Consensus Recommendations for the Use of Automated Insulin Delivery Technologies in Clinical Practice

Efficacy of automated insulin delivery in pregnant women with type 1 diabetes: a meta-analysis and trial sequential analysis of randomized controlled trials

BACKGROUND

Automated insulin delivery (AID) devices have shown to be a promising treatment to improve glycemic control in patients with type 1 diabetes mellitus (T1DM). However, its efficacy in pregnant women with T1DM remains uncertain.

METHODS

PubMed, Scopus, Cochrane Central and ClinicalTrials.gov were systematically searched for randomized controlled trials (RCTs) comparing AID to standard care (SC), defined as use of sensor-augmented pump and multiple daily insulin injections. Outcomes included time in range (TIR), nocturnal TIR, time in hypoglycemic and hyperglycemic ranges, among others. Sensitivity and trial sequential analyses (TSA) were performed.

PROSPERO ID

CRD42023474398.

RESULTS

We included five RCTs with a total of 236 pregnant women, of whom 117 (50.6%) received AID. There was a significant increase in nocturnal TIR (mean difference [MD] 12.69%; 95% CI 8.74-16.64; p < 0.01; I2 = 0%) and a decrease in glucose variability (standard deviation of glucose; MD -2.91; 95% CI -5.13 to -0.69; p = 0.01; I2 = 0%). No significant differences were observed for TIR, HBGI, LGBI, mean glucose and time spent in hyperglycemia and hypoglycemia. Regarding TSA, the statistical significance obtained in nocturnal TIR was conclusive and with minimal risk of a type I error.

CONCLUSION

Our findings suggest that AID systems can significantly improve nocturnal glycemic control and potentially reduce glycemic variability in pregnant women with T1DM, with no effect in the risk of hypoglycemia and hyperglycemia compared with current insulin treatments.

Expert Panel Recommendations for a Standardized Ambulatory Glucose Profile Report for Connected Insulin Pens

Background: Connected insulin pens capture data on insulin dosing/timing and can integrate with continuous glucose monitoring (CGM) devices with essential insulin and glucose metrics combined into a single platform. Standardization of connected insulin pen reports is desirable to enhance clinical utility with a single report. Methods: An international expert panel was convened to develop a standardized connected insulin pen report incorporating insulin and glucose metrics into a single report containing clinically useful information. An extensive literature review and identification of examples of current connected insulin pen reports were performed serving as the basis for creation of a draft of a standardized connected insulin pen report. The expert panel participated in three virtual standardization meetings and online surveys. Results: The Ambulatory Glucose Profile (AGP) Report: Connected Insulin Pen brings all clinically relevant CGM-derived glucose and connected insulin pen metrics into a single simplified two-page report. The first page contains the time in ranges bar, summary of key insulin and glucose metrics, the AGP curve, and detailed basal (long-acting) insulin assessment. The second page contains the bolus (mealtime and correction) insulin assessment periods with information on meal timing, insulin-to-carbohydrate ratio, average bolus insulin dose, and number of days with bolus doses recorded. The report's second page contains daily glucose profiles with an overlay of the timing and amount of basal and bolus insulin administered. Conclusion: The AGP Report: Connected Insulin Pen is a standardized clinically useful report that should be considered by companies developing connected pen technology as part of their system reporting/output.

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.

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.

Impact of Missed and Late Meal Boluses on Glycemic Outcomes in Automated Insulin Delivery-Treated Children and Adolescents with Type 1 Diabetes: A Two-Center, Population-Based, Cohort Study

OBJECTIVE

To evaluate the impact of missed or late meal boluses (MLBs) on glycemic outcomes in children and adolescents with type 1 diabetes using automated insulin delivery (AID) systems.

RESEARCH DESIGN AND METHODS

AID-treated (Tandem Control-IQ or Medtronic MiniMed 780G) children and adolescents (aged 6-21 years) from Stanford Medical Center and Steno Diabetes Center Copenhagen with ≥10 days of data were included in this two-center, binational, population-based, retrospective, 1-month cohort study. The primary outcome was the association between number of algorithm-detected MLBs and time in target glucose range (TIR; 70-180 mg/dL).

RESULTS

The study included 189 children and adolescents (48% females with a mean ± SD age of 13 ± 4 years). Overall, the mean number of MLBs per day in the cohort was 2.2 ± 0.9. For each additional MLB per day, TIR decreased by 9.7%-points (95% CI 11.3; 8.1), and compared to the quartile with fewest MLBs (Q1), the quartile with most (Q4) had 22.9% less TIR (95% CI 27.2; 18.6). The age-, sex-, and treatment modality-adjusted probability of achieving a TIR of >70% in Q4 was 1.4% compared to 74.8% in Q1 (p<0.001).

CONCLUSIONS

MLBs significantly impacted glycemic outcomes in AID-treated children and adolescents. The results emphasize the importance of maintaining a focus on bolus behavior to achieve higher TIR, and supports the need for further research in technological or behavioral support tools to handle missed and late meal boluses.

Addressing the Burden of Multiple Daily Insulin Injections in Type 2 Diabetes with Insulin Pump Technology: A Narrative Review

The growing prevalence of type 2 diabetes (T2D) remains a leading health concern in the US. Despite new medications and technologies, glycemic control in this population remains suboptimal, which increases the risk of poor outcomes, increased healthcare resource utilization, and associated costs. This article reviews the clinical and economic impacts of suboptimal glycemic control in patients on basal-bolus insulin or multiple daily injections (MDI) and discusses how new technologies, such as tubeless insulin delivery devices, referred to as "patch pumps", have the potential to improve outcomes in patients with T2D.

