 219 ±14) and 4h (177 ± 12 vs 212 ±12) after NMES, in comparison to NMES-placebo. No differences in glucose variability were found: coefficient of variation (%) at 0-6h (11.4±1.3 vs 11.4±1.2), 6-12h (9.8±1.0 vs 11.6±1.6), 12-18h (15.5±2.0 vs 11.4±2.1), 18-24h (12.8±2.3 vs 10.0±1.6); standard deviation (mg/dl) at 0-6h (21.6±2 vs 24.6±3.5), 6-12h (19.5±1.8 vs 20.3±2.8), 12-18h (29.9±3.5 vs 21.3±2.8),18-24h (22.8±4.1 vs 16.6±2.0) and mean amplitude of glycemic excursions (mg/dl) 54.9±25.0 vs 70.3±35.7. Endothelial and microvascular functions did not change. In conclusion, one acute NMES session was strong enough to trigger glucose reduction in individuals with type 2 DM, but it failed to induce any significant change in glucose variability, endothelial and microvascular functions.