An integrated wearable differential microneedle array for continuous glucose monitoring in interstitial fluids

Monitoring biomarkers in human interstitial fluids (ISF) using microneedle sensors has been extensively studied. However, most of the previous studies were limited to simple in vitro demonstrations and lacked system integration and analytical performance. Here we report a miniaturized, high-precision, fully integrated wearable electrochemical microneedle sensing device that works with a customized smartphone application to wirelessly and in real-time monitor glucose in human ISF. A microneedle array fabrication method is proposed which enables multiple individually addressable, regionally separated sensing electrodes on a single microneedle system. As a demonstration, a glucose sensor and a differential sensor are integrated in a single sensing patch. The differential sensing electrodes can eliminate common-mode interference signals, thus significantly improving the detection accuracy. The basic mechanism of microneedle penetration into the skin was analyzed using the finite element method (FEM). By optimizing the structure of the microneedle, the puncture efficiency was improved while the puncture force was reduced. The electrochemical properties, biocompatibility, and system stability of the microneedle sensing device were characterized before human application. The test results were closely correlated with the gold standard (blood). The platform can be used not only for glucose detection, but also for various ISF biomarkers, and it expands the potential of microneedle technology in wearable sensing.

Tailored diffusion limiting membrane for microneedle glucose sensors with wide linear range

Continuous glucose monitoring is very important to daily blood glucose control in diabetic patients, but its accuracy is limited by the narrow linear range of the response of biosensor to the glucose concentration because of the oxygen starvation in tissue and the limited maximum conversion rate of glucose oxidase. In this work, a biocompatible diffusion limiting membrane based on two medical-grade polyurethanes is developed via blending modification to restrict the diffusion flux of glucose to match the oxygen concentration and the maximum conversion rate. The expansiveness of the linear range for the nanomaterials-modified electrode in the glucose biosensor can be achieved through the regulation of two polyurethanes, the solvent, and the thickness of the membrane. In addition, the mass transport of hydrogen peroxide and interfering substances is also limited of the membrane. The in vitro experiments demonstrated that the membrane-modified microneedle biosensor exhibited a rapid response to the concentration variation of glucose, a wide linear range that is sufficient to cover the blood concentration of healthy and diabetic people, the ability to resist the oxygen concentration fluctuation and interfering substances, good reproducibility and long-term stability. The custom wearable electrochemical system, possessing these characteristics, has been proven to accurately monitor the blood concentration in a living rat in real time. This demonstrates a significant potential for application in both daily and clinical blood glucose monitoring.

Continuous glucose monitoring in adults with type 2 diabetes: a systematic review and meta-analysis

AIMS/HYPOTHESIS

Continuous glucose monitoring (CGM) is increasingly used in the treatment of type 2 diabetes, but the effects on glycaemic control are unclear. The aim of this systematic review and meta-analysis is to provide a comprehensive overview of the effect of CGM on glycaemic control in adults with type 2 diabetes.

METHODS

We performed a systematic review using Embase, MEDLINE, Web of Science, Scopus and ClinicalTrials.gov from inception until 2 May 2023. We included RCTs investigating real-time CGM (rtCGM) or intermittently scanned CGM (isCGM) compared with self-monitoring of blood glucose (SMBG) in adults with type 2 diabetes. Studies with an intervention duration <6 weeks or investigating professional CGM, a combination of CGM and additional glucose-lowering treatment strategies or GlucoWatch were not eligible. Change in HbA1c and the CGM metrics time in range (TIR), time below range (TBR), time above range (TAR) and glycaemic variability were extracted. We evaluated the risk of bias using the Cochrane risk-of-bias tool version 2. Data were synthesised by performing a meta-analysis. We also explored the effects of CGM on severe hypoglycaemia and micro- and macrovascular complications.

RESULTS

We found 12 RCTs comprising 1248 participants, with eight investigating rtCGM and four isCGM. Compared with SMBG, CGM use (rtCGM or isCGM) led to a mean difference (MD) in HbA1c of -3.43 mmol/mol (-0.31%; 95% CI -4.75, -2.11, p<0.00001, I2=15%; moderate certainty). This effect was comparable in studies that included individuals using insulin with or without oral agents (MD -3.27 mmol/mol [-0.30%]; 95% CI -6.22, -0.31, p=0.03, I2=55%), and individuals using oral agents only (MD -3.22 mmol/mol [-0.29%]; 95% CI -5.39, -1.05, p=0.004, I2=0%). Use of rtCGM showed a trend towards a larger effect (MD -3.95 mmol/mol [-0.36%]; 95% CI -5.46 to -2.44, p<0.00001, I2=0%) than use of isCGM (MD -1.79 mmol/mol [-0.16%]; 95% CI -5.28, 1.69, p=0.31, I2=64%). CGM was also associated with an increase in TIR (+6.36%; 95% CI +2.48, +10.24, p=0.001, I2=9%) and a decrease in TBR (-0.66%; 95% CI -1.21, -0.12, p=0.02, I2=45%), TAR (-5.86%; 95% CI -10.88, -0.84, p=0.02, I2=37%) and glycaemic variability (-1.47%; 95% CI -2.94, -0.01, p=0.05, I2=0%). Three studies reported one or more events of severe hypoglycaemia and macrovascular complications. In comparison with SMBG, CGM use led to a non-statistically significant difference in the incidence of severe hypoglycaemia (RR 0.66, 95% CI 0.15, 3.00, p=0.57, I2=0%) and macrovascular complications (RR 1.54, 95% CI 0.42, 5.72, p=0.52, I2=29%). No trials reported data on microvascular complications.

CONCLUSIONS/INTERPRETATION

CGM use compared with SMBG is associated with improvements in glycaemic control in adults with type 2 diabetes. However, all studies were open label. In addition, outcome data on incident severe hypoglycaemia and incident microvascular and macrovascular complications were scarce.

REGISTRATION

This systematic review was registered on PROSPERO (ID CRD42023418005).

Mixed methods study on the feasibility of implementing periodic continuous glucose monitoring among individuals with type 2 diabetes mellitus in a primary care setting

Background

Health care professionals (HCPs) play a central role in leveraging technologies to support individuals with diabetes. This mixed-method study was completed to determine the feasibility of implementing periodic continuous glucose monitoring (CGM) in a primary care setting.

Aim

This study aimed to evaluate and describe the experiences of using periodic CGM with data visualization tools in patients with type 2 diabetes to foster a person-centered approach in a primary care setting.

Methods

Fifty outpatients aged ≥18 years, diagnosed with type 2 diabetes, and with a disease duration of at least 2 years were included in this study. Data were collected from April 2021 to January 2022. Patients completed a single period of sensor measurements for 28 days and a diabetes questionnaire about feelings and experiences of health care. HbA1c was also measured. A focus group interview was conducted to evaluate and describe the HCPs experiences of using periodic CGM.

Results

Patients reported to HCPs that the CGM device was comfortable to wear and noted that LibreView was easy to use when scanning the sensor to obtain and visualize the glucose levels and trends. Data availability of CGM data was >70 %.Clinical observations revealed a mean reduction in HbA1c, mmol/mol from 60.06 [7.65 %] at baseline to 55.42 [7.20 %] after 4 weeks (p < 0.001). Two categories were identified: 1) Fostering dialogue on self-care and 2) Promoting understanding.

Conclusions

The HCPs and participants in this study had a positive experience or viewed the implementation of periodic CGM with data visualization tools as a positive experience and appeared to be feasible for implementation in a primary care setting.

Mean Glucose and Gestational Weight Gain as Predictors of Large-for-Gestational-Age Infants in Pregnant Women with Type 1 Diabetes Using Continuous Glucose Monitoring

Aims/hypothesis: To compare glycemic metrics during pregnancy between women with type 1 diabetes (T1D) delivering large-for-gestational-age (LGA) and appropriate-for-gestational-age (AGA) infants, and to identify predictors of LGA infants. Materials and Methods: A cohort study including 111 women with T1D using intermittently scanned continuous glucose monitoring from conception until delivery. Average sensor-derived metrics: mean glucose, time in range in pregnancy (TIRp), time above range in pregnancy, time below range in pregnancy, and coefficient of variation throughout pregnancy and in pregnancy intervals of 0-10, 11-21, 22-33, and 34-37 weeks were compared between women delivering LGA and AGA infants. Predictors of LGA infants were sought for. Infant growth was followed until 3 months postdelivery. Results: In total, 53% (n = 59) delivered LGA infants. Mean glucose decreased during pregnancy in both groups, with women delivering LGA infants having a 0.4 mmol/L higher mean glucose from 11-33 weeks (P = 0.01) compared with women delivering AGA infants. Mean TIRp >70% was obtained from 34 weeks in women delivering LGA infants and from 22-33 weeks in women delivering AGA infants. Independent predictors for delivering LGA infants were mean glucose throughout pregnancy and gestational weight gain. At 3 months postdelivery, infant weight was higher in infants born LGA compared with infants born AGA (6360 g ± 784 and 5988 ± 894, P = 0.04). Conclusions/interpretations: Women with T1D delivering LGA infants achieved glycemic targets later than women delivering AGA infants. Mean glucose and gestational weight gain were independent predictors for delivering LGA infants. Infants born LGA remained larger postdelivery compared with infants born AGA.

Continuous glucose monitoring with structured education in adults with type 2 diabetes managed by multiple daily insulin injections: a multicentre randomised controlled trial

AIMS/HYPOTHESIS

The aim of this study was to compare the effectiveness of stand-alone intermittently scanned continuous glucose monitoring (isCGM) with or without a structured education programme and blood glucose monitoring (BGM) in adults with type 2 diabetes on multiple daily insulin injections (MDI).

METHODS

In this 24 week randomised open-label multicentre trial, adults with type 2 diabetes on intensive insulin therapy with HbA1c levels of 58-108 mmol/mol (7.5-12.0%) were randomly assigned in a 1:1:1 ratio to isCGM with a structured education programme on adjusting insulin dose and timing according to graphical patterns in CGM (intervention group), isCGM with conventional education (control group 1) or BGM with conventional education (control group 2). Block randomisation was conducted by an independent statistician. Due to the nature of the intervention, blinding of participants and investigators was not possible. The primary outcome was change in HbA1c from baseline at 24 weeks, assessed using ANCOVA with the baseline value as a covariate.

RESULTS

A total of 159 individuals were randomised (n=53 for each group); 148 were included in the full analysis set, with 52 in the intervention group, 49 in control group 1 and 47 in control group 2. The mean (± SD) HbA1c level at baseline was 68.19±10.94 mmol/mol (8.39±1.00%). The least squares mean change (± SEM) from baseline HbA1c at 24 weeks was -10.96±1.35 mmol/mol (-1.00±0.12%) in the intervention group, -6.87±1.39 mmol/mol (-0.63±0.13%) in control group 1 (p=0.0367 vs intervention group) and -6.32±1.42 mmol/mol (-0.58±0.13%) in control group 2 (p=0.0193 vs intervention group). Adverse events occurred in 28.85% (15/52) of individuals in the intervention group, 26.42% (14/53) in control group 1 and 48.08% (25/52) in control group 2.

CONCLUSIONS/INTERPRETATION

Stand-alone isCGM offers a greater reduction in HbA1c in adults with type 2 diabetes on MDI when education on the interpretation of graphical patterns in CGM is provided.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04926623.

FUNDING

This study was supported by Daewoong Pharmaceutical Co., Ltd.

Impact of macronutrients intake on glycemic homeostasis of preterm infants: evidence from continuous glucose monitoring

Nutritional intake could influence the blood glucose profile during early life of preterm infants. We investigated the impact of macronutrient intake on glycemic homeostasis using continuous glucose monitoring (CGM). We analyzed macronutrient intake in infants born ≤ 32 weeks gestational age (GA) and/or with birth weight ≤ 1500 g. CGM was started within 48 h of birth and maintained for 5 days. Mild and severe hypoglycemia were defined as sensor glucose (SG) < 72 mg/dL and <47 mg/dL, respectively, while mild and severe hyperglycemia were SG > 144 mg/dL and >180 mg/dL. Data from 30 participants were included (age 29.9 weeks (29.1; 31.2), birthweight 1230.5 g (1040.0; 1458.6)). A reduced time in mild hypoglycemia was associated to higher amino acids intake (p = 0.011) while increased exposure to hyperglycemia was observed in the presence of higher lipids intake (p = 0.031). The birthweight was the strongest predictor of neonatal glucose profile with an inverse relationship between the time spent in hyperglycemia and birthweight (p = 0.007).  Conclusions: Macronutrient intakes influence neonatal glucose profile as described by continuous glucose monitoring. CGM might contribute to adjust nutritional intakes in preterm infants. What is Known: • Parenteral nutrition may affect glucose profile during the first days of life of preterm infants. What is New: • Continuous glucose monitoring describes the relationship between daily parenteral nutrient intakes and time spent in hypo and hyperglycemic ranges.

A Comparison of the Rates of Clock-Based Nocturnal Hypoglycemia and Hypoglycemia While Asleep Among People Living with Diabetes: Findings from the Hypo-METRICS Study

Introduction: Nocturnal hypoglycemia is generally calculated between 00:00 and 06:00. However, those hours may not accurately reflect sleeping patterns and it is unknown whether this leads to bias. We therefore compared hypoglycemia rates while asleep with those of clock-based nocturnal hypoglycemia in adults with type 1 diabetes (T1D) or insulin-treated type 2 diabetes (T2D). Methods: Participants from the Hypo-METRICS study wore a blinded continuous glucose monitor and a Fitbit Charge 4 activity monitor for 10 weeks. They recorded details of episodes of hypoglycemia using a smartphone app. Sensor-detected hypoglycemia (SDH) and person-reported hypoglycemia (PRH) were categorized as nocturnal (00:00-06:00 h) versus diurnal and while asleep versus awake defined by Fitbit sleeping intervals. Paired-sample Wilcoxon tests were used to examine the differences in hypoglycemia rates. Results: A total of 574 participants [47% T1D, 45% women, 89% white, median (interquartile range) age 56 (45-66) years, and hemoglobin A1c 7.3% (6.8-8.0)] were included. Median sleep duration was 6.1 h (5.2-6.8), bedtime and waking time ∼23:30 and 07:30, respectively. There were higher median weekly rates of SDH and PRH while asleep than clock-based nocturnal SDH and PRH among people with T1D, especially for SDH <70 mg/dL (1.7 vs. 1.4, P < 0.001). Higher weekly rates of SDH while asleep than nocturnal SDH were found among people with T2D, especially for SDH <70 mg/dL (0.8 vs. 0.7, P < 0.001). Conclusion: Using 00:00 to 06:00 as a proxy for sleeping hours may underestimate hypoglycemia while asleep. Future hypoglycemia research should consider the use of sleep trackers to record sleep and reflect hypoglycemia while asleep more accurately. The trial registration number is NCT04304963.

Application and management of continuous glucose monitoring in diabetic kidney disease

Diabetic kidney disease (DKD) is a common complication of diabetes mellitus that contributes to the risk of end-stage kidney disease (ESKD). Wide glycemic var-iations, such as hypoglycemia and hyperglycemia, are broadly found in diabetic patients with DKD and especially ESKD, as a result of impaired renal metabolism. It is essential to monitor glycemia for effective management of DKD. Hemoglobin A1c (HbA1c) has long been considered as the gold standard for monitoring glycemia for > 3 months. However, assessment of HbA1c has some bias as it is susceptible to factors such as anemia and liver or kidney dysfunction. Continuous glucose monitoring (CGM) has provided new insights on glycemic assessment and management. CGM directly measures glucose level in interstitial fluid, reports real-time or retrospective glucose concentration, and provides multiple glycemic metrics. It avoids the pitfalls of HbA1c in some contexts, and may serve as a precise alternative to estimation of mean glucose and glycemic variability. Emerging studies have demonstrated the merits of CGM for precise monitoring, which allows fine-tuning of glycemic management in diabetic patients. Therefore, CGM technology has the potential for better glycemic monitoring in DKD patients. More research is needed to explore its application and management in different stages of DKD, including hemodialysis, peritoneal dialysis and kidney transplantation.

Disparities in prevalence and treatment of diabetes, cardiovascular and chronic kidney diseases - Recommendations from the taskforce of the guideline workshop

There is a mounting clinical, psychosocial, and socioeconomic burden worldwide as the prevalence of diabetes, cardiovascular disease (CVD), and chronic kidney disease (CKD) continues to rise. Despite the introduction of therapeutic interventions with demonstrated efficacy to prevent the development or progression of these common chronic diseases, many individuals have limited access to these innovations due to their race/ethnicity, and/or socioeconomic status (SES). However, practical guidance to providers and healthcare systems for addressing these disparities is often lacking. In this article, we review the prevalence and impact of healthcare disparities derived from the above-mentioned chronic conditions and present broad-based recommendations for improving access to quality care and health outcomes within the most vulnerable populations.

Switching from Intermittently Scanned Continuous Glucose Monitoring to Real-Time Continuous Glucose Monitoring with a Predictive Urgent Low Soon Alert Reduces Exposure to Hypoglycemia

Differences in the effectiveness of real-time continuous glucose monitoring (rtCGM) and intermittently scanned continuous glucose monitoring (isCGM) in type 1 diabetes (T1D) are reported. The impact on percent time in range of switching from an isCGM with glucose threshold-based optional alerts only (FreeStyle Libre 2 [FSL2]) to an rtCGM (Dexcom G7) with an urgent low soon predictive alert was assessed, alongside other secondary outcomes including hemoglobin A1c (HbA1c) and other continuous glucose monitoring metrics. Adults with T1D using FSL2 were switched to Dexcom G7 for 12 weeks. HbA1c and continuous glucose data during FSL2 and Dexcom G7 use were compared. Data from 29 participants (aged 44.8 ± 16.5 years, 12 male and 17 female) were analyzed. After switching to rtCGM, participants spent less time in hypoglycemia below 3.9 mmol/L (70 mg/dL) (3.0% [1.0%, 5.0%] vs. 2.0% [1.0%, 3.0%], P = 0.006) and had higher percentage achievement of time below 3.9 mmol/L (70 mg/dL) of <4% (55.2% vs. 82.8%, P = 0.005). Coefficient of variation was lower (39.3 ± 6.6% vs. 37.2 ± 5.6%, P = 0.008). In conclusion, adults with T1D who switched from isCGM to rtCGM may benefit from reduced exposure to hypoglycemia and glycemic variability.

Continuous Glucose Monitoring-Derived Glucometrics in Adults with Type 1 Diabetes When Switching Basal Insulins

Context: Limited evidence is available on the real-world effect of insulin degludec (IDeg) in type 1 diabetes (T1D), using continuous glucose monitoring (CGM)-derived metrics. Objective: To assess the real-world effect of switching to IDeg from other long-acting insulins on time in ranges (TIRs) measured by CGM, metabolic control, and insulin dose for people with T1D. Design: This retrospective multicenter study encompassed five time points during a 12-month pre-switch of IDeg and a 12-month follow-up period. For each visit, clinical and CGM data were collected to evaluate temporal trends in glycemic outcomes. Participants: Of 753 persons with T1D who were assessed for eligibility, 486 persons were included, mostly men (61.5%), 47.4 (16.9) years old and diabetes duration of 23.8 (14.2) years at IDeg-initiation. Main Outcome Measure: Primary outcome was the evolution of percent TIR (70-180 mg/dL or 3.9-10.0 mmol/L, TIR) before versus after switch to IDeg. Results: TIR over 24 h increased at 12 months versus baseline (56.7% vs. 52.3%, P < 0.001), mostly during daytime. Time <54 mg/dL (<3.0 mmol/L) over 24 h decreased at 12 months versus baseline (2.02% vs. 2.86%, P < 0.001), mostly during nighttime. Glycated hemoglobin (7.9% vs. 8.1%, P < 0.001) and coefficient of variation (40.0% vs. 41.5%, P < 0.001) improved at 12 months versus baseline. Mean daily basal, bolus and total insulin doses decreased at 12 months (P < 0.001 for all vs. baseline). Conclusions: This retrospective real-world study reports that switching basal insulin significantly improved time spent in glucometric ranges and glycemic variability in the studied population of people with T1D. Clinical Trial Registration number: NCT05434559.

Effect of Arterialization on Venous Blood Glucose Concentrations and Implications for Observed Continuous Glucose Monitoring Accuracy

Background: Heating of the arm and/or hand ("arterialization") is sometimes used in continuous glucose monitoring (CGM) performance studies with the reported aim of reducing differences between venous and capillary glucose concentrations. In this study, the effect of heating on venous glucose concentrations and CGM accuracy was investigated. Methods: A heating pad set to 50°C (122°F) was used with 20 participants to heat either the dominant or nondominant arm and hand. Venous and capillary samples were obtained every 15 min on both arms throughout each of three 6-h glucose challenges. CGM sensors were worn on each upper arm for each of the three visits. Results: Heating of the arm led to a median increase in venous glucose concentrations of +1.4%. No similar effect on capillary concentrations was observed. As a result, the median capillary to venous difference decreased from +5.9% in the nonheated arm to +4.2% in the heated arm. CGM accuracy observed in this study was affected by the selection of heated venous, nonheated venous, or capillary glucose concentrations as comparator data. The heating effect was more pronounced with rapidly decreasing glucose concentrations. Temperatures on the skin did not exceed 40°C (104°F). No adverse events or protocol deviations were associated with the use of the heating pad. Conclusions: Heating of the arm led to a small increase in venous glucose concentrations, but venous concentrations did not reach the level of capillary glucose concentrations. CGM accuracy observed in this study varied depending on the selected comparator data. This study was registered at the German Clinical Trials Register (DRKS00031197).

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.

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.

Exploring Technology's Influence on Health Behaviours and Well-being in Type 1 Diabetes: a Review

PURPOSE OF REVIEW

Maintaining positive health behaviours promotes better health outcomes for people with type 1 diabetes (T1D). However, implementing these behaviours may also lead to additional management burdens and challenges. Diabetes technologies, including continuous glucose monitoring systems, automated insulin delivery systems, and digital platforms, are being rapidly developed and widely used to reduce these burdens. Our aim was to review recent evidence to explore the influence of these technologies on health behaviours and well-being among adults with T1D and discuss future directions.

RECENT FINDINGS

Current evidence, albeit limited, suggests that technologies applied in diabetes self-management education and support (DSME/S), nutrition, physical activity (PA), and psychosocial care areas improved glucose outcomes. They may also increase flexibility in insulin adjustment and eating behaviours, reduce carb counting burden, increase confidence in PA, and reduce mental burden. Technologies have the potential to promote health behaviours changes and well-being for people with T1D. More confirmative studies on their effectiveness and safety are needed to ensure optimal integration in standard care practices.

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.

Effect of sodium-glucose cotransporter-2 inhibitors on continuous glucose monitoring metrics, as adjunctive to insulin in adults with type 1 diabetes mellitus: a meta-analysis of randomized controlled trials

AIMS

This meta-analysis of randomized controlled trials (RCTs) aimed to evaluate the effect of sodium-glucose cotransporter-2 inhibitors (SGLT2is) on continuous glucose monitoring metrics as adjunctive to insulin in adults with type 1 diabetes mellitus (T1D).

METHODS

A systematic literature search was conducted through Medline (via PubMed), Cochrane Library and Google Scholar until October 25, 2023. Dual-independent study selection, data extraction and quality assessment were conducted. Results were summarized with random effects meta-analysis.

RESULTS

Eight RCTs were identified, involving a total of 2310 T1D patients. The use of SGLT2is on top of standard insulin therapy was associated with a significantly higher time in range (TIR) compared to placebo (mean difference (MD) 9.7 %; 95 % confidence interval (CI) [8.3, 1.11]; P < 0.001). The time above range was significantly lower in patients receiving SGLT2is (MD -8.71 %; 95 % CI [-11.62, -5.79]; P < 0.001), whereas no difference was observed regarding the time below range (TBR) (MD 0.34 %; 95 % CI [-0.17, 0.85]; P = 0.19). A significantly lower sensor-recorded mean daily glucose was noted in the group receiving SGLT2is (MD -16.55 mg/dL; 95 % CI [-19.82, -13.29]; P < 0.001). When considering the metrics of glucose variability, SGLT2is demonstrated a significant favorable effect on the mean amplitude of glucose excursions (MD -16.92 mg/dL; 95 % CI [-25.31, -8.13]; P < 0.001) and the mean standard deviation of weekly glucose levels (MD -7.67 mg/dL; 95 % CI [-11, -4.35]; P < 0.001). No significant effect was observed concerning the coefficient of variation (MD -1 %; 95 % CI [-2.39, 0.4]; P = 0.16). Regarding safety outcomes, SGLT2is were significantly linked to higher odds of diabetic ketoacidosis compared to insulin alone (OR 3.18; 95 % CI [1.79, 5.66]; P < 0.001), with no significant impact on severe hypoglycemia events (OR 1; 95 % CI [0.54, 1.85]; P = 0.1).

CONCLUSION

Our findings suggest that in individuals with T1D, adjunct therapy with SGLT2is provides a significant benefit in terms of TIR and reduced glucose variability, without an increase in TBR.

Time in Range Is Associated with Incident Diabetic Retinopathy in Adults with Type 1 Diabetes: A Longitudinal Study

Abstract Objective: To evaluate the association between continuous glucose monitoring (CGM)-based time in various ranges and the subsequent development of diabetic retinopathy (incident DR) in adults with type 1 diabetes. Methods: Between June 2018 and March 2022, adults with type 1 diabetes with incident DR or no retinopathy (control) were identified. CGM data were collected retrospectively for up to 7 years before the date of eye examination defining incident DR or control. Associations between incident DR and CGM metrics were evaluated using logistic regression models. Results: This analysis included 71 adults with incident DR (mean age 27 years, 52% females, and mean diabetes duration 15 years) and 92 adults without DR (mean age 38 years, 48% females, and mean diabetes duration 20 years). Adjusting for age, diabetes duration, and CGM type, each 0.5% increase in glycated hemoglobin (HbA1c), 10 mg/dL increase in mean glucose, 5% decrease in time in target range 70-180 mg/dL (TIR), 5% decrease in time in tight target range 70-140 mg/dL (TITR), and 5% increase in time above 180 mg/dL (TAR) were associated with 24%, 22%, 18%, 28%, and 20% increase in odds of incident DR, respectively. Spearman correlations of TIR, TITR, TAR, and mean glucose with each other were all ≥0.97. Conclusion: Similar to HbA1c, TIR, TITR, TAR, and mean glucose were associated with increased risk for incident DR in adults with type 1 diabetes. These CGM metrics are highly correlated indicating that they provide similar information on glycemic control and diabetic retinopathy risk.