An "out of the box" approach for prevention of ketoacidosis in youth with poorly controlled type 1 diabetes: combined use of insulin pump and long-acting insulin

BACKGROUND

Poorly controlled adolescents living with type 1 diabetes (T1D) and pump failure of insulin delivery leading to diabetic ketoacidosis (DKA) are still challenging in the western world.

AIM

To investigate the effect of a combination modality of long-acting insulin for basal coverage and a pump for boluses, on the incidence of DKA and glycemic parameters in pediatric and young adults with poorly controlled T1D.

METHODS

This multicenter, observational retrospective study included 55 patients (age range 3-25 years, 52.7% males) who were treated with the combination modality for a median of 18 months [(IQR)12,47], as part of their clinical care. Data were retrieved at initiation of the combined modality, after 6 months, and at last visit.

RESULTS

Cohort's median age at combination modality initiation was 14.5 years [IQR12.4,17.3], and its median HbA1c level was 9.2% [IQR 8.2,10.2]. The main reasons for combination modality initiation were: (a) concern about sustained hyperglycemia on current management in 41.8%, (b) previous DKA episodes in 30.8%, and (c) refusal to wear a pump continuously in 14.6%. The percent of patients experiencing DKA who used the modality till end decreased from 25.4 to 8.8%. The frequency of DKA events per patient month decreased after 6 months from 0.073 (min 0, max 0.5) to 0.020 (min 0, max 0.5), p = 0.01, and at end to 0.016 (min 0, max 0.25), p = 0.007.

CONCLUSIONS

The combination modality of once-daily long-acting insulin and pump for boluses is safe, feasible, and effective in preventing DKA among poorly controlled young people living with T1D, unable or un-willing to use advanced closed pumps.

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.

The role of automated insulin delivery technology in diabetes

The role of automated insulin delivery systems in diabetes is expanding. Hybrid closed-loop systems are being used in routine clinical practice for treating people with type 1 diabetes. Encouragingly, real-world data reflects the performance and usability observed in clinical trials. We review the commercially available hybrid closed-loop systems, their distinctive features and the associated real-world data. We also consider emerging indications for closed-loop systems, including the treatment of type 2 diabetes where variability of day-to-day insulin requirements is high, and other challenging applications for this technology. We discuss issues around access and implementation of closed-loop technology, and consider the limitations of present closed-loop systems, as well as innovative approaches that are being evaluated to improve their performance.

Exploratory insights into prefrontal cortex activity in continuous glucose monitoring: findings from a portable wearable functional near-infrared spectroscopy system

The escalating global prevalence of diabetes highlights an urgent need for advancements in continuous glucose monitoring (CGM) technologies that are non-invasive, accurate, and user-friendly. Here, we introduce a groundbreaking portable wearable functional near-infrared spectroscopy (fNIRS) system designed to monitor glucose levels by assessing prefrontal cortex (PFC) activity. Our study delineates the development and application of this novel fNIRS system, emphasizing its potential to revolutionize diabetes management by providing a non-invasive, real-time monitoring solution. Fifteen healthy university students participated in a controlled study, where we monitored their PFC activity and blood glucose levels under fasting and glucose-loaded conditions. Our findings reveal a significant correlation between PFC activity, as measured by our fNIRS system, and blood glucose levels, suggesting the feasibility of fNIRS technology for CGM. The portable nature of our system overcomes the mobility limitations of traditional setups, enabling continuous, real-time monitoring in everyday settings. We identified 10 critical features related to blood glucose levels from extensive fNIRS data and successfully correlated PFC function with blood glucose levels by constructing predictive models. Results show a positive association between fNIRS data and blood glucose levels, with the PFC exhibiting a clear response to blood glucose. Furthermore, the improved regressive rule principal component analysis (PCA) method outperforms traditional PCA in model prediction. We propose a model validation approach based on leave-one-out cross-validation, demonstrating the unique advantages of K-nearest neighbor (KNN) models. Comparative analysis with existing CGM methods reveals that our paper's KNN model exhibits lower RMSE and MARD at 0.11 and 8.96%, respectively, and the fNIRS data were highly significant positive correlation with actual blood glucose levels (r = 0.995, p < 0.000). This study provides valuable insights into the relationship between metabolic states and brain activity, laying the foundation for innovative CGM solutions. Our portable wearable fNIRS system represents a significant advancement in effective diabetes management, offering a promising alternative to current technologies and paving the way for future advancements in health monitoring and personalized medicine.

A Biomineralized Bifunctional Patient-Friendly Nanosystem for Sustained Glucose Monitoring and Control in Diabetes

Regular blood glucose monitoring and control is necessary for people with type 1 or advanced type 2 diabetes, yet diagnosing and treating patients with diabetes in an accurate, sustained and patient-friendly manner remains limited. Here, a glucose-responsive bifunctional nanosystem (PGOxMns) is constructed via one-pot biomineralisation of manganese dioxide with glucose oxidase and ε-poly-L-lysine. Under hyperglycaemic conditions, the cascade reactions that occur when glucose interacts with PGOxