Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range

Sustained Effectiveness of an Advanced Hybrid Closed-Loop System in a Cohort of Children and Adolescents With Type 1 Diabetes: A 1-Year Real-World Study

OBJECTIVE

To investigate glucose metrics and identify potential predictors of the achievement of glycemic outcomes in children and adolescents during their first 12 months of MiniMed 780G use.

RESEARCH DESIGN AND METHODS

This multicenter, longitudinal, real-world study recruited 368 children and adolescents with type 1 diabetes (T1D) starting SmartGuard technology between June 2020 and June 2022. Ambulatory glucose profile data were collected during a 15-day run-in period (baseline), 2 weeks after automatic mode activation, and every 3 months. The influence of covariates on glycemic outcomes after 1 year of MiniMed 780G use was assessed.

RESULTS

After 15 days of automatic mode use, all glucose metrics improved compared with baseline (P < 0.001), except for time below range (P = 0.113) and coefficient of variation (P = 0.330). After 1 year, time in range (TIR) remained significantly higher than at baseline (75.3% vs. 62.8%, P < 0.001). The mean glycated hemoglobin (HbA1c) over the study duration was lower than the previous year (6.9 ± 0.6% vs. 7.4 ± 0.9%, P < 0.001). Time spent in tight range (70-140 mg/dL) was 51.1%, and the glycemia risk index was 27.6. Higher TIR levels were associated with a reduced number of automatic correction boluses (P < 0.001), fewer SmartGuard exits (P = 0.021), and longer time in automatic mode (P = 0.030). Individuals with baseline HbA1c >8% showed more relevant improvement in TIR levels (from 54.3% to 72.3%).

CONCLUSIONS

Our study highlights the sustained effectiveness of MiniMed 780G among youth with T1D. Findings suggest that even children and adolescents with low therapeutic engagement may benefit from SmartGuard technology.

Associations Between HbA1c and Glucose Time in Range Using Continuous Glucose Monitoring in Type 1 Diabetes: Cross-Sectional Population-Based Study

INTRODUCTION

Continuous glucose monitoring (CGM) introduces novel indicators of glycemic control.

METHODS

This cross-sectional study, based on the Swedish National Diabetes Register, examines 27,980 adults with type 1 diabetes. It explores the relationships between HbA1c (glycated hemoglobin) and various CGM-derived metrics, including TIR (time in range, representing the percentage of time within the range of 4-10 mmol/l for 2 weeks), TAR (time above range), TBR (time below range), mean glucose, standard deviation (SD), and coefficient of variation (CV). Pearson correlation coefficients and linear regression models were utilized for estimation.

RESULTS

The analysis included 46% women, 30% on insulin pump, 7% with previous coronary heart disease and 64% with retinopathy. Mean ± SD values were age 48 ± 18 years, diabetes duration 25 ± 16 years, HbA1c 58.8 ± 12.8 mmol/mol, TIR 58.8 ± 19.0%, TAR 36.3 ± 20.0%, TBR 4.7 ± 5.4%, mean sensor glucose 9.2 ± 2.0 mmol/l, SD 3.3 ± 1.0 mmol/l, and CV 36 ± 7%. The overall association between HbA1c and TIR was - 0.71 (Pearson's r), with R2 0.51 in crude linear regression and 0.57 in an adjusted model. R2 values between HbA1c and CGM mean glucose were 0.605 (unadjusted) 0.619 (adjusted) and TAR (unadjusted 0.554 and fully adjusted 0.568, respectively), while fully adjusted R2 values were 0.458, 0.175 and 0.101 between HbA1c and CGM SD, CGM CV and TBR, respectively.

CONCLUSIONS

This descriptive study demonstrates that the degree of association between HbA1c and new and readily available CGM-derived metrics, i.e., time in range (TIR), time above range (TAR), and CGM mean glucose, is robust in assessing the management of individuals with type 1 diabetes in clinical settings. Metrics from CGM that pertain to variability and hypoglycemia exhibit only weak correlations with HbA1c.

Research progress on the association between glycemic variability index derived from CGM and cardiovascular disease complications

Currently, glycated hemoglobin A1c (HbA1c) has been widely used to assess the glycemic control of patients with diabetes. However, HbA1c has certain limitations in describing both short-term and long-term glycemic control. To more accurately evaluate the glycemic control of diabetes patients, the continuous glucose monitoring (CGM) technology has emerged. CGM technology can provide robust data on short-term glycemic control and introduce new monitoring parameters such as time in range, time above range, and time below range as indicators of glycemic fluctuation. These indicators are used to describe the changes in glycemic control after interventions in clinical research or treatment modifications in diabetes patient care. Recent studies both domestically and internationally have shown that these indicators are not only associated with microvascular complications of diabetes mellitus but also closely related to cardiovascular disease complications and prognosis. Therefore, this article aims to comprehensively review the association between CGM-based glycemic parameters and cardiovascular disease complications by analyzing a large number of domestic and international literature. The purpose is to provide scientific evidence and guidance for the standardized application of these indicators in clinical practice, in order to better evaluate the glycemic control of diabetes patients and prevent the occurrence of cardiovascular disease complications. This research will contribute to improving the quality of life for diabetes patients and provide important references for clinical decision-making.

Association between continuous glucose monitoring metrics and clinical outcomes in adults with type 1 diabetes in a real-world setting

AIMS

Continuous glucose monitoring (CGM) metrics can assist diabetes management. Consensus statements recommend > 70 % time in range (TIR) and ≤ 36 % glucose coefficient of variation (CV). However, how these targets perform in clinical practice is unknown. This retrospective, longitudinal cohort study analyzed relationships between TIR, CV, glycated hemoglobin (HbA1c), and hypoglycemia in a real-world setting.

METHODS

Data of 542 adults with type 1 diabetes who used CGM (January 2014-July 2020) were analyzed. Associations between TIR and HbA1c at the same and subsequent visits, incidence rate ratios (IRRs) for hypoglycemia at different CVs, and number of hypoglycemic events at cross-sections of HbA1c and CV were estimated by regression.

RESULTS

TIR was inversely related to HbA1c; for every 10 % increase in TIR, HbA1c was significantly reduced by 0.34 % (4 mmol/mol) and 0.20 % (2 mmol/mol) at the same and subsequent visits, respectively. Level 2 hypoglycemia was significantly reduced at CV < 30 %, 30-33 %, 33.1-36 %, and 36.1-40 %: adjusted IRRs vs CV ≥ 40.1 % of 0.14, 0.28, 0.32, and 0.50, respectively. Hypoglycemic events were reduced at lower CV across HbA1c levels and at higher HbA1c across CV levels.

CONCLUSION

This study quantifies HbA1c improvements with increased TIR and hypoglycemia reductions with improved CV in clinical practice.

Cystatin C as an adjunct to HbA1c may prove useful in predicting the development of diabetic complications in children and adolescents with type 1 diabetes

Purpose

Complications from diabetes mellitus can occur over time and although glycosylated hemoglobin (HbA1c) is a good biomarker for glycaemic control, other factors also contribute to the development of complications in type 1 diabetes. More markers able to identify the risk of complications are needed. This study aimed to investigate plasma levels of FGF21, Cystatin C, lipocalin-2, and MMP-9 in children and adolescents with different duration of type 1 diabetes and possible correlation to HbA1c to identify potential biomarkers of future complication development.

Methods

Patients (n = 244, 0-18 years) with type 1 diabetes, at Helsingborg's Hospital, Sweden, were included in this study. Circulating levels of FGF21, Cystatin C, lipocalin-2, and MMP-9 were investigated in plasma using automated ELISA with the ELLA™ system and standardised controls.

Results

Cystatin C levels were elevated in patients with diabetes duration longer than 5 years (P < 0.001). HbA1c and Cystatin C levels were inversely correlated for all participants (rs = - 0.23, CI95: -0.35--0.10; P < 0.001). A stepwise multiple regression analysis showed that HbA1c (P < 0.001) and Cystatin C (P = 0.03) were associated to the duration of diabetes at sampling while MMP-9, lipocalin-2, and FGF21 did not reach statistical significance.

Conclusion

In conclusion, Cystatin C levels were higher in patients with diabetes duration longer than 5 years, and inverse correlation was found between HbA1c and Cystatin C levels as well as duration of diabetes. Cystatin C may prove useful as an adjunct to HbA1c in predicting eventual development of diabetic complications.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-024-01419-1.

Comparing advanced hybrid closed loop therapy and standard insulin therapy in pregnant women with type 1 diabetes (CRISTAL): a parallel-group, open-label, randomised controlled trial

BACKGROUND

Advanced hybrid closed loop (AHCL) therapy can improve glycaemic control in pregnant women with type 1 diabetes. However, data are needed on the efficacy and safety of AHCL systems as these systems, such as the MiniMed 780G, are not currently approved for use in pregnant women. We aimed to investigate whether the MiniMed 780G can improve glycaemic control with less hypoglycaemia in pregnant women with type 1 diabetes.

METHODS

CRISTAL was a double-arm, parallel-group, open-label, randomised controlled trial conducted in secondary and tertiary care specialist endocrinology centres at 12 hospitals (11 in Belgium and one in the Netherlands). Pregnant women aged 18-45 years with type 1 diabetes were randomly assigned (1:1) to AHCL therapy (MiniMed 780G) or standard insulin therapy (standard of care) at a median of 10·1 (IQR 8·6-11·6) weeks of gestation. Randomisation was done centrally with minimisation dependent on baseline HbA1c, insulin administration method, and centre. Participants and study teams were not masked to group allocation. The primary outcome was proportion of time spent in the pregnancy-specific target glucose range (3·5-7·8 mmol/L), measured by continuous glucose monitoring (CGM) at 14-17 weeks, 20-23 weeks, 26-29 weeks, and 33-36 weeks. Key secondary outcomes were overnight time in target range, and time below glucose range (<3·5 mmol/L) overall and overnight. Analyses were conducted on an intention-to-treat basis. This trial is registered with ClinicalTrials.gov (NCT04520971).