Insulin pump treatment vs. multiple daily insulin injections in patients with poorly controlled Type 2 diabetes mellitus: a comparison of cardiovascular effects

AIMS

Both hyperglycaemia and large glycaemic variability are associated with worse outcomes in patients with Type 2 diabetes mellitus (T2DM), possibly causing sympatho-vagal imbalance and endothelial dysfunction. Continuous subcutaneous insulin injection (CSII) improves glycemic control compared to multiple daily insulin injections (MDI). We aimed to assess whether CSII may improve cardiac autonomic and vascular dilation function compared to MDI.

METHODS

We enrolled T2DM patients without cardiovascular disease with poor glycaemic control, despite optimized MDI therapy. Patients were randomized to continue MDI (with multiple daily peripheral glucose measurements) or CSII; insulin dose was adjusted to achieve optimal target ranges of blood glucose levels. Patients were studied at baseline and after 6 months by: 1) flow-mediated dilation (FMD) and nitrate-mediated dilation (NMD) of the brachial artery; 2) heart rate variability (HRV) by 24-hour ECG Holter monitoring (HM). 7-day continuous glucose monitoring (CGM) was performed in 9 and 8 patients of Group 1 and 2, respectively.

RESULTS

Overall, 21 patients were enrolled, 12 randomized to CSII (Group 1) and 9 to MDI (Group 2). The daily dose of insulin and Hb1AC did not differ significantly between the 2 groups, both at baseline and at follow-up. Glucose variability showed some significant improvement at follow-up in the whole population, but no differences were observed between the 2 groups. Both FMD and NMD, as well as HRV parameters, showed no significant differences between the 2 groups at 6-month follow-up.

CONCLUSIONS

In this randomized small study we show that, in T2DM patients, CSII achieves a similar medium-term glycemic control compared to MDI, without any adverse effect on the cardiovascular system.

Early glucose abnormalities revealed by continuous glucose monitoring associate with lung function decline in cystic fibrosis: A five-year prospective study

BACKGROUND

Cystic fibrosis related diabetes (CFRD) is commonly associated with declining lung function and nutritional status. We aimed to evaluate the pulmonary impact of early glucose abnormalities by using 2-h standard oral glucose tolerance testing (OGTT) and continuous glucose monitoring (CGM) in people with cystic fibrosis (PwCF).

METHODS

PwCF aged ≥10 years old without known CFRD were included in a five-year prospective multicentre study. Annual evaluation of nutritional status, lung function, OGTT and CGM was set up. Associations between annual rate changes (Δ) in lung function, ΔFEV1 (forced expiratory volume in 1 s) percentage predicted (pp) and ΔFVC (forced vital capacity) pp., and annual rate changes in OGTT or CGM variables were estimated with a mixed model with a random effect for subject.

RESULTS

From 2009 to 2016, 112 PwCF (age: 21 ± 11 years, BMI (body mass index) z-score: -0.55 ± 1.09, FEV1pp: 77 ± 24 %, 2-h OGTT glucose: 122 ± 44 mg/dL, AUC (area under curve) >140 mg/dL: 1 mg/dL/day (0.2, 3.0) were included. A total of 428 OGTTs and 480 CGMs were collected. The participants presented annual decline of FVCpp and FEV1pp at -1.0 % per year (-1.6, -0.4), p < 0.001 and - 1.9 % per year (-2.5, -1.3), p < 0.001 respectively without change in BMI z-score during the study. Variation of two-hour OGTT glucose was not associated with declining lung function, as measured by ΔFEV1pp (p = 0.94) and ΔFVCpp (p = 0.90). Among CGM variables, only increase in AUC >140 mg/dL between two annual visits was associated with a decrease in ΔFVCpp (p < 0.05) and ΔFEV1pp (p < 0.05).

CONCLUSIONS

This prospective study supports the fact that early glucose abnormalities revealed by CGM predict pulmonary function decline in PwCF, while 2-h standard OGTT glucose is not associated with pulmonary impairment.

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.

Primary care diabetes assessment when HbA1c and other measures of glycemia disagree

AIMS

Although diabetes management decisions in primary care are typically based largely on HbA1c, mismatches between HbA1c and other measures of glycemia that are increasingly more available present challenges to optimal management. This study aimed to assess a systematic approach to identify the frequency of mismatches of potential clinical significance amongst various measures of glycemia in a primary care setting.

METHODS

Following screening to exclude conditions known to affect HbA1c interpretation, HbA1c, and fructosamine were obtained and repeated after ∼90 days on 53 adults with prediabetes or type 2 diabetes. A subset of 13 participants with repeat labs wore continuous glucose monitoring (CGM) for 10 days.

RESULTS

As expected, HbA1c and fructosamine only modestly correlated (initial R2 = 0.768/repeat R2 = 0.655). The HbA1c/fructosamine mismatch frequency of ± 0.5% (using the following regression HbA1c = 0.015 *fructosamine + 2.994 calculated from the initial sample) was 27.0%. Of the 13 participants with CGM data, HbA1c and CGM-based Glucose Management Indicator correlated at R2 = 0.786 with a mismatch frequency of ± 0.5% at 46.2% compared to a HbA1c/fructosamine mismatch frequency of ± 0.5% at 30.8%.

CONCLUSIONS

HbA1c is frequently mismatched with fructosamine and CGM data. As each of the measures has strengths and weaknesses, the utilization of multiple different measures of glycemia may be informative for diabetes assessment in the clinical setting.

Effects of a 2-Week Kinect-Based Mixed-Reality Exercise Program on Prediabetes: A Pilot Trial during COVID-19

Background

Pre-diabetes can develop into type 2 diabetes mellitus, but can prevented by regular exercise. However, the outcomes when combining unsupervised Kinect-based mixed-reality (KMR) exercise with continuous glucose monitoring (CGM) remain unclear. Therefore, this single-arm pilot trial examined changes in blood glucose (BG) concentrations over 672 hours (4 weeks), including a 2-week period of KMR exercise and CGM in individuals with pre-diabetes.

Methods

This was a pre-and post-treatment case-control study with nine participants. General questionnaires were administered and body composition, fasting BG concentrations, and 2-hour oral glucose tolerance test (2-OGTT) results were measured pre-and post-treatment. Weekly average glucose concentrations, hyperglycemia rate, hypoglycemia rate, average glucose concentration over time, amount of physical activity, amount of food intake, and pre- and postprandial BG (immediately and 30, 60, 90, and 120 minutes after lunch) were measured over 4 weeks (pre-test, exercise, and post -test weeks). Glucose concentrations were measured before exercising, between sets, and 30 and 60 minutes after exercise during the 2 weeks of unsupervised exercise (3 days/week).

Results

In all participants, body mass index (27.16±2.92 kg/m2), fasting BG (108.00±7.19 mg/dL), 2-OGTT (162.56±18.12 mg/dL), hyperglycemia rate (P=0.040), and 90-minute postprandial BG (P=0.035) were significantly reduced during the 2 exercise weeks, and the 2-OGTT result (P=0.044) and diastolic blood pressure (DBP) (P=0.046) were significantly reduced at the post -test as compared with the pre-test.

Conclusion

This study found that 2 weeks of unsupervised KMR exercise reduced 2-OGTT, DBP, hyperglycemia rate, and 90-minute postprandial BG concentration. We believed this effect could be identified more clearly in studies involving a larger number of participants and longer durations of exercise.

Increased glycemic variability results in abnormal differentiation of T cell subpopulation in type 2 diabetes patients

AIMS

We aimed to investigate the association between glycemic variability (GV) and the abnormal differentiation of T-cell subpopulations in patients with type 2 diabetes mellitus (T2DM).

METHODS

In total, 108 hospitalized patients with T2DM were enrolled and divided into two subgroups (normal glycemic excursion (NGE) and high glycemic excursion (HGE)) according to their mean amplitude of glycemic excursion (MAGE) level. The MAGE was evaluated via continuous glucose monitoring for 72 h consecutively. Flow cytometry was used to determine the proportions of T cell subpopulations.

RESULTS

The T helper (Th) 1 cell/Th2 cell ratio was significantly higher, and the proportion of regulatory T cells (Tregs) was significantly lower in the NGE group than in the HGE group (all P < 0.05). After fully adjusting for confounders, the MAGE was positively associated with the Th1 cell/Th2 cell ratio (β = 0.370; P = 0.009) and negatively associated with the proportion of Tregs (β = -0.554; P = 0.001).

CONCLUSION

The MAGE was an independent risk factor for abnormally high Th1 cell/Th2 cell ratio and proportion of Tregs. Abnormal differentiation of T cell subpopulations induced by GV may impair β-cell function, aggravate insulin resistance, and contribute to the development of diabetic complications.