FINDINGS

Between Jan 15, 2021 and Sept 30, 2022, 101 participants were screened, and 95 were randomly assigned to AHCL therapy (n=46) or standard insulin therapy (n=49). 43 patients assigned to AHCL therapy and 46 assigned to standard insulin therapy completed the study. At baseline, 91 (95·8%) participants used insulin pumps, and the mean HbA1c was 6·5% (SD 0·6). The mean proportion of time spent in the target range (averaged over four time periods) was 66·5% (SD 10·0) in the AHCL therapy group compared with 63·2% (12·4) in the standard insulin therapy group (adjusted mean difference 1·88 percentage points [95% CI -0·82 to 4·58], p=0·17). Overnight time in the target range was higher (adjusted mean difference 6·58 percentage points [95% CI 2·31 to 10·85], p=0·0026), and time below range overall (adjusted mean difference -1·34 percentage points [95% CI, -2·19 to -0·49], p=0·0020) and overnight (adjusted mean difference -1·86 percentage points [95% CI -2·90 to -0·81], p=0·0005) were lower with AHCL therapy than with standard insulin therapy. Participants assigned to AHCL therapy reported higher treatment satisfaction. No unanticipated safety events occurred with AHCL therapy.

INTERPRETATION

In pregnant women starting with tighter glycaemic control, AHCL therapy did not improve overall time in target range but improved overnight time in target range, reduced time below range, and improved treatment satisfaction. These data suggest that the MiniMed 780G can be safely used in pregnancy and provides some additional benefits compared with standard insulin therapy; however, it will be important to refine the algorithm to better align with pregnancy requirements.

FUNDING

Diabetes Liga Research Fund and Medtronic.

Neural-Net Artificial Pancreas: A Randomized Crossover Trial of a First-in-Class Automated Insulin Delivery Algorithm

Background: Automated insulin delivery (AID) is now integral to the clinical practice of type 1 diabetes (T1D). The objective of this pilot-feasibility study was to introduce a new regulatory and clinical paradigm-a Neural-Net Artificial Pancreas (NAP)-an encoding of an AID algorithm into a neural network that approximates its action and assess NAP versus the original AID algorithm. Methods: The University of Virginia Model-Predictive Control (UMPC) algorithm was encoded into a neural network, creating its NAP approximation. Seventeen AID users with T1D were recruited and 15 participated in two consecutive 20-h hotel sessions, receiving in random order either NAP or UMPC. Their demographic characteristics were ages 22-68 years old, duration of diabetes 7-58 years, gender 10/5 female/male, White Non-Hispanic/Black 13/2, and baseline glycated hemoglobin 5.4%-8.1%. Results: The time-in-range (TIR) difference between NAP and UMPC, adjusted for entry glucose level, was 1 percentage point, with absolute TIR values of 86% (NAP) and 87% (UMPC). The two algorithms achieved similar times <70 mg/dL of 2.0% versus 1.8% and coefficients of variation of 29.3% (NAP) versus 29.1 (UMPC)%. Under identical inputs, the average absolute insulin-recommendation difference was 0.031 U/h. There were no serious adverse events on either controller. NAP had sixfold lower computational demands than UMPC. Conclusion: In a randomized crossover study, a neural-network encoding of a complex model-predictive control algorithm demonstrated similar performance, at a fraction of the computational demands. Regulatory and clinical doors are therefore open for contemporary machine-learning methods to enter the AID field. Clinical Trial Registration number: NCT05876273.

Intra-pancreatic fat is associated with continuous glucose monitoring metrics

AIM

To investigate the relationship of fat in the pancreas with time spent in different glycaemic ranges.

METHODS

Abdominal magnetic resonance imaging at 3.0 Tesla was used to quantify fat in the pancreas as both continuous [i.e. intra-pancreatic fat deposition (IPFD)] and binary (i.e. fatty change of the pancreas vs. normal pancreas) variables. Dexcom G6 devices were used to collect continuous glucose monitoring data every 5 min over a continuous 7-day period. Time above range (TAR), time in range (TIR) and time below range were computed. Statistical models were built to adjust for age, sex, body composition, and other covariates in linear regression analysis and analysis of covariance.

RESULTS

In total, 38 individuals were studied. IPFD was significantly associated with TAR (p = .036) and TIR (p = .042) after adjustment for covariates. For every 1% increase in IPFD, there was a 0.3 unit increase in TAR and a decrease in TIR. Individuals with fatty change of the pancreas, when compared with those with normal pancreas, had significantly higher TAR (p = .034) and lower TIR (p = .047) after adjustment for covariates. Neither IPFD (p = .805) nor fatty change of the pancreas (p = .555) was associated with time below range after adjustment for covariates.

CONCLUSION

Increased fat in the pancreas is associated with excessive glycaemic variability. Fatty change of the pancreas may contribute to heightening the risk of cardiovascular diseases.

Association Between Treatment Adherence and Continuous Glucose Monitoring Outcomes in People With Diabetes Using Smart Insulin Pens in a Real-World Setting

OBJECTIVE

To evaluate the association of insulin injection adherence, smart insulin pen engagement, and glycemic control using real-world data from 16 countries from adults self-administering basal insulin degludec and bolus insulin with a smart insulin pen (NovoPen 6 or NovoPen Echo Plus) alongside continuous glucose monitoring (CGM).

RESEARCH DESIGN AND METHODS

Data were aggregated over 14-day periods. Treatment adherence was defined according to the number of missed basal and missed bolus insulin doses and smart pen engagement according to the number of days with data uploads.

RESULTS

Data from 3,945 adults, including 25,157 14-day periods with ≥70% CGM coverage, were analyzed. On average, 0.2 basal and 6.0 bolus insulin doses were missed over 14 days. The estimated probability of missing at least one basal insulin dose over a 14-day period was 17.6% (95% CI 16.5, 18.7). Missing one basal or bolus insulin dose per 14 days was associated with a significant decrease in percentage of time with glucose levels in range (TIR) (3.9-10.0 mmol/L), of -2.8% (95% CI -3.7, -1.8) and -1.7% (-1.8, -1.6), respectively; therefore, missing two basal or four bolus doses would decrease TIR by >5%. Smart pen engagement was associated positively with glycemic outcomes.

CONCLUSIONS

This combined analysis of real-world smart pen and CGM data showed that missing two basal or four bolus insulin doses over a 14-day period would be associated with a clinically relevant decrease in TIR. Smart insulin pens provide valuable insights into treatment injection behaviors.

Real-World Continuous Glucose Monitoring Data from a Population with Type 1 Diabetes in South Korea: Nationwide Single-System Analysis

Background: We used continuous glucose monitoring (CGM) data to investigate glycemic outcomes in a real-world population with type 1 diabetes (T1D) from South Korea, where the widespread use of CGM and the nationwide education program began almost simultaneously. Methods: Data from Dexcom G6 users with T1D in South Korea were collected between January 2019 and January 2023. Users were included if they provided at least 90 days of glucose data and used CGM at least 70% of the days in the investigational period. The relationship between CGM utilization and glycemic metrics, including the percentage of time in range (TIR), time below range (TBR), and time above range (TAR), was assessed. The study was approved by the Institutional Review Board of Samsung Medical Center (SMC 2023-05-030). Results: A total of 2288 users were included. Mean age was 41.5 years (57% female), with average uploads of 428 days. Mean TIR was 62.4% ± 18.5%, mean TBR <70 mg/dL was 2.6% ± 2.8%, mean TAR >180 mg/dL was 35.0% ± 19.3%, mean glucose was 168.1 ± 35.8 mg/dL, mean glucose management indicator was 7.2% ± 0.9%, and mean coefficient of variation was 36.7% ± 6.0%. Users with higher CGM utilization had higher TIR (67.8% vs. 52.7%), and lower TBR <70 mg/dL (2.3% vs. 4.7%) and TAR >180 mg/dL (30.0% vs. 42.6%) than those with low CGM utilization (P < 0.001 for all). Users whose data were shared with others had higher TIR than those who did not (63.3% vs. 60.8%, P = 0.001). Conclusions: In this South Korean population, higher CGM utilization was associated with a favorably higher mean TIR, which was close to the internationally recommended target. Using its remote data-sharing feature showed beneficial impact on TIR.

Glucose metrics improvement in youths with type 1 diabetes using the Ambulatory Glucose Profile report: A real-world study

AIMS

In this study, we aimed to analyze the possible change in Time In Range (TIR) in subjects with type 1 diabetes (T1D) using the Ambulatory Glucose Profile (AGP) and to identify the main socio-demographic and clinical predictors of sustained use.

METHODS

143 youths wearing instant-scanning CGM received structured counseling on the AGP report interpretation, and who were able to use AGP at least every 14 days were enrolled in group A (n = 100), whereas no users were considered as group B (n = 43). Socio-demographic data at the enrollment, clinical data, and glucose metrics were collected at baseline and during quarterly consultations. Metabolic outcomes were evaluated during follow-up, and a comparison between groups A and B was performed.

RESULTS

In group A compared to group B, at 12 months, the percentage of sensor usage and TIR were higher (p = 0.04 and p = 0.02), and Time Above Range and HbA1c were lower (p = 0.0004, p < 0.0001, respectively). Multiple logistic regression analysis did not show a significant relationship between sustained AGP software usage and the variables analyzed.

CONCLUSIONS

Systematic use of the AGP software was feasible and showed improved metabolic control in youths with T1D. This may be related to increased sensor usage and more informed decisions.

Effect of switch from flash glucose monitoring to flash glucose monitoring with real-time alarms on hypoglycaemia in people with type 1 diabetes mellitus

We aimed to evaluate the utility of the FreeStyle Libre 2 device for reducing time below range level 1 and level 2 compared with the Freestyle Libre device (without alarms) in people with type 1 diabetes mellitus. We conducted longitudinal observational follow-up study of a cohort of 100 people with type 1 diabetes mellitus who had switched from FreeStyle Libre to FreeStyle Libre 2 as part of routine clinical practice. Three months after switching to FreeStyle Libre 2, compared with results with FreeStyle Libre, there were a significant improvements in time below range level 1 (p = 0.02) and level 2 (p <0.001), time in range (p <0.001), time above range level 1 (p = 0.002), glucose management indicator (p= 0.04) and mean glucose (p= 0.04) during follow-up. Furthermore there was a significant direct association between age and change in TIR with a coefficient of 0.23, and a significant inverse association between age and change in TAR-1 with a coefficient of 0.11. Switching to a flash glucose monitoring system with alarms improves time below range, time in range and coefficient of variation in people with type 1 diabetes mellitus.

Rapid Improvement in Weight, Body Composition, and Glucose Variability With Semaglutide in Type 1 Diabetes

The efficacy of glucagon-like peptide-1 receptor agonists (GLP1-RA) in type 2 diabetes mellitus is well-established. GLP1-RAs are not approved for use in type 1 diabetes mellitus (T1DM). A 34-year-old woman with a 23-year history of T1DM presented for review for weight gain (weight 63 kg, BMI 26.9 kg/m2) and increased HbA1c (8.3%) and glycemic variability. Subcutaneous semaglutide (1 mg weekly) was commenced. After two months, there was decrease in weight by 12 kg, body fat percent by 15%, visceral fat by 7%, and a reduction in insulin dose, glycemic variability, and HbA1c. Semaglutide could be an important adjunct to insulin treatment in T1DM.

The IDEAL (Insulin therapy DE-intensificAtion with iglarLixi) Randomised Controlled Trial-Study Design and Protocol

INTRODUCTION

Multiple daily injection insulin regimen (MDI) represents the most intensive insulin regimen used in the management of people with type 2 diabetes (PwT2D). Its efficacy regarding glycaemic control is counterbalanced by the increased risk of hypoglycaemia, frequently observed tendency to weight gain and necessity for frequent glucose monitoring. Recent introduction of novel antidiabetic medications with pleiotropic effects reaching far beyond the reduction of glycaemia (HbA1c), such as the glucagon-like peptide 1 receptor agonist (GLP-1 RA), has significantly widened the therapeutic options available for management of T2D. Consequently, there is currently a substantial number of PwT2D for whom the MDI regimen was initiated at a time when no other options were available. Yet, in present times, these individuals could benefit from simplified insulin regimens ideally taking advantage of the beneficial effects of the novel classes of antidiabetic medications. iGlarLixi (Suliqua®) is a once-daily fixed-ratio combination of basal insulin analogue glargine 100 U/ml and a GLP-1 RA lixisenatide.

METHODS

Insulin therapy DE-intensificAtion with iglarLixi (IDEAL) is a six-centre, open-label, parallel-group, active comparator, phase IV randomised controlled trial with a 24-week active treatment period examining the efficacy and safety of MDI regimen de-intensification with once-daily administration of iGlarLixi versus MDI regimen continuation in PwT2D on a backgroud therapy with metformin ± sodium-glucose cotransporter 2 inhibitor.

PLANNED OUTCOMES

The primary objective is to compare the effects of MDI therapy de-intensification with iGlarLixi versus MDI regimen continuation regarding glycaemic control (HbA1c). Secondary objectives include detailed evaluation of the effects of MDI regimen de-intensification with iGlarLixi on glycaemic control using standardised continuous glucose monitoring (CGM) metrics and self-monitoring of plasma glucose. Furthermore, body weight and body composition analysis, quality of life and safety profile are evaluated.

TRIAL REGISTRATION

ClinicalTrials.gov, identifier NCT04945070.

Associations between daily step count classifications and continuous glucose monitoring metrics in adults with type 1 diabetes: analysis of the Type 1 Diabetes Exercise Initiative (T1DEXI) cohort

AIMS/HYPOTHESIS

Adults with type 1 diabetes should perform daily physical activity to help maintain health and fitness, but the influence of daily step counts on continuous glucose monitoring (CGM) metrics are unclear. This analysis used the Type 1 Diabetes Exercise Initiative (T1DEXI) dataset to investigate the effect of daily step count on CGM-based metrics.

METHODS

In a 4 week free-living observational study of adults with type 1 diabetes, with available CGM and step count data, we categorised participants into three groups-below (<7000), meeting (7000-10,000) or exceeding (>10,000) the daily step count goal-to determine if step count category influenced CGM metrics, including per cent time in range (TIR: 3.9-10.0 mmol/l), time below range (TBR: <3.9 mmol/l) and time above range (TAR: >10.0 mmol/l).

RESULTS

A total of 464 adults with type 1 diabetes (mean±SD age 37±14 years; HbA1c 48.8±8.1 mmol/mol [6.6±0.7%]; 73% female; 45% hybrid closed-loop system, 38% standard insulin pump, 17% multiple daily insulin injections) were included in the study. Between-participant analyses showed that individuals who exceeded the mean daily step count goal over the 4 week period had a similar TIR (75±14%) to those meeting (74±14%) or below (75±16%) the step count goal (p>0.05). In the within-participant comparisons, TIR was higher on days when the step count goal was exceeded or met (both 75±15%) than on days below the step count goal (73±16%; both p<0.001). The TBR was also higher when individuals exceeded the step count goals (3.1%±3.2%) than on days when they met or were below step count goals (difference in means -0.3% [p=0.006] and -0.4% [p=0.001], respectively). The total daily insulin dose was lower on days when step count goals were exceeded (0.52±0.18 U/kg; p<0.001) or were met (0.53±0.18 U/kg; p<0.001) than on days when step counts were below the current recommendation (0.55±0.18 U/kg). Step count had a larger effect on CGM-based metrics in participants with a baseline HbA1c ≥53 mmol/mol (≥7.0%).

CONCLUSIONS/INTERPRETATION

Our results suggest that, compared with days with low step counts, days with higher step counts are associated with slight increases in both TIR and TBR, along with small reductions in total daily insulin requirements, in adults living with type 1 diabetes.

DATA AVAILABILITY

The data that support the findings reported here are available on the Vivli Platform (ID: T1-DEXI; https://doi.org/10.25934/PR00008428 ).

Metabolic effect of adrenaline infusion in people with type 1 diabetes and healthy individuals

AIMS/HYPOTHESIS

As a result of early loss of the glucagon response, adrenaline is the primary counter-regulatory hormone in type 1 diabetes. Diminished adrenaline responses to hypoglycaemia due to counter-regulatory failure are common in type 1 diabetes, and are probably induced by exposure to recurrent hypoglycaemia, however, the metabolic effects of adrenaline have received less research attention, and also there is conflicting evidence regarding adrenaline sensitivity in type 1 diabetes. Thus, we aimed to investigate the metabolic response to adrenaline and explore whether it is modified by prior exposure to hypoglycaemia.

METHODS

Eighteen participants with type 1 diabetes and nine healthy participants underwent a three-step ascending adrenaline infusion during a hyperinsulinaemic-euglycaemic clamp. Continuous glucose monitoring data obtained during the week before the study day were used to assess the extent of hypoglycaemia exposure.

RESULTS

While glucose responses during the clamp were similar between people with type 1 diabetes and healthy participants, plasma concentrations of NEFAs and glycerol only increased in the group with type 1 diabetes (p<0.001). Metabolomics revealed an increase in the most common NEFAs (p<0.01). Other metabolic responses were generally similar between participants with type 1 diabetes and healthy participants. Exposure to hypoglycaemia was negatively associated with the NEFA response; however, this was not statistically significant.

CONCLUSIONS/INTERPRETATION

In conclusion, individuals with type 1 diabetes respond with increased lipolysis to adrenaline compared with healthy participants by mobilising the abundant NEFAs in plasma, whereas other metabolic responses were similar. This may suggest that the metabolic sensitivity to adrenaline is altered in a pathway-specific manner in type 1 diabetes.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05095259.

A comparison of the usage of an open-source automated insulin delivery system and the MiniMed™ 780 G system in children and adolescents with type 1 diabetes in real-world settings: the AWeSoMe study group

PURPOSE

In recent years there has been a noticeable increase in the use of advanced hybrid closed-loop systems (AHCLs) for managing type 1 diabetes (T1D) among youth. However, there is a lack of comparison between the open-source automated insulin delivery (AID) system and the MiniMed™ 780 G system (780 G).

METHODS

In this multi-center study, we retrospectively compared selected glycemic ranges of 26 individuals who used open-source AID and 20 individuals who used 780 G (age 11.3 years [IQR 9.3, 12.9] and 13.4 years [IQR 10.9, 16.5], respectively, p = 0.069) from system initiation to the most recent visit.

RESULTS

At baseline, the median HbA1c was significantly lower and the time below range (TBR)<54mg/dL was significantly higher in the open-source AID group compared to the 780 G group (6.8% [IQR 6.4, 7.1] vs. 7.4% [IQR 6.9, 8.6], p = 0.006 and (1.0% [IQR 0.5, 2.8] vs. 0.0% [0.0, 1.0], p = 0.014), respectively; the median time in range (TIR70-180mg/dL) was similar (p = 0.068). After a median duration of 10.9 months on AHCLs the reduction of HbA1c was similar ( ~ 0.3%). The time spent in the hypoglycemic ranges was longer among users of the open-source AID compared to 780 G (TBR54-70mg/dL 4.2% [IQR 2.6, 7.3] vs. 2.0% [1.0, 4.0], p = 0.005) and TBR<54mg/dL 1.1% [IQR 0.4, 2.3] vs. 0.0 [0.0, 1.0], p = 0.001).

CONCLUSIONS

Both AHCLs similarly improved HbA1c and TIR70-180mg/dL. The open-source AID youth had better glycemic control but spent longer time in the hypoglycemic range. These findings must be considered when choosing the use of AHCL technologies.

Diabetes technology and sexual health: which role?

PURPOSE

The aim of this review is to evaluate the effects of new technology used in the management of diabetes mellitus (DM), including the use of continuous glucose monitoring (CGM) and the administration of insulin through continuous subcutaneous insulin infusion (CSII), on male and female sexual function.

METHODS

This narrative review was performed for all available prospective, retrospective and review articles, published up to June 2023 in PubMed. Data were extracted from the text and from the tables of the manuscript.

RESULTS

Sexual dysfunctions are an underestimated comorbidity of DM in both male and female. Although erectile dysfunction (ED) is recognized by the guidelines as a complication of DM, female sexual dysfunction (FSD) is poorly investigated in clinical setting. In addition to the complications of DM, the different types of therapies can also influence male and female sexual response. Furthermore, insulin therapy can be administered through multiple-daily injections (MDI) or a CSII. The new technologies in the field of DM allow better glycemic control which results in a reduction in the occurrence or aggravation of complications of DM. Despite this evidence, few data are available on the impact of new technologies on sexual dysfunctions.

CONCLUSIONS

The use of DM technology might affect sexual function due to the risk of a worse body image, as well as discomfort related to CSII disconnection during sexual activity. However, the use is related to an improved metabolic control, which, in the long-term associates to a reduction in all diabetes complications, including sexual function.

12-Month Real-Life Efficacy of the MiniMed 780G Advanced Closed-Loop System in Patients Living with Type 1 Diabetes: A French Observational, Retrospective, Multicentric Study

Aim: To evaluate the evolution of glycemic outcomes in patients living with type 1 diabetes (T1D) after 1 year of use of the MiniMed 780G advanced hybrid closed-loop (AHCL) system. Methods: We conducted an observational, retrospective, multicentric study in 20 centers in France. The primary objective was to evaluate the improvement in glycemic control after 1-year use of AHCL. The primary endpoint was the variation of time in range (TIR) between pre-AHCL and after 1-year use of AHCL. Secondary objectives were to analyze the glycemic outcomes after 3, 6, and 12 months of AHCL use, the safety, and the long-term observance of AHCL. Results: Two hundred twenty patients were included, and 200 were analyzed for the primary endpoint. 92.7% of patients continued to use AHCL. After 1 year of use of AHCL, TIR was 72.5% ± 10.6% (+9.1%; 95% confidence interval [CI] [7.6-10.5] compared to pre-AHCL initiation, P < 0.001), HbA1c 7.1% ± 0.7% (-0.5%; 95% CI [-0.6 to -0.4]; P < 0.001), time below range 2.0% [1.0; 3.0] (0.0% [-2.0; 0.0], P < 0.001), and time above range 24.8% ± 10.9% (-7.3%; 95% CI [-8.8 to -5.7]; P < 0.001). More patients achieved the glycemic treatment goals of HbA1c <7.0% (45.1% vs. 18.1%, P < 0.001) and TIR >70% (59.0% vs. 29.5% P < 0.001) when compared with pre-AHCL. Five patients experienced severe hypoglycemia events and two patients experienced ketoacidosis. Conclusion: After 1 year of use of AHCL, people living with T1D safely improved their glucose control and a higher proportion of them achieved optimal glycemic control.

Time-in-Range With Insulin Versus Metformin in Gestational Diabetes Mellitus Using Continuous Glucose Monitoring: A Randomized Control Study at a Tertiary Care Centre in South India

Background The prevalence of gestational diabetes mellitus (GDM) is increasing globally. When diet and lifestyle modifications are inadequate for control, managing GDM often involves insulin or metformin. Metformin's oral administration option improves patient compliance and acceptance, but concerns about its use persist, necessitating careful evaluation. Comparative studies between insulin and metformin in GDM are scarce. In pregnancies complicated by diabetes, precise glucose control is crucial for maternal-fetal well-being, and continuous glucose monitoring (CGM) plays a valuable role in achieving recommended targets. CGM provides comprehensive glucose profiles, including postprandial glucose excursions and details about time spent in hypoglycemia, euglycemia, and hyperglycemia. The time-in-range (TIR) metric, when used alongside A1C, offers more actionable information than A1C alone. To the best of our knowledge, no published trials compare TIR in GDM with metformin or insulin aspart/detemir, specifically focusing on CGM metrics. This randomized controlled trial (RCT) aims to assess TIR in women with GDM treated with either metformin or insulin. Materials and methods This study was a non-inferiority randomized control trial evaluating TIR in GDM using continuous glucose monitoring with metformin or insulin. Forty-four women with GDM were enrolled. The diagnosis of GDM was based on the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. CGM readings were collected for 14 days after sensor activation. Results In our study, 44 women with GDM completed the protocol, with 22 in the Metformin group and 22 in the Insulin group. Baseline characteristics did not differ between the groups. Age, BMI pre-gravid, BMI at 28 weeks, parity, family history of diabetes mellitus, previous history of GDM, glycated hemoglobin (HbA1c), oral glucose tolerance tests (OGTT) at zero hours, one hour, and two hours, as well as gestational weeks, did not significantly differ between the two groups. The metformin and insulin groups did not differ significantly in CGM metrics, including TIR, time above range, time below range, mean glucose, and glucose management indicator. Conclusion Based on our findings, the metformin and insulin groups did not differ in CGM metrics, including TIR, time above range, time below range, mean glucose, and glucose management indicator. In clinical practice, CGM metrics complement fasting blood glucose, postprandial glucose, and HbA1c as appropriate and useful clinical targets and outcome measurements. Metformin's oral administration option offers advantages such as improved patient compliance and acceptance in women with GDM.

Effects of Macronutrient Intake and Number of Meals on Glycemic Outcomes Over 1 Year in Youth with Type 1 Diabetes

Objective: Insulin bolus doses derive from glucose levels and planned carbohydrate intake, although fat and protein impact glycemic excursions. We examined the impact of macronutrients and number of daily meals/snacks on glycemic outcomes in youth with type 1 diabetes. Methods: Youth (N = 136, ages 8-17) with type 1 diabetes completed 3-day food records, wore 3-day masked continuous glucose monitoring, and had A1c measurements every 3 months for 1 year. Diet data were analyzed using Nutrition Data System for Research. Longitudinal mixed models assessed effects of macronutrient intake and number of meals/snacks on glycemic outcomes. Results: At baseline, youth (48% male) had mean age of 12.8 ± 2.5 years and diabetes duration of 5.9 ± 3.1 years; 73% used insulin pumps. Baseline A1c was 8.1% ± 1.0%, percent time in range 70-180 mg/dL (%TIR) was 49% ± 17%, % time below range <70 mg/dL (%TBR) was 6% ± 8%, % time above range >180 mg/dL (%TAR) was 44% ± 20%, and glycemic variability as coefficient of variation (CV) was 41% ± 8%; macronutrient intake included 48% ± 5% carbohydrate, 36% ± 5% fat, and 16% ± 2% protein. Most youth (56%) reported 3-4 meals/snacks daily (range 1-9). Over 1 year, greater carbohydrate intake was associated with lower A1c (P = 0.0003), more %TBR (P = 0.0006), less %TAR (P = 0.002), and higher CV (P = 0.03). Greater fat intake was associated with higher A1c (P = 0.006), less %TBR (P = 0.002), and more %TAR (P = 0.005). Greater protein intake was associated with higher A1c (P = 0.01). More daily meals/snacks were associated with lower A1c (P = 0.001), higher %TIR (P = 0.0006), and less %TAR (P = 0.0001). Conclusions: Both fat and protein impact glycemic outcomes. Future automated insulin delivery systems should consider all macronutrients for timely insulin provision. The present research study derived from secondary analysis of the study registered under NCT00999375.

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.

Retrospective observational study on real world use of the Minimed™ 780G automated insulin delivery system: Impact of the settings on autocorrection and omitted meal boluses

INTRODUCTION

The Medtronic MiniMed™ 780G (MM780G) system uses an algorithm that includes autocorrection bolus (AB) delivery. This study evaluates the impact of omitted meal boluses and the system settings, glucose target and active insulin time (AIT), on the AB.

METHOD

Retrospective observational study on data uploaded by all MiniMed 780G users in our healthcare area, obtained through the remote monitoring platform Care Connect, from April to August 2023. Downloads with a sensor usage time <95% were excluded.

RESULTS

235 downloads belonging to 235 users were analysed. AB delivery was significantly higher at 2 h AIT (36.08 ± 13.17%) compared to the rest of settings (2.25-4 h) (26.43 ± 13.2%) (p < 0.001). AB differences based on the glucose target were not found. Patients with <3 meal boluses per day had higher AB delivery (46.91 ± 19.00% vs 27.53 ± 11.54%) (p < 0.001) and had more unfavourable glucometric parameters (GMI 7.12 ± 0.45%, TIR 67.46 ± 12.89% vs GMI 6.78 ± 0.3%, TIR 76.51 ± 8.37%) (p < 0.001). However, the 2-h AIT group presented similar TAR, TIR and GMI regardless of the number of meal boluses.

CONCLUSION

The fewer user-initiated boluses, the greater the autocorrection received. The active insulin time of 2 h entails a more active autocorrection pattern that makes it possible to more effectively compensate for the omission of meal boluses without increasing hypoglycaemias.

During an 18-month course of automated insulin delivery treatment, children aged 2 to 6 years achieve and maintain a higher time in tight range

AIMS

To investigate whether the positive effects on glycaemic outcomes of 3-month automated insulin delivery (AID) achieved in 2- to 6-year-old children endure over an extended duration and how AID treatment affects time in tight range (TITR), defined as 3.9-7.8 mmol/L.

RESEARCH DESIGN AND METHODS

We analysed 18 months of follow-up data from a non-randomized, prospective, single-arm clinical trial (n = 35) conducted between 2021 and 2023. The main outcome measures were changes in time in range (TIR), glycated haemoglobin (HbA1c), time above range (TAR), TITR, and mean sensor glucose (SG) value during follow-up visits (at 0, 6, 12 and 18 months). The MiniMed 780G AID system in SmartGuard Mode was used for 18 months. Parental diabetes distress was evaluated at 3 and 18 months with the validated Problem Areas in Diabetes-Parent, revised (PAID-PR) survey.

RESULTS

Between 0 and 6 months, TIR and TITR increased, and HbA1c, mean SG value and TAR decreased significantly (p < 0.001); the favourable effect persisted through 18 months of follow-up. Between 3 and 18 months, PAID-PR score declined significantly (0 months: mean score 37.5; 3 months: mean score 28.6 [p = 0.06]; 18 months: mean score 24.6 [p < 0.001]).

CONCLUSIONS

Treatment with AID significantly increased TITR and TIR in young children. The positive effect of AID on glycaemic control observed after 6 months persisted throughout the 18 months of follow-up. Similarly, parental diabetes distress remained reduced during 18 months follow-up. These findings are reassuring and suggest that AID treatment improves glycaemic control and reduces parental diabetes distress in young children over an extended 18-month follow-up.

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.

HbA1c overestimates the glucose management indicator: a pilot study in patients with diabetes, chronic kidney disease not on dialysis, and anemia using isCGM

Introduction

There are multiple mechanisms by which HbA1c values can be altered in chronic kidney disease (CKD), which limits its usefulness as a strategy to assess glycemic control in this population.

Methods

Concordance and agreement study between two diagnostic tests: HbA1c and glucose management indicator (GMI) measured by intermittently scanned continuous glucose monitoring (isCGM), based in a prospective cohort of patients with diabetes, CKD (glomerular filtration rate between 15 and 60 ml/min/1.73 m²), and anemia. The isCGM was performed for 3 months, and the GMI was compared with the HbA1c levels taken at the end of isCGM. Agreement was evaluated using Bland-Altman graph analysis and Lin's concordance correlation coefficient (CCC). The concordance of the measures with good glycemic control (<7%) was also evaluated.

Results

A total of 74 patients were enrolled (median age 68.5 years, 51.3% female, 64.9% with CKD stage 3, hemoglobin 11.1 ± 1.2 g/l). The Bland-Altman analysis shows a mean difference between GMI and HbA1c of 0.757 ± 0.687% (95% limits of agreement: -0.590 and 2.105). Difference was greater as the values of GMI and HbA1c increased. The agreement was poor [CCC 0.477; 95% confidence interval (CI): 0.360-0.594], as well as the concordance of values with good glycemic control according to GMI versus HbA1c (67.5% versus 29.7%, p < 0.001) (Kappa 0.2430; 95% CI: 0.16-0.32).

Conclusion

The HbA1c overestimates the GMI values with highly variable ranges of difference, which prevents a precise correction factor. isCGM probably is a safer option for monitoring and decision-making in this population, especially in patients treated with insulin where the risk of hypoglycemia is greater.

Real-Life Achievements of MiniMed 780G Advanced Closed-Loop System in Youth with Type 1 Diabetes: AWeSoMe Study Group Multicenter Prospective Trial

Background: We assessed real-life glycemic outcomes and predictors of composite measures of optimal glycemic control in children and adolescents with type 1 diabetes (T1D) during their initial 12 months of the MiniMed™ 780G use. Methods: This prospective observational multicenter study collected demographic, clinical, and 2-week 780G system data at five time points. Optimal glycemic control was defined as a composite glycemic control (CGC) score requiring the attainment of four recommended continuous glucose monitoring (CGM) targets, as well as the glycemia risk index (GRI) of hypoglycemia and hyperglycemia and composite CGM index (COGI). Outcome measures included longitudinal changes in multiple glycemic parameters and CGC, GRI, and COGI scores, as well as predictors of these optimal measures. Results: The cohort included 93 children, 43% girls, with a median age of 15.1 years (interquartile range [IQR] 12.9,17.0). A longitudinal analysis adjusted for age and socioeconomic index yielded a significant improvement in glycemic control for the entire cohort (ptime < 0.001) after the transition to 780G. The mean hemoglobin A1c (HbA1c) (SE) was 8.65% (0.12) at baseline and dropped by >1% after 1 year to 7.54% (0.14) (ptime < 0.001). Optimal glycemic control measures improved at 12 months post 780G; CGC improved by 5.6-fold (P < 0.001) and was attained by 24% of the participants, the GRI score improved by 10-fold (P = 0.009) and was achieved by 10% of them, and the COGI improved by 7.6-fold (P < 0.001) and was attained by 20% of them. Lower baseline HbA1c levels and increased adherence to Advanced Hybrid Closed-Loop (AHCL) usage were predictors of achieving optimal glycemic control. Conclusions: The AHCL 780G system enhances glycemic control in children and adolescents with T1D, demonstrating improvements in HbA1c and CGM metrics, albeit most participants did not achieve optimal glycemic control. This highlights yet ongoing challenges in diabetes management, emphasizing the need for continued proactive efforts on the part of health care professionals, youth, and caregivers.

Utility of time in tight range (TITR) in evaluating metabolic control in pediatric and adult patients with type 1 diabetes in treatment with advanced hybrid closed-loop systems

PURPOSE

To analyze the time in tight range (TITR), and its relationship with other glucometric parameters in patients with type 1 diabetes (T1D) treated with advanced hybrid closed-loop (AHCL) systems.

METHODS

A prospective observational study was conducted on pediatric and adult patients with T1D undergoing treatment with AHCL systems for at least 3 months. Clinical variables and glucometric parameters before and after AHCL initiation were collected.

RESULTS

A total of 117 patients were evaluated. Comparison of metabolic control after AHCL initiation showed significant improvements in HbA1c (6.9 ± 0.9 vs. 6.6 ± 0.5%, p < 0.001), time in range (TIR) (68.2 ± 11.5 vs. 82.5 ± 6.9%, p < 0.001), TITR (43.7 ± 10.8 vs. 57.3 ± 9.7%, p < 0.001), glucose management indicator (GMI) (6.9 ± 0.4 vs. 6.6 ± 0.3%, p < 0.001), time below range (TBR) 70-54 mg/dl (4.3 ± 4.5 vs. 2.0 ± 1.4%, p < 0.001), and time above range (TAR) > 180 mg/dl (36.0 ± 7.6 vs. 15.1 ± 6.4%, p < 0.001). Coefficient of variation (CV) also improved (36.3 ± 5.7 vs. 30.6 ± 3.7, p < 0.001), while time between 140-180 mg/dl remained unchanged. In total, 76.3% achieved TITR > 50% (100% pediatric). Correlation analysis between TITR and TIR and GRI showed a strong positive correlation, modified by glycemic variability.

CONCLUSIONS

AHCL systems achieve significant improvements in metabolic control (TIR > 70% in 93.9% patients). The increase in TIR was not related to an increase in TIR 140-180 mg/dl. Despite being closely related to TIR, TITR allows for a more adequate discrimination of the achieved control level, especially in a population with good initial metabolic control. The correlation between TIR and TITR is directly influenced by the degree of glycemic variability.

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.

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

INTRODUCTION

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

METHOD

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

RESULTS

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

CONCLUSION

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

Extended-Release Versus Immediate-Release Triamcinolone Acetonide in Patients Who Have Knee Osteoarthritis and Type 2 Diabetes Mellitus

BACKGROUND

Intra-articular corticosteroid injections may cause hyperglycemia (glucose level >180 mg/dL). In a phase 2 study of 33 patients who had osteoarthritis of the knee and type 2 diabetes mellitus, triamcinolone acetonide extended-release (TA-ER) was associated with minimal glycemic control disruption compared with triamcinolone acetonide immediate-release (TA-IR). This post hoc analysis characterizes the clinical relevance of these results.

METHODS

Patients who had symptomatic osteoarthritis of the knee for ≥6 months, type 2 diabetes mellitus for ≥1 year, and hemoglobin A1c ≥6.5 and ≤9.0% were randomized to receive an intra-articular injection of either TA-ER or TA-IR. Changes in continuous glucose monitor daily glucose level, percentage of time in or above the target glucose range (>70 to 180 mg/dL), time to glucose level 250 mg/dL and maximum glucose level >250 mg/dL, and glycemic variability were evaluated.

RESULTS

Across postinjection days 1 to 3, the TA-ER group (n = 18) had a lower median change from baseline in maximum glucose level (92.3 versus 169.1 mg/dL), a reduced percentage of time with a glucose level >250 mg/dL (12 versus 26%), a smaller proportion of patients who had a maximum glucose level >250 mg/dL (50 versus 93%), and a greater percentage of time in the target glucose range (62 versus 48%) versus the TA-IR group (n = 15). There was less glycemic variability and lower glucose spikes in the TA-ER versus TA-IR group. Median times to glucose level 250 mg/dL (44 versus 6 hours) and maximum glucose level (34 versus 13 hours) were significantly longer in the TA-ER versus TA-IR group.

CONCLUSIONS

Use of TA-ER was associated with a clinically meaningful reduction in hyperglycemia versus TA-IR.

Association between proinflammatory cytokines and arterial stiffness in type 1 diabetic adolescents

OBJECTIVES

Type 1 diabetes mellitus is considered a state of chronic low-grade inflammation and activation of the innate immune system, which is regulated by several proinflammatory cytokines and other acute-phase reactants. Arterial stiffness, a dynamic property of the vessels evaluated by the determination of pulse wave velocity (PWV), is increased in diabetic patients and is associated with microvascular and macrovascular complications of diabetes and higher cardiovascular risk. In the present study, we aimed to compare the proinflammatory state and arterial stiffness in diabetic and non-diabetic adolescents, and to characterize the association between these two parameters.

METHODS

Twenty-three type 1 diabetic patients, aged 12-16 years, followed at a tertiary center, and 23 adolescents nonoverweighted healthy controls, from a Portuguese birth-cohort, were included in the present analysis. Anthropometry, blood pressure, glycemic control data, and lipid parameters were collected. Arterial stiffness was evaluated by carotid-femoral pulse wave velocity. Proinflammatory cytokines' concentrations (TNF-α, IL-1β, IL-6, IL-10, IFN-γ, and GM-CSF) were quantified by multiplex immunoassays using a Luminex 200 analyzer.

RESULTS

There were no statistically significant differences between the proinflammatory cytokines' concentrations in the two groups. PWV [6.63 (6.23-7.07) vs. 6.07 (5.15-6.65) m/s, p=0.015] was significantly higher in the diabetic group. PWV was negatively correlated with GM-CSF (ρ=-0.437, p=0.037) in the diabetic group. A linear association was found between diabetes duration and PWV (with PWV increasing by 0.094 m/s (95 % confidence interval, 0.019 to 0.169) per month of disease duration). In the diabetic group, HbA1c was negatively correlated with IL-10 (ρ=-0.473, p=0.026). Negative correlations were also found between IL-10 and total, HDL, and LDL cholesterol only in the diabetic group.

CONCLUSIONS

Diabetic adolescent patients present higher PWV, when compared to their healthy counterparts, even though we could not find differences in the levels of several proinflammatory cytokines between the two groups. The negative correlation found between IL-10 and HbA1c might translate a protective counterbalance effect of this anti-inflammatory cytokine, which might also explain the negative correlations found with blood lipids. Further studies are needed to better clarify the association between arterial stiffness and the proinflammatory milieu of diabetes.

The association of chronic complications with time in tight range and time in range in people with type 1 diabetes: a retrospective cross-sectional real-world study

AIMS/HYPOTHESIS

The aim of this study was to evaluate the association of chronic complications with time in tight range (TITR: 3.9-7.8 mmol/l) and time in range (TIR: 3.9-10.0 mmol/l) in people with type 1 diabetes.

METHODS

The prevalence of microvascular complications (diabetic retinopathy, diabetic nephropathy and diabetic peripheral neuropathy [DPN]) and macrovascular complications according to sensor-measured TITR/TIR was analysed cross-sectionally in 808 adults with type 1 diabetes. Binary logistic regression was used to evaluate the association between TITR/TIR and the presence of complications without adjustment, with adjustment for HbA1c, and with adjustment for HbA1c and other confounding factors (sex, age, diabetes duration, BMI, BP, lipid profile, smoking, and use of statins and renin-angiotensin-aldosterone system inhibitors).

RESULTS

The mean TITR and TIR were 33.9 ± 12.8% and 52.5 ± 15.0%, respectively. Overall, 46.0% had any microvascular complication (34.5% diabetic retinopathy, 23.8% diabetic nephropathy, 16.0% DPN) and 16.3% suffered from any macrovascular complication. The prevalence of any microvascular complication, diabetic retinopathy, diabetic nephropathy and a cerebrovascular accident (CVA) decreased with increasing TITR/TIR quartiles (all ptrend<0.05). Each 10% increase in TITR was associated with a lower incidence of any microvascular complication (OR 0.762; 95% CI 0.679, 0.855; p<0.001), diabetic retinopathy (OR 0.757; 95% CI 0.670, 0.856; p<0.001), background diabetic retinopathy (OR 0.760; 95% CI 0.655, 0.882; p<0.001), severe diabetic retinopathy (OR 0.854; 95% CI 0.731, 0.998; p=0.048), diabetic nephropathy (OR 0.799; 95% CI 0.699, 0.915; p<0.001), DPN (OR 0.837; 95% CI 0.717, 0.977; p=0.026) and CVA (OR 0.651; 95% CI 0.470, 0.902; p=0.010). The independent association of TITR with any microvascular complication (OR 0.867; 95% CI 0.762, 0.988; p=0.032), diabetic retinopathy (OR 0.837; 95% CI 0.731, 0.959; p=0.010), background diabetic retinopathy (OR 0.831; 95% CI 0.705, 0.979; p=0.027) and CVA (OR 0.619; 95% CI 0.426, 0.899; p=0.012) persisted after adjustment for HbA1c. Similar results were obtained when controlling for HbA1c and other confounding factors.

CONCLUSIONS/INTERPRETATION

TITR and TIR are inversely associated with the presence of microvascular complications and CVA in people with type 1 diabetes. Although this study was not designed to establish a causal relationship, this analysis adds validity to the use of TITR and TIR as key measures in glycaemic management.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02601729 and NCT02898714.

Automated Insulin Delivery Systems in Pediatric Type 1 Diabetes: A Narrative Review

This narrative review assesses the use of automated insulin delivery (AID) systems in managing persons with type 1 diabetes (PWD) in the pediatric population. It outlines current research, the differences between various AID systems currently on the market and the challenges faced, and discusses potential opportunities for further advancements within this field. Furthermore, the narrative review includes various expert opinions on how different AID systems can be used in the event of challenges with rapidly changing insulin requirements. These include examples, such as during illness with increased or decreased insulin requirements and during physical activity of different intensities or durations. Case descriptions give examples of scenarios with added user-initiated actions depending on the type of AID system used. The authors also discuss how another AID system could have been used in these situations.

Online Classification of Unstructured Free-Living Exercise Sessions in People with Type 1 Diabetes

Background: Managing exercise in type 1 diabetes is challenging, in part, because different types of exercises can have diverging effects on glycemia. The aim of this work was to develop a classification model that can classify an exercise event (structured or unstructured) as aerobic, interval, or resistance for the purpose of incorporation into an automated insulin delivery (AID) system. Methods: A long short-term memory network model was developed with real-world data from 30-min structured sessions of at-home exercise (aerobic, resistance, or mixed) using triaxial accelerometer, heart rate, and activity duration information. The detection algorithm was used to classify 15 common free-living and unstructured activities and relate each to exercise-associated change in glucose. Results: A total of 1610 structured exercise sessions were used to train, validate, and test the model. The accuracy for the structured exercise sessions in the testing set was 72% for aerobic, 65% for interval, and 77% for resistance. In addition, we tested the classifier on 3328 unstructured sessions. We validated the session-associated change in glucose against the expected change during exercise for each type. Mean and standard deviation of the change in glucose of -20.8 (40.3) mg/dL were achieved for sessions classified as aerobic, -16.2 (39.0) mg/dL for sessions classified as interval, and -11.6 (38.8) mg/dL for sessions classified as resistance. Conclusions: The proposed algorithm reliably identified physical activity associated with expected change in glucose, which could be integrated into an AID system to manage the exercise disturbance in glycemia according to the predicted class.

Quality of life, diabetes-related stress and treatment satisfaction are correlated with glycemia risk index (GRI), time in range and hypoglycemia/hyperglycemia components in type 1 diabetes

INTRODUCTION

To evaluate the relationship between the GRI -component of hypoglycemia (CHypo) and hyperglycemia (CHyper)- with diabetes quality of life (DQoL), diabetes-related stress (DDS), perception of hypoglycemia (Clarke Test), visual analogic scale (VAS) and diabetes-knowledge (DKQ2) in T1D.

METHODS

Cross-sectional study in 92 patients with T1D under intensive insulin treatment (21.7% CSII) and flash glucose monitoring (isCGM). Clinical, metabolic and glycometric parameters and quality of life/satisfaction questionnaires were analyzed.

RESULTS

92 patients (54.3% male, BMI 25.4 ± 4.5 kg/m2, HbA1c 7.5 ± 1.0%, TIR 53.9 ± 15.9%) with mean age 36.1 ± 12.6years and 17.8 ± 11.3 T1D duration. The mean GRI was 60.6 ± 22.2 with a CHypo and CHyper of 5.9 ± 4.8 and 27.3 ± 14.4, respectively. 19.1% presented a pathological Clarke's test. Patients with TIR > 70% and GRI < 40 showed better VAS (8.8 ± 1.3 vs 9.3 ± 0.9, p < 0.05) and DDS (46.4 ± 22.1 vs 36.7 ± 16.6, p < 0.05) scores, showing no differences between groups. CHyper > 15 and Chypo > 3.4 were related to worse levels of DQoL (91.1 ± 23.9 vs 76.6 ± 18.6 and 94.6 ± 24.8 vs 79.8 ± 20.1, p < 0.01), DDS(49.8 ± 22.4 vs 35.7 ± 16.5 and 49.8 ± 22.4 vs 35.7 ± 16.5, p < 0.01),and DKQ2 (24.4 ± 4.3 vs 26.8 ± 5.2 and 24.1 ± 4.8 vs 26.0 ± 4.6, p < 0.05), respectively. Worse metabolic control defined by GRI correlated with worse scores in VAS (r = -0.209, p < 0.05), DQoL (r = 0.205, p < 0.05), and DDS (r = 0.205, p < 0.05). No difference was observed in knowledge´s scale. CHyper correlated with worse scores in VAS (r = -0.231, p < 0.05), DQoL (r = 0.422, p < 0.01), and DDS (r = 0.341, p < 0.01) and lower degree of knowledge DKQ2 (r = -0.231, p < 0.05). When analyzing DQoL as a dependent variable in a multiple lineal regression, only age (β = 0.747; p < 0.001) and CHyper (β = 0.717; p < 0.001) maintained statistical significance.

CONCLUSIONS

Higher GRI was related to worse quality of life, diabetes-related stress and satisfaction with treatment, analogous to the TIR results.CHyper an Chypo were related to a greater decline in quality of life, diabetes-related stress, and lower satisfaction with treatment.However, in a multiple linear regression, only CHyper maintained statistical significance.

Continuous Glucose Monitoring for Management of Type 2 Diabetes and Perinatal Outcomes

OBJECTIVE

To evaluate the association between continuous glucose monitoring in pregnant people with type 2 diabetes and perinatal outcomes.

METHODS

This was a retrospective cohort study of pregnant people with type 2 diabetes who received prenatal care and delivered singleton, nonanomalous neonates at a single academic tertiary care center from November 1, 2019, to February 28, 2023. The primary outcome was a composite of neonatal morbidity, including hypoglycemia, hyperbilirubinemia, shoulder dystocia, large for gestational age at birth, preterm birth, neonatal intensive care unit (NICU) admission, or perinatal death. Demographics and outcomes were compared by type of monitoring (continuous glucose monitoring vs intermittent self-monitoring of blood glucose), and multivariable logistic regression estimated the association between continuous glucose monitoring use and perinatal outcomes.

RESULTS

Of 360 pregnant people who met the inclusion criteria, 82 (22.7%) used continuous glucose monitoring. The mean gestational age at continuous glucose monitoring initiation was 21.3±6.4 weeks. The use of continuous glucose monitoring was associated with lower odds of the primary composite neonatal morbidity (65.9% continuous glucose monitoring vs 77.0% self-monitoring of blood glucose, adjusted odds ratio [aOR] 0.48, 95% CI, 0.24-0.94). Continuous glucose monitoring use was also associated with lower odds of preterm birth (13.4% vs 25.2%, aOR 0.48, 95% CI, 0.25-0.93) and NICU admission (33.8% vs 47.6%, aOR 0.36, 95% CI, 0.16-0.81).

CONCLUSION

In pregnant people with type 2 diabetes, continuous glucose monitoring use was associated with less neonatal morbidity, fewer preterm births, and fewer NICU admissions.

Heterogeneity of glycaemic phenotypes in type 1 diabetes

AIMS/HYPOTHESIS

Our study aims to uncover glycaemic phenotype heterogeneity in type 1 diabetes.

METHODS

In the Study of the French-speaking Society of Type 1 Diabetes (SFDT1), we characterised glycaemic heterogeneity thanks to a set of complementary metrics: HbA1c, time in range (TIR), time below range (TBR), CV, Gold score and glycaemia risk index (GRI). Applying the Discriminative Dimensionality Reduction with Trees (DDRTree) algorithm, we created a phenotypic tree, i.e. a 2D visual mapping. We also carried out a clustering analysis for comparison.

RESULTS

We included 618 participants with type 1 diabetes (52.9% men, mean age 40.6 years [SD 14.1]). Our phenotypic tree identified seven glycaemic phenotypes. The 2D phenotypic tree comprised a main branch in the proximal region and glycaemic phenotypes in the distal areas. Dimension 1, the horizontal dimension, was positively associated with GRI (coefficient [95% CI]) (0.54 [0.52, 0.57]), HbA1c (0.39 [0.35, 0.42]), CV (0.24 [0.19, 0.28]) and TBR (0.11 [0.06, 0.15]), and negatively with TIR (-0.52 [-0.54, -0.49]). The vertical dimension was positively associated with TBR (0.41 [0.38, 0.44]), CV (0.40 [0.37, 0.43]), TIR (0.16 [0.12, 0.20]), Gold score (0.10 [0.06, 0.15]) and GRI (0.06 [0.02, 0.11]), and negatively with HbA1c (-0.21 [-0.25, -0.17]). Notably, socioeconomic factors, cardiovascular risk indicators, retinopathy and treatment strategy were significant determinants of glycaemic phenotype diversity. The phenotypic tree enabled more granularity than traditional clustering in revealing clinically relevant subgroups of people with type 1 diabetes.

CONCLUSIONS/INTERPRETATION

Our study advances the current understanding of the complex glycaemic profile in people with type 1 diabetes and suggests that strategies based on isolated glycaemic metrics might not capture the complexity of the glycaemic phenotypes in real life. Relying on these phenotypes could improve patient stratification in type 1 diabetes care and personalise disease management.

Multilevel functional data analysis modeling of human glucose response to meal intake

Glucose meal response information collected via Continuous Glucose Monitoring (CGM) is relevant to the assessment of individual metabolic status and the support of personalized diet prescriptions. However, the complexity of the data produced by CGM monitors pushes the limits of existing analytic methods. CGM data often exhibits substantial within-person variability and has a natural multilevel structure. This research is motivated by the analysis of CGM data from individuals without diabetes in the AEGIS study. The dataset includes detailed information on meal timing and nutrition for each individual over different days. The primary focus of this study is to examine CGM glucose responses following patients' meals and explore the time-dependent associations with dietary and patient characteristics. Motivated by this problem, we propose a new analytical framework based on multilevel functional models, including a new functional mixed R-square coefficient. The use of these models illustrates 3 key points: (i) The importance of analyzing glucose responses across the entire functional domain when making diet recommendations; (ii) The differential metabolic responses between normoglycemic and prediabetic patients, particularly with regards to lipid intake; (iii) The importance of including random, person-level effects when modelling this scientific problem.

Efficacy and safety of advanced hybrid closed loop systems in children with type 1 diabetes younger than 6 years

Background

Tight glycemic control is essential for the normal growth and development of preschool children. The aim of our study was to evaluate the impact of advanced hybrid closed loop (AHCL) systems in a real-life setting in children younger than 6 years.

Methods

We conducted a two-center prospective study. We enrolled 19 patients with a median age at disease onset of 2.6 years [interquartile range (IQR) 1.6; 4.4] and a median disease duration of 1.4 years (IQR 0.9; 2.8) who were switched to AHCL from multiple daily injections or open-loop insulin therapy and with a 6-month follow-up. Clinical data, sensor glycemic metrics, and pump settings were collected and analyzed.

Results

After 6 months of follow-up, there was a significant reduction in median HbA1c (p = 0.0007) and glucose management indicator (p = 0.03). A reduction in both mild (>180 mg/dL) (p = 0.04) and severe (>250 mg/dL) (p = 0.01) hyperglycemia was observed after 1 month of auto mode, and in mild hyperglycemia, it persisted up to 6 months (p = 0.02). A small increase in time below range (<70 mg/dL) was observed (p = 0.04) without a significant difference in time <54 mg/dL (p = 0.73). Time in range increased significantly, reaching a 10% increment (p = 0.03) compared with baseline. A significant reduction in the average sensor glucose was observed (p = 0.01) while coefficient of glucose variability (CV%) remained stable (p = 0.12). No episodes of ketoacidosis or severe hypoglycemia have been recorded.

Conclusion

AHCL systems are effective and safe for children younger than 6 years and should be considered as a valid therapeutic option from diabetes onset.

Type 2 diabetes in latin America: recommendations on the flash glucose monitoring system

OBJECTIVE

To establish recommendations through the consensus of a Latin American experts panel on the use of the flash glucose monitoring system (fCGM) in people living with type 2 diabetes mellitus (T2DM) regarding the benefits and challenges of using the fCGM.

METHODS

An executive committee of experts was created, comprised by a panel of fifteen physicians, including endocrinologists and internal medicine physicians, with expertise in management of adult patients with T2DM. The experts were from various countries: Colombia, Chile, Peru, Mexico, Argentina, and Brazil. The modified Delphi method was used, considering a consensus level of at least 80% of the participants. A seventeen-item instrument was developed to establish recommendations on the use of fCGM in patients with T2DM in Latin American.

RESULTS

The number of glucose scans recommended per day with the fCGM for patients managed with oral antidiabetic drugs or basal insulin was a median of 6 scans per day, and for those managed with multiple insulin doses, a median of 10 scans per day was recommended. Additionally, a holistic and individualized management approach was recommended, taking into account new treatment directions and identifying patients who would benefit from the use of the fCGM.

CONCLUSION

Continuous use of the fCGM is recommended for people living with T2DM, regardless of their type of treatment. These metrics must be evaluated individually for each patient profile.

Enhancing equity in access to automated insulin delivery systems in an ethnically and socioeconomically diverse group of children with type 1 diabetes

INTRODUCTION

Manufacturer-supported didactic teaching programmes offer effective automated insulin delivery (AID) systems onboarding in children and young people (CYP) with type 1 diabetes (T1D). However, this approach has limited flexibility to accommodate the needs of families requiring additional support.

RESEARCH DESIGN AND METHODS

Evaluate the efficacy of an inperson manufacturer-supported didactic teaching programme (Group A), in comparison to a flexible flipped learning approach delivered virtually or inperson (Group B). Retrospective analysis of CYP with T1D using continuous glucose monitoring (CGM), who were initiated on AID systems between 2021 and 2023. Compare CGM metrics from baseline to 90 days for both groups A and B. Additionally, compare the two groups for change in CGM metrics over the 90-day period (∆), patient demographics and onboarding time.

RESULTS

Group A consisted of 74 CYP (53% male) with median age of 13.9 years and Group B 91 CYP (54% male) with median age of 12.7 years. From baseline to 90 days, Group A lowered mean (±SD) time above range (TAR, >10.0 mmol/L) from 47.6% (±15.0) to 33.2% (±15.0) (p<0.001), increased time in range (TIR, 3.9-10.0 mmol/L) from 50.4% (±14.0) to 64.7% (±10.2) (p<0.001). From baseline to 90 days, Group B lowered TAR from 51.3% (±15.1) to 34.5% (±11.3) (p<0.001) and increased TIR from 46.5% (±14.5) to 63.7% (±11.0) (p<0.001). There was no difference from baseline to 90 days for time below range (TBR, <3.9 mmol/L) for Group A and Group B. ∆ TAR, TIR and TBR for both groups were comparable. Group B consisted of CYP with higher socioeconomic deprivation, greater ethnic diversity and lower carer education achievement (p<0.05). The majority of Group B (n=79, 87%) chose virtual flipped learning, halving diabetes educator time and increasing onboarding cadence by fivefold.

CONCLUSIONS

A flexible virtual flipped learning programme increases onboarding cadence and capacity to offer equitable AID system onboarding.

Sex-driven factors associated with anxiety and depression in autoimmune diabetes

AIM

To analyze the prevalence of anxiety and depression in a large cohort of adults with autoimmune diabetes, identifying sex-driven associated factors.

MATERIALS AND METHODS

In this cross-sectional study, we enrolled 553 consecutive adults with Type 1 diabetes mellitus or latent autoimmune diabetes in adults who came to the Division of Endocrinology of the S.Orsola-Malpighi Polyclinic, Bologna (Italy), to receive their second dose of SARS-CoV-2 vaccine. We administered the questionnaires: Hospital Anxiety and Depression Scale, Diabetes Distress Scale, Diabetes-related Quality of Life, Diabetes Treatment Satisfaction Questionnaire. We collected clinical and biochemical data and 14 days glucose metrics in patients with sensor use > 70% in a time span of ± 4 months from the questionnaires' administration. We excluded 119 patients from our analyses with missing data (final cohort n = 434: 79% of those enrolled).

RESULTS

Anxiety and depression prevalence was respectively 30.4% and 10.8%. According to the multivariate analysis, higher diabete-related emotional burden, lower treatment satisfaction, but not physician-related distress, were risk factors for anxiety and depression; female sex was associated with anxiety (OR 0.51, 95% 0.31-0.81; p = 0.005); in women, depression was associated with increasing age (males vs. females OR 0.96 per 1 year increase, 95% CI 0.92-1.00; p = 0.036), whilst in men with HbA1c (OR 1.08 per 1 mmol/mol increase, 95% CI 1.03-1.13; p = 0.002).

CONCLUSION

Nearly 1/3 of patients with autoimmune diabetes suffers from anxiety and 1/10 from depression. These conditions are associated with independent modifiable and non-modifiable characteristics. For depression, these characteristics differ between males and females.

A retrospective study comparing the results of continuous glucose monitoring to self-blood glucose monitoring for pregnant women with type 1 diabetes mellitus

BACKGROUND

Type 1 diabetes mellitus (T1DM) is associated with adverse maternal and fetal outcomes. Continuous glucose monitoring (CGM) during pregnancy is associated with better glycemic control in women with T1DM. However, no clear benefits have been demonstrated in reducing adverse feto-maternal outcomes in pregnant women with T1DM.

DESIGN AND METHODS

This is a retrospective, single-center study of pregnant women with T1DM to evaluate the impact of CGM use on glycemic control and feto-maternal outcomes in pregnant women with T1DM.

RESULTS

Of 265 women with T1DM, 92 (34.7%) used CGM, and 173 (65.3%) were managed with capillary blood glucose (CBG) monitoring. The mean (SD) age and BMI at the first visit were 29.4 (4.7) years and 27.2 (5.2) kg/m2, respectively. The mean (SD) HbA1c at the first-trimester visit was 63 (1) mmol/mol, and in the last trimester was 51 (1%). There was no difference in the mean changes in HbA1c between the two groups. Women using CGM had lower insulin requirements (1.02 + 0.37 vs. 0.87 + 0.04 units/kg, p = 0.01). The two groups had no significant differences in maternal or fetal outcomes.

CONCLUSION

CGM use in pregnant T1DM women is not associated with improved fetomaternal outcomes.

Fabrication of Multiple-Channel Electrochemical Microneedle Electrode Array via Separated Functionalization and Assembly Method

Real-time monitoring of physiological indicators inside the body is pivotal for contemporary diagnostics and treatments. Implantable electrodes can not only track specific biomarkers but also facilitate therapeutic interventions. By modifying biometric components, implantable electrodes enable in situ metabolite detection in living tissues, notably beneficial in invasive glucose monitoring, which effectively alleviates the self-blood-glucose-managing burden for patients. However, the development of implantable electrochemical electrodes, especially multi-channel sensing devices, still faces challenges: (1) The complexity of direct preparation hinders functionalized or multi-parameter sensing on a small scale. (2) The fine structure of individual electrodes results in low spatial resolution for sensor functionalization. (3) There is limited conductivity due to simple device structures and weakly conductive electrode materials (such as silicon or polymers). To address these challenges, we developed multiple-channel electrochemical microneedle electrode arrays (MCEMEAs) via a separated functionalization and assembly process. Two-dimensional microneedle (2dMN)-based and one-dimensional microneedle (1dMN)-based electrodes were prepared by laser patterning, which were then modified as sensing electrodes by electrochemical deposition and glucose oxidase decoration to achieve separated functionalization and reduce mutual interference. The electrodes were then assembled into 2dMN- and 1dMN-based multi-channel electrochemical arrays (MCEAs), respectively, to avoid damaging functionalized coatings. In vitro and in vivo results demonstrated that the as-prepared MCEAs exhibit excellent transdermal capability, detection sensitivity, selectivity, and reproducibility, which was capable of real-time, in situ glucose concentration monitoring.

A case of diffuse congenital hyperinsulinism in which continuous glucose monitoring contributed to the choice of a treatment strategy following a subtotal pancreatectomy

Patients with diffuse congenital hyperinsulinism (CHI) refractory to drug therapy require subtotal or near-total pancreatectomy. Although almost all patients develop diabetes postoperatively, the clinical course and timing of insulin therapy remain unclear. A 7-yr-old girl presented with recurrent hypoglycemia shortly after birth and a relatively elevated insulin level, which confirmed the diagnosis of CHI. Genetic analysis revealed compound heterozygous ATP-binding cassette, Subfamily C, Member 8 pathogenic variants and diffuse CHI was suspected. Because her condition was refractory to diazoxide and octreotide, she underwent a subtotal pancreatectomy at the age of 4 mo. The drug therapy was discontinued. Although an oral glucose tolerance test at the age of 2 yr showed hyperglycemia after loading, continuous glucose monitoring (CGM) revealed that her daily glucose trends were almost within the 70-180 mg/dL range, and mild hypoglycemia appeared during the daytime. After the age of 6 yr, CGM showed an elevation in glucose trends from midnight to early morning, suggesting that insulin secretion was attenuated and hepatic glucose production was insufficiently suppressed. Insulin therapy was initiated at the age of 7 yr. These results indicate that CGM can be useful for making treatment decisions.

An Aerobic Cooldown After Morning, Fasted Resistance Exercise Has Limited Impact on Post-exercise Hyperglycemia in Adults With Type 1 Diabetes: A Randomized Crossover Study

OBJECTIVES

Expert guidelines recommend an aerobic cooldown to lower blood glucose for the management of post-exercise hyperglycemia. This strategy has never been empirically tested. Our aim in this study was to compare the glycemic effects of performing an aerobic cooldown vs not performing a cooldown after a fasted resistance exercise session. We hypothesized that the cooldown would lower blood glucose in the 30 minutes after exercise and would result in less time in hyperglycemia in the 6 hours after exercise.

METHODS

Participants completed 2 identical resistance exercise sessions. One was followed by a low-intensity (30% of peak oxygen consumption) 10-minute cycle ergometer cooldown, and the other was followed by 10 minutes of sitting. We compared the changes in capillary glucose concentration during these sessions and continuous glucose monitoring (CGM) outcomes over 24 hours post-exercise.

RESULTS

Sixteen participants completed the trial. Capillary glucose was similar between conditions at the start of exercise (p=0.07). Capillary glucose concentration decreased by 0.6±1.0 mmol/L during the 10-minute cooldown, but it increased by 0.7±1.3 mmol/L during the same time in the no-cooldown condition. The resulting difference in glucose trajectory led to a significant interaction (p=0.02), with no effect from treatment (p=0.7). Capillary glucose values at the end of recovery were similar between conditions (p>0.05). There were no significant differences in CGM outcomes.

CONCLUSIONS

An aerobic cooldown reduces glucose concentration in the post-exercise period, but the small and brief nature of this reduction makes this strategy unlikely to be an effective treatment for hyperglycemia occurring after fasted exercise.

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.

Time in Tight Glucose Range in Type 1 Diabetes: Predictive Factors and Achievable Targets in Real-World Users of the MiniMed 780G System

OBJECTIVE

We studied time in tight range (TITR) (70-140 mg/dL) in real-world users of the MiniMed 780G system (MM780G).

RESEARCH DESIGN AND METHODS

CareLink Personal data were extracted (August 2020 to December 2022) to examine TITR and its relationship with time in range (TIR; 70-180 mg/dL), factors predicting higher TITR, and which TITR target is a reasonable treatment goal.

RESULTS

The 13,461 users (3,762 age ≤15 years and 9,699 age >15 years) showed an average TITR of 48.9% in those age ≤15 years and 48.8% in the older group (vs. TIR 71.2% and 73.9%, respectively). Consistent use of a glucose target (GT) of 100 mg/dL and active insulin time (AIT) of 2 h were the most relevant factors predicting higher TITR (P < 0.0001). In users consistently applying these optimal settings, TITR was 56.7% in those age ≤15 years and 57.0% in the older group, and the relative impact of these settings on TITR was 60% and 86% greater than that on TIR, respectively. TITRs of ∼45% (age ≤15 years 46.3% and older group 45.4%), ∼50% (50.7% and 50.7%) and ∼55% (56.4% and 58.0%) were best associated with glucose management indicators <7.0%, <6.8%, and <6.5%, respectively. TITRs of >45%, >50%, and >55% were achieved in 91%, 74%, and 55% of those age ≤15 years and 93%, 81%, and 57% of older group users, respectively, at optimal settings.

CONCLUSIONS

This study demonstrates that 1) mean TIR is high with a high mean TITR in MM780G users (>48%), 2) consistent use of optimal GT/AIT improves TITR (>56%), 3) the impact of these settings on TITR is larger than on TIR, and 4) a TITR target >50% is our suggested treatment goal.