Clinical Effectiveness of Continuous Glucose Monitoring in Pregnancies Affected by Type 1 Diabetes

Background: Continuous glucose monitoring (CGM) improves neonatal outcomes in type 1 diabetes pregnancies; however, its effectiveness has not been assessed in a real-world setting in the United States. Objective: The Triple C Study aimed to examine the clinical effectiveness, assessed through maternal glucose control and gestational health outcomes, of CGM use compared with self-monitoring of blood glucose (SMBG) in pregnancies associated with type 1 diabetes in a real-world setting. Research Design and Methods: We retrospectively identified 160 type 1 diabetes pregnancies at the Barbara Davis Center for Diabetes managed with CGM therapy (n = 109) or SMBG (n = 51) over a 6.5-year period (2014-2020). Obstetric care was provided at multiple practices. CGM use was defined as ≥60% wear in the second and third trimesters of pregnancy. Data were obtained from the electronic medical record system, hospital records, and vital statistics departments (Colorado and Wyoming). We used Student's t-test for continuous variables and chi-square test for categorical variables to compare outcomes between groups. Results: The CGM group had more participants meeting trimester-specific hemoglobin A1C (HbA1c) goals throughout pregnancy and postpartum (P < 0.01 in each time period). The CGM group had fewer participants never meeting HbA1c goals in any trimester than the SMBG group (P < 0.001). There were no significant differences in neonatal outcomes between groups, other than for macrosomia (12.8% CGM vs. 29.4% SMBG, P = 0.01). Infants of CGM users required a neonatal intensive care unit admission less often (52.9% CGM vs. 68.3% SMBG, P = 0.0989). Conclusions: CGM use was associated with improved maternal glucose levels in a diverse real-world cohort.

Correlation between time in range and serum uric acid in Chinese patients with type-2 diabetes: an observational cross-sectional study

BACKGROUND

At present, the relationship between serum uric acid and blood glucose is controversial, and even opposite conclusions have been reached. We aimed to investigate the relationship between time in range and serum uric acid and estimate the influence of serum uric acid on blood glucose fluctuations in Chinese patients with type-2 diabetes mellitus (T2DM).

METHODS

A total of 458 hospitalized patients with T2DM were selected. According to the SUA level, patients were divided into four groups by quartile: Q1 (≤ 254.5 µmol/L), Q2 (254.5-306.0 µmol/L), Q3 (306.0-385.5 µmol/L) and Q4 (> 385.5 µmol/L). The differences in general data, TIR and other clinical indicators between the four groups were assessed. Multifactor regression was used to analyze the relationship between subgroups of SUA and TIR, TBR, TAR, MAGE, SD, ADRR, MODD and M value. Curve fitting was used to analyze the association between TIR and SUA and to identify the inflection point.

RESULTS

TIR showed an overall increasing trend with increasing SUA, while HbA1c, TAR, MAGE, SD, ADRR, MODD and M value showed an overall decreasing trend with increasing SUA. Multivariate regression analysis showed that, compared with Q1, there was no correlation between SUA and TIR, TAR, ADRR, SD, or MODD in all models of Q2. In the Q3 and Q4 groups, SUA was correlated with SD, MODD, and MAGE in all models. In the Q4 group, SUA was correlated with TIR, TAR, ADRR, and the M value in all models. When SUA > 306 µmol/L (Q3 and Q4), TIR and SUA have a curve-like relationship, and the inflection point of the fitted curve was SUA = 460 mmol/L. Before the inflection point, β was 0.1, indicating that when SUA increases by 10 mmol/L, the corresponding TIR increases by 1%. After the inflection point, there was no significant difference in the correlation between TIR and SUA (P > 0.05).

CONCLUSIONS

There is a close relationship between TIR and SUA in T2DM patients, it is speculated that SUA in a certain range had a positive protective effect on blood glucose control.

Continuous glucose monitoring metrics in pregnancy with type 1 diabetes mellitus

Managing diabetes during pregnancy is challenging, given the significant risk it poses for both maternal and foetal health outcomes. While traditional methods involve capillary self-monitoring of blood glucose level monitoring and periodic HbA1c tests, the advent of continuous glucose monitoring (CGM) systems has revolutionized the approach. These devices offer a safe and reliable means of tracking glucose levels in real-time, benefiting both women with diabetes during pregnancy and the healthcare providers. Moreover, CGM systems have shown a low rate of side effects and high feasibility when used in pregnancies complicated by diabetes, especially when paired with continuous subcutaneous insulin infusion pump as hybrid closed loop device. Such a combined approach has been demonstrated to improve overall blood sugar control, lessen the occurrence of preeclampsia and neonatal hypoglycaemia, and minimize the duration of neonatal intensive care unit stays. This paper aims to offer a comprehensive evaluation of CGM metrics specifically tailored for pregnancies impacted by type 1 diabetes mellitus.

Metabolic health tracking using Ultrahuman M1 continuous glucose monitoring platform in non- and pre-diabetic Indians: a multi-armed observational study

Continuous glucose monitoring (CGM) device adoption in non- and pre-diabetics for preventive healthcare has uncovered a paucity of benchmarking data on glycemic control and insulin resistance for the high-risk Indian/South Asian demographic. Furthermore, the correlational efficacy between digital applications-derived health scores and glycemic indices lacks clear supportive evidence. In this study, we acquired glycemic variability (GV) using the Ultrahuman (UH) M1 CGM, and activity metrics via the Fitbit wearable for Indians/South Asians with normal glucose control (non-diabetics) and those with pre-diabetes (N = 53 non-diabetics, 52 pre-diabetics) for 14 days. We examined whether CGM metrics could differentiate between the two groups, assessed the relationship of the UH metabolic score (MetSc) with clinical biomarkers of dysglycemia (OGTT, HbA1c) and insulin resistance (HOMA-IR); and tested which GV metrics maximally correlated with inflammation (Hs-CRP), stress (cortisol), sleep, step count and heart rate. We found significant inter-group differences for mean glucose levels, restricted time in range (70-110 mg/dL), and GV-by-SD, all of which improved across days. Inflammation was strongly linked with specific GV metrics in pre-diabetics, while sleep and activity correlated modestly in non-diabetics. Finally, MetSc displayed strong inverse relationships with insulin resistance and dysglycemia markers. These findings present initial guidance GV data of non- and pre-diabetic Indians and indicate that digitally-derived metabolic scores can positively influence glucose management.

Eating habits and sleep quality in individuals with type 1 diabetes on continuous glucose monitoring and insulin pump

BACKGROUND AND AIMS

Sleep disorders are bidirectionally linked with eating behaviors and glucose metabolism, which could be clinically relevant in type 1 diabetes (T1D). We investigated the relationship between dietary habits and sleep quality in individuals with T1D on insulin pumps and continuous glucose monitoring (CGM).

METHODS AND RESULTS

In a cross-sectional study, dietary habits (7-day food diary, EPIC questionnaire) and sleep quality (Pittsburgh Sleep Quality Index questionnaire) were assessed in 59 men and 58 women with T1D, aged 19-79 years, using CGM and insulin pump. Differences in dietary habits and blood glucose after dinner (6 h) between participants differing in sleep quality, sleep duration, and sleep onset latency were evaluated. Bad Sleepers (n = 81) were twice as prevalent as Good Sleepers (n = 36) and had a significantly higher intake of fat than Good Sleepers (dinner: 30.7 ± 10.7 vs. 24.0 ± 10.5 g, p = 0.004). Short sleepers had a significantly higher usual intake (g/1000 kcal) of coffee and tea (90.4 ± 71.7 vs. 62.0 ± 35.6), alcoholic (47.8 ± 51.1 vs. 28.9 ± 31.5) and carbonated beverages (21.8 ± 38.1 vs. 9.3 ± 17.2) (p < 0.05 for all) than Long Sleepers. Long Sleep Onset Latency was associated with a significantly higher fat intake at dinner (41.8 ± 7.4 vs. 38.1 ± 9.1 % total energy, p = 0.029) than Short Sleep Onset Latency. No significant differences in post-dinner blood glucose levels were detected between participants with good or bad sleep quality.

CONCLUSION

Sleep disruption is common in T1D and is associated with unhealthy dietary choices, especially at dinner, independently of post-dinner blood glucose control.

Continuous Glucose Monitoring-Guided Insulin Administration in Long-Term Care Facilities: A Randomized Clinical Trial

OBJECTIVES

To evaluate the efficacy of real-time continuous glucose monitoring (rt-CGM) in adjusting insulin therapy in long-term care facilities (LTCF).

DESIGN

Prospective randomized clinical trial.

SETTINGS AND PARTICIPANTS

Insulin-treated patients with type 2 diabetes (T2D) admitted to LTCF.

METHODS

Participants in the standard of care wore a blinded CGM with treatment adjusted based on point-of-care capillary glucose results before meals and bedtime (POC group). Participants in the intervention (CGM group) wore a Dexcom G6 CGM with treatment adjusted based on daily CGM profile. Treatment adjustment was performed by the LTCF medical team, with a duration of intervention up to 60 days. The primary endpoint was difference in time in range (TIR 70-180 mg/dL) between treatment groups.

RESULTS

Among 100 participants (age 74.73 ± 11 years, 80% admitted for subacute rehabilitation and 20% for nursing home care), there were no significant differences in baseline clinical characteristics between groups, and CGM data were compared for a median of 17 days. There were no differences in TIR (53.38% ± 30.16% vs 48.81% ± 28.03%, P = .40), mean daily mean CGM glucose (184.10 ± 43.4 mg/dL vs 190.0 ± 45.82 mg/dL, P = .71), or the percentage of time below range (TBR) <70 mg/dL (0.83% ± 2.59% vs 1.18% ± 3.54%, P = .51), or TBR <54 mg/dL (0.23% ± 0.85% vs 0.56% ± 2.24%, P = .88) between rt-CGM and POC groups.

CONCLUSIONS AND IMPLICATIONS

The use of rtCGM is safe and effective in guiding insulin therapy in patients with T2D in LTCF resulting in a similar improvement in glycemic control compared to POC-guided insulin adjustment.

Evaluation of Glucose Metrics in Adults with Type 1 Diabetes Switching to Insulin Glargine 300 U/mL: A Retrospective, Propensity-Score Matched Study

Objectives: To study real-world effect of switching to Insulin Glargine 300 U/mL (Gla-300) on glucose metrics in people with type 1 diabetes. Methods: This retrospective secondary-use study compared 151 adults who switched to Gla-300 from first-generation long-acting insulins (Switchers) to 281 propensity-score matched controls (Non-switchers) who continued first-generation long-acting insulins. Primary endpoint was difference in time in range (TIR) evolution. A fictive "switching" date was assigned to Non-switchers to facilitate between-group comparisons. Results: In the period before switching, TIR decreased numerically for people in whom Gla-300 was eventually initiated (-0.05%/month [-0.16 to 0.07]), while it increased for matched controls (0.08%/month [0.02 to 0.015]; between-group difference P = 0.047). After Gla-300-initiation, Switchers had similar TIR increase compared to Non-switchers (P = 0.531). Switchers used higher basal dose than before switch (Δ0.012 U/[kg·d] [0.006 to 0.018]; P < 0.0001). Conclusion: In real-life, Gla-300 was typically initiated in people where TIR was decreasing, which was reversed after switch using slightly higher basal insulin dose. ClinicalTrials: ClinicalTrials.gov number NCT05109520.

Association Between Adherence, A1C Improvement, and Type of Continuous Glucose Monitoring System in People with Type 1 Diabetes or Type 2 Diabetes Treated with Intensive Insulin Therapy

INTRODUCTION

Use of continuous glucose monitoring (CGM) systems by people with diabetes is associated with improved glycemic outcomes, including lower glycated hemoglobin (A1C). Less is known about adherence to CGM systems, whether glycemic outcomes are impacted by levels of adherence, or whether adherence rates differ between types of CGM systems-intermittently scanned CGM (isCGM) or real-time CGM (rtCGM).

METHODS

A retrospective analysis of de-identified US administrative health claims and linked laboratory data was conducted using the Merative™ MarketScan® Research Database. The cohort included CGM-naïve people with type 1 diabetes (T1D) or type 2 diabetes treated with intensive insulin therapy (T2D-IIT) who initiated rtCGM or isCGM between August 1, 2019 and March 31, 2021 (defined as the index date). Adherence was calculated over a 12-month period using the proportion of days covered (PDC) with PDC ≥ 0.8 defined as adherent. A1C values were obtained within 6 months of the index date.

RESULTS

A total of 7669 individuals were identified. Subgroups included T1D using isCGM (n = 1578), T1D using rtCGM (n = 1244), T2D-IIT using isCGM (n = 3567), and T2D-IIT using rtCGM (n = 1280). After 12 months, PDC was 0.71 (0.30)-0.72 (0.31) (mean(SD)) for T1D and T2D-IIT rtCGM users and 0.55 (0.34)-0.56 (0.34) for T1D and T2D-IIT isCGM users. The proportion of adherent users (PDC ≥ 0.8) was 56.8-59.7% for rtCGM users and 36.3-37.6% for isCGM users. Overall, regardless of diabetes type, the odds of adherence were over two times higher for rtCGM users compared to isCGM users. For those with available A1C information (T1D n = 213; T2D-IIT n = 346), independent of CGM type, adherence to CGM was associated with a greater reduction in A1C and more people reaching A1C targets of < 7.0% or < 8.0%.

CONCLUSION

For people with T1D or T2D-IIT, higher adherence to CGM is associated with greater reductions in A1C, and higher adherence rates were observed with rtCGM systems than with isCGM systems.

Neonatal hypoglycemia and neurodevelopmental outcomes: Yesterday, today, tomorrow

Neonatal hypoglycemia is a major source of concern for pediatricians since it has commonly been related to poor neurodevelopmental outcomes. Diagnosis is challenging, considering the different operational thresholds provided by each guideline. Screening of infants at risk plays a crucial role, considering that most hypoglycemic infants show no clinical signs. New opportunities for prevention and treatment are provided by the use of oral dextrose gel. Continuous glucose monitoring systems could be a feasible tool in the next future. Furthermore, there is still limited evidence to underpin the current clinical practice of administering, in case of hypoglycemia, an intravenous "mini-bolus" of 10% dextrose before starting a continuous dextrose infusion. This brief review provides an overview of the latest advances in this field and neurodevelopmental outcomes according to different approaches.   Conclusion: To adequately define if a more permissive approach is risk-free for neurodevelopmental outcomes, more research on continuous glucose monitoring and long-term follow-up is still needed. What is Known: • Neonatal hypoglycemia (NH) is a well-known cause of brain injury that could be prevented to avoid neurodevelopmental impairment. • Diagnosis is challenging, considering the different suggested operational thresholds for NH (<36, <40, <45, <47 or <50 mg/dl). What is New: • A 36 mg/dl threshold seems to be not associated with a worse psychomotor development at 18 months of life when compared to the "traditional" threshold (47 mg/dl). • Further studies on long-term neurodevelopmental outcomes are required before suggesting a more permissive management of NH.

Continuous glucose monitoring in people with diabetes and end-stage kidney disease-review of association studies and Evidence-Based discussion

Diabetic nephropathy is currently the leading cause of end-stage kidney disease. The present methods of assessing diabetes control, such as glycated hemoglobin or self-monitoring of blood glucose, have limitations. Over the past decade, the field of continuous glucose monitoring has been greatly improved and expanded. This review examines the use of continuous glucose monitoring in people with end-stage kidney disease treated with hemodialysis (HD), peritoneal dialysis (PD), or kidney transplantation. We assessed the use of both real-time continuous glucose monitoring and flash glucose monitoring technology in terms of hypoglycemia detection, glycemic variability, and efficacy, defined as an improvement in clinical outcomes and diabetes control. Overall, the use of continuous glucose monitoring in individuals with end-stage kidney disease may improve glycemic control and detection of hypoglycemia. However, most of the published studies were observational with no control group. Moreover, not all studies used the same assessment parameters. There are very few studies involving subjects on peritoneal dialysis. The small number of studies with limited numbers of participants, short follow-up period, and small number of manufacturers of continuous glucose monitoring systems are limitations of the review. More studies need to be performed to obtain more reliable results.

Basic carbohydrate counting and glycemia in young people with type 1 diabetes in India: A randomized controlled trial

OBJECTIVES

The aim of this study was to evaluate the effect on glycemic control and acceptability of basic carbohydrate counting (BCC) in children and young adults with type 1 diabetes (T1DM).

METHODS

Ninety-two children and young adults (6-25 y of age) with T1DM were randomized to receive either routine nutrition education (RNE), which addressed food groups, glycemic index, and effects of food and exercise on glycemia, or learn BCC with personalized portion size education. A continuous glucose monitoring study and glycosylated hemoglobin (HbA1c) were performed at baseline and after 12 wk. The primary outcome was a change in time-in-range from baseline through 12 wk. A questionnaire on the acceptability of BCC was administered.

RESULTS

At 12 wk, there was no significant difference in change in time-in-range between the two groups (BCC group: 1.2 ± 12.2; RNE group: 1.9 ± 12.3; P = 0.786). No significant changes were observed in the percentage of time that blood glucose was >180 or >250 mg/dL; <70 or <54 mg/dL; glycemic variability, percentage of nights with hypoglycemia and HbA1c. In subgroup analysis, there was a significant decrease in HbA1c in the BCC group among participants with higher maternal education (-0.5 versus 0.2, P = 0.042). The total score on the acceptability questionnaire was higher in the BCC group (P = 0.022).

CONCLUSION

Among children and young adults in our region with T1DM, BCC provided flexibility in food choices and perception of greater ease of insulin adjustment. Although BCC was equivalent to RNE in terms of glycemic control, larger studies may reveal benefit in outcomes in certain subgroups.

Relationships of hypoglycemia awareness, hypoglycemia beliefs, and continuous glucose monitoring glycemic profiles with anxiety and depression symptoms in adults with type 1 diabetes using continuous glucose monitoring systems

AIMS

To evaluate relationships of hypoglycemia awareness, hypoglycemia beliefs, and continuous glucose monitoring (CGM) glycemic profiles with anxiety and depression symptoms in adults with type 1 diabetes (T1D) who use CGM.

METHODS

A cross-sectional survey and data collections were completed with 196 T1D adults who used CGM (59% also used automated insulin delivery devices (AIDs)). We assessed hypoglycemia awareness (Gold instrument), hypoglycemia beliefs (Attitudes to Awareness of Hypoglycemia instrument), CGM glycemic profiles, demographics, and anxiety and depression symptoms (Hospital Anxiety and Depression Scale). Analysis included simple and multiple linear regression analyses.

RESULTS

Lower hypoglycemia awareness, weaker "hypoglycemia concerns minimized" beliefs, stronger "hyperglycemia avoidance prioritized" beliefs were independently associated with higher anxiety symptoms (P < 0.05), with similar trends in both subgroups using and not using AIDs. Lower hypoglycemia awareness were independently associated with greater depression symptoms (P < 0.05). In participants not using AIDs, more time in hypoglycemia was related to less anxiety and depression symptoms (P < 0.05). Being female and younger were independently associated with higher anxiety symptoms, while being younger was also independently associated with greater depression symptoms (P < 0.05).

CONCLUSION

Our findings revealed relationships of impaired hypoglycemia awareness, hypoglycemia beliefs, CGM-detected hypoglycemia with anxiety and depression symptoms in T1D adults who use CGMs.

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.

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.

Reducing Diabetes Burden in Medtronic's Automated Insulin Delivery Systems

Background: The MiniMed™ 780G advanced hybrid closed-loop system (MM780G) builds on the basal automation and low-glucose protection features of the MiniMed™ 670G and 770G systems. While previous publications have focused on glycemic control improvements with MM780G, burden reduction has not been fully described. Methods: Data from two 3-month pivotal trials for the MM670G with Guardian™ Sensor 3 (GS3) (104 adults; 125 children) and MM780G with Guardian™ 4 Sensor (G4S) (67 adults;109 children) were compared. Real-world data (RWD) from United States users (N = 3851) transitioning from MM770G+GS3 to MM780G+G4S were also analyzed. Analyses included a new metric for diabetes management burden (i.e., pentagon composite metric), glycemic outcomes and system burden (e.g., closed-loop exits and fingersticks per day). Results: Diabetes burden metric (-22.8% and -28.5%), time in range (+3.1% [*P = 0.035] and +6.4% [P < 0.001]) and time below range (-1.8% [*P < 0.001] and -0.7% [*P < 0.001]) significantly improved, compared to MM670G for adult and pediatric participants, respectively. The pediatric mean sensor glucose (SG) reduced by -8.6 mg/dL (*P < 0.001), while the adults' saw no change. Closed-loop use significantly increased for both cohorts (+17.1% [*P < 0.001] and +20.5% [*P < 0.001]). Closed-loop exits were significantly reduced to about 1 per week (-0.5 [*P < 0.001] and -0.7 [*P < 0.001]); fingerstick tests were also reduced (-6.2 [*P < 0.001] and -6.9 [*P < 0.001]). Similar outcomes were observed from U.S. RWD. Conclusions: MiniMed™ 780G with G4S use was associated with significant reduction in diabetes management burden with fewer closed-loop exits, fingersticks and other interactions, and improvements in glycemic control when compared to the MiniMed™ 670G with GS3.

Emerging Technologies and Therapeutics for Type 1 Diabetes

Recent years witnessed advancements in diabetes technologies and therapeutics. People with type 1 diabetes have more options to control their blood glucose, prevent hypoglycemia, and spend more time with their loved ones. Newer diabetes technologies and therapeutics improve the quality of life and boost the confidence of people with type 1 diabetes. In parallel to changes in the diabetes technology field, stem cell research has been evolving. Gene editing and production of β cells from stem cells are ongoing. The current focus of cure studies is how to increase the survival of cells produced with stem cells. New adjunctive therapies are under development.

Glycemic variability in diagnosis of gestational diabetes as predictor of pharmacological treatment

INTRODUCTION

To establish whether glycemic variability (GV) parameters used when gestational diabetes mellitus (GDM) has been diagnosed could help predict the probability that a patient will need pharmacological treatment, and to analyze the link of these parameters to the development of maternal-fetal complications.

MATERIALS AND METHODS

A prospective study of 87 women with GDM who underwent retrospective continuous glucose monitoring (CGM) for six days between weeks 26 and 32 of gestation, following diagnosis. The mean glycemia levels and GV variables were analyzed together with their link to maternal-fetal complications, and the need for pharmacological treatment. ROC (receiver operating characteristic) curves were developed to determine validity to detect the need for pharmacological treatment.

RESULTS

Patients with higher mean glycemia (p < 0.001) and continuous overlapping of net glycemic action in a period of n-hours (CONGAn) (p = 0.001) required pharmacological treatment. The ROC curves showed cut-off points of 98.81 mg/dL for mean glycemia, and 86.70 mg/dL for CONGAn, with 83.3% sensitivity and 67.8% specificity for both parameters. No relation between the GV parameters and development of maternal-fetal complications was observed.

CONCLUSIONS

The use of CGM, once GDM is diagnosed, enables us to identify those patients who would benefit from closer monitoring during gestation, and facilitate a speedier take-up of pharmacological treatment. However, prospective studies involving a higher number of patients are needed, as well as a cost assessment for recommending the use of CGM following GDM diagnosis.

A Comparison of Continuous Glucose Monitoring-Measured Time-in-Range 70-180 mg/dL Versus Time-in-Tight-Range 70-140 mg/dL

Objective: To evaluate the relationship between continuous glucose monitoring (CGM)-measured time-in-range 70-180 mg/dL (TIR) and time-in-tight-range 70-140 mg/dL (TITR). Methods: TIR and TITR were calculated from CGM data collected using blinded or unblinded Dexcom sensors from 9 studies with 912 participants with type 1 diabetes (T1D) and 2 studies with 184 participants with type 2 diabetes (T2D). The TIR-TITR relationship was assessed overall and stratified by coefficient of variation (CV) and by time below range <70 mg/dL (TBR). Results: The correlation between TIR and TITR was 0.94. TITR was higher for a given TIR for T2D compared with T1D. However, after adjusting for the differences in CV or TBR, both of which were higher with T1D than T2D, the differences were minimized. The TIR-TITR relationship was nonlinear, with a higher ratio of TITR:TIR observed as TIR increased ranging from 0.42 when TIR was 20% to 0.66 when TIR was 80%. Similarly, as TITR increased, the ratio of TIR:TITR decreased, varying from 2.6 with TITR of 10% to 1.3 for TITR of 70%. The TIR-TITR relationship varied according to CV and TBR, such that the higher the CV or higher the amount of TBR the greater was TITR for a given TIR. Conclusions: TIR and TITR are highly correlated, although the relationship is nonlinear. With knowledge of TIR, TITR can be estimated with reasonable precision.

Diabetic Ketoacidosis at Diagnosis in Youth with Type 1 Diabetes Is Associated with a Higher Hemoglobin A1c Even with Intensive Insulin Management

Introduction: Diabetic ketoacidosis (DKA) at diagnosis is associated with short- and long-term complications. We assessed the relationship between DKA status and hemoglobin A1c (A1c) levels in the first year following type 1 diabetes (T1D) diagnosis. Research Design and Methods: The Pilot Teamwork, Targets, Technology, and Tight Control (4T) study offered continuous glucose monitoring to youth with T1D within 1 month of diagnosis. A1c levels were compared between historical (n = 271) and Pilot 4T (n = 135) cohorts stratified by DKA status at diagnosis (DKA: historical = 94, 4T = 67 versus without DKA: historical = 177, 4T = 68). A1c was evaluated using locally estimated scatter plot smoothing. Change in A1c from 4 to 12 months postdiagnosis was evaluated using a linear mixed model. Results: Median age was 9.7 (interquartile range [IQR]: 6.6, 12.7) versus 9.7 (IQR: 6.8, 12.7) years, 49% versus 47% female, 44% versus 39% non-Hispanic White in historical versus Pilot 4T. In historical and 4T cohorts, DKA at diagnosis demonstrated higher A1c at 6 (0.5% [95% confidence interval (CI): 0.21-0.79; P < 0.01] and 0.38% [95% CI: 0.02-0.74; P = 0.04], respectively), and 12 months (0.62% [95% CI: -0.06 to 1.29; P = 0.07] and 0.39% [95% CI: -0.32 to 1.10; P = 0.29], respectively). The highest % time in range (TIR; 70-180 mg/dL) was seen between weeks 15-20 (69%) versus 25-30 (75%) postdiagnosis for youth with versus without DKA in Pilot 4T, respectively. Conclusions: Pilot 4T improved A1c outcomes versus the historical cohort, but those with DKA at diagnosis had persistently elevated A1c throughout the study and intensive diabetes management did not mitigate this difference. DKA prevention at diagnosis may translate into better glycemic outcomes in the first-year postdiagnosis. Clinical Trial Registration: clinicaltrials.gov: NCT04336969.

The Myth of MARD (Mean Absolute Relative Difference): Limitations of MARD in the Clinical Assessment of Continuous Glucose Monitoring Data

The mean absolute relative difference (MARD) is a numerical metric that has been adopted by the diabetes technology community as the main indicator that describes the accuracy of a glucose sensor at a single point in time. The appropriateness of this adoption is questionable because there is limited evidence that MARD has meaningful clinical relevance in the current era of sensor technology. The calculation may be simple, but evaluation of MARD can be very complex because it is substantially impacted by the design of the data collection in an accuracy study. Factors that can influence the overall MARD include participant demographics such as type of diabetes and age, site of sensor wear, and the percentage of collected values in each glycemic range during the study that is, in turn, a function of the study design. MARD is only one of several important statistical metrics such as bias and precision that are relevant to assessing accuracy of a sensor. Furthermore, these analytic metrics convey little information about the safety and effectiveness of sensor use with an automated insulin delivery system or a standalone device. There are no clinical studies in people with diabetes (PWD) proving that MARD can accurately differentiate between a safe and unsafe sensor or between a more and less clinically effective sensor. Moreover, there are alternatives to MARD that can do this in a clinically meaningful way, which include error grid analyses and clinical studies in PWD. This review attempts to demythologize the status of MARD for the diabetes community in an effort to shift the focus from MARD to using clinically relevant assessments.

Positive association between the proinsulin-to-C-peptide ratio and prolonged hyperglycemic time in type 2 diabetes

The proinsulin-to-C-peptide (PI:C) ratio is an index applied during the early stage of pancreatic β-cell dysfunction. The aim of this study was to identify the characteristics associated with the PI:C ratio to discuss pancreatic β-cell dysfunction progression during the natural course of type 2 diabetes and its relationship with glycemic management. This multicenter, prospective observational study included 272 outpatients with type 2 diabetes. Continuous glucose monitoring was performed and fasting blood samples were collected and analyzed. We identified the clinical factors associated with the PI:C ratio by multiple regression analysis. The mean age of the cohort was 68.0 years, mean hemoglobin A1c 7.1% (54 mmol/mol), and mean body mass index 24.9 kg/m2. Multiple regression analysis showed that a prolonged time above the target glucose range (>180 mg/dL) and high body mass index contributed to a high PI:C ratio. However, no associations were found between the PI:C ratio and glucose variability indices. These findings suggested that the PI:C ratio is positively associated with a prolonged hyperglycemic time in type 2 diabetes, whereas its relationship with glucose variability remains unclear.

Limitations of 14-Day Continuous Glucose Monitoring Sampling for Assessment of Hypoglycemia and Glycemic Variability in Type 1 Diabetes

Continuous glucose monitoring (CGM) has become the standard of care in diabetes management with the recent advances in technology and accessibility in the last decade. An International Consensus was established to define CGM metrics and its goals in diabetes care. The 2019 International Consensus suggested 14 days of CGM sampling for the assessment of CGM metrics stating the limitations that may occur for hypoglycemia and glycemic variability metrics. Since then, several studies assessed the correlation between CGM metrics and duration of the sampling period. This review summarized the studies that investigated the relationship between 14-day CGM sampling to 90-day CGM data in >70% CGM users for all CGM metrics and highlighted possible solutions for more accurate CGM sampling durations in type 1 diabetes (T1D). Accumulating evidence showed that 14-day CGM sampling correlates well with 90-day CGM data for mean glucose, time in 70-180 mg/dL, and hyperglycemia metrics; however, it correlates weakly for hypoglycemia and glycemic variability metrics. In the studies included in this review, in adults with T1D, minimum sampling duration was 14 days for mean glucose, time in 70-180 mg/dL, and time in hyperglycemia (>180 and >250 mg/dL); however, minimum sampling duration varied between 21 to 30 days for time <70 mg/dL, 30 to 35 days for time <54 mg/dL, and 28 to 35 days for coefficient of variation. Longer than 14 days of CGM, sampling was required to properly assess hypoglycemia and glycemic variability in T1D.

Closed-Loop Insulin Delivery Systems for People with Type 1 Diabetes and Chronic Very Poor Metabolic Control: It Works and Is Safe!

To evaluate the percentage of patients with type 1 diabetes (T1D) and very poor metabolic control who would agree to be treated with a hybrid closed-loop (HCL) insulin delivery system, and to assess metabolic improvement and safety. In a single center, we identified all patients aged >18 years with hemoglobin A1c (HbA1c) >11% (97 mmol/mol) before HCL treatment. We collected metabolic control and safety data up to 1 year post-HCL in those who accepted HCL after it was proposed to them. We identified 65 patients eligible for the study, 32 (50%) already used, or accepted to start using HCL. Patients were aged 18-49 years; mean(±standard deviation) baseline HbA1c was 12.5(±1.8)% (113 ± 20 mmol/mol). After 1 year, 25 patients (78%) were still using HCL and their mean HbA1c decreased to 9.4(±1.9)% (79 mmol/mol) (P < 0.001). The rate of acute metabolic events was similar during the year of follow-up to the rate in the 3 years before HCL initiation. HCL systems should be considered in patients with T1D and very poor metabolic control. ClinicalTrials registration no. NCT05282264.

The effect of carbohydrate intake on glycaemic control in individuals with type 1 diabetes: a randomised, open-label, crossover trial

Background

Few studies have examined the effects of lower carbohydrate diets on glucose control in persons with type 1 diabetes (T1D). The objective of the study was to investigate whether a moderate carbohydrate diet improves glucose control in persons with T1D.

Methods

A randomised, multicentre, open-label, crossover trial over 12 weeks. There were 69 individuals assessed for eligibility, 54 adults with T1D and HbA1c ≥ 58 mmol/mol (7.5%) were randomised. Interventions were moderate carbohydrate diet versus traditional diet (30 vs 50% of total energy from carbohydrates) over four weeks, with a four-week wash-out period between treatments. Masked continuous glucose monitoring was used to evaluate effects on glucose control. The primary endpoint was the difference in mean glucose levels between the last 14 days of each diet phase.

Findings

50 individuals were included in the full analysis set with a mean baseline HbA1c of 69 mmol/mol (8.4%), BMI 29 kg/m2, age of 48 years, and 50% were female. The difference in mean glucose levels between moderate carbohydrate and traditional diet was -0.6 mmol/L, 95% CI -0.9 to -0.3, p < 0.001. Time in range increased during moderate carbohydrate diet by 4.7% (68 min/24 h) (95% CI 1.3 to 8.0), p = 0.008. Time above range (>10 mmol/L) decreased by 5.9% (85 min/24 h), 95% CI -9.6 to -2.2, p = 0.003. There were no significant differences in the standard deviation of glucose levels (95% CI -0.3 to 0.0 mmol/L, p = 0.15) or hypoglycaemia in the range <3.9 mmol/L (95% CI -0.4 to 2.9%, p = 0.13) and <3.0 mmol/L (95% CI -0.4 to 1.6%, p = 0.26). Four participants withdrew, none because of adverse events. There were no serious adverse events including severe hypoglycaemia and ketoacidosis. Mean ketone levels were 0.17 (SD 0.14) mmol/L during traditional and 0.18 (SD 0.13) mmol/L during moderate carbohydrate diet (p = 0.02).

Interpretation

A moderate carbohydrate diet is associated with decreases in mean glucose levels and time above range and increases in time in range without increased risk of hypoglycaemia or ketoacidosis compared with a traditional diet in individuals with T1D.

Funding

The Healthcare Board, Region Västra Götaland, The Dr P Håkansson Foundation and the Swedish state under the agreement between the Swedish government and the county councils, the ALF-agreement [ALFGBG-966173].

Identification of individuals with diabetes who are eligible for continuous glucose monitoring forecasting

BACKGROUND AND OBJECTIVES

Predicting glucose levels in individuals with diabetes offers potential improvements in glucose control. However, not all patients exhibit predictable glucose dynamics, which may lead to ineffective treatment strategies. We sought to investigate the efficacy of a 7-day blinded screening test in identifying diabetes patients suitable for glucose forecasting.

METHODS

Participants with type 1 diabetes (T1D) were stratified into high and low initial error groups based on screening results (eligible and non-eligible). Long-term glucose predictions (30/60 min lead time) were evaluated among 334 individuals who underwent continuous glucose monitoring (CGM) over a total of 64,460,560 min.

RESULTS

A strong correlation was observed between screening accuracy and long-term mean absolute relative difference (MARD) (0.661-0.736; p < 0.001), suggesting significant predictability between screening and long-term errors. Group analysis revealed a notable reduction in predictions falling within zone D of the Clark Error Grid by a factor of three and in zone C by a factor of two.

CONCLUSIONS

The identification of eligible patients for glucose prediction through screening represents a practical and effective strategy. Implementation of this approach could lead to a decrease in adverse glucose predictions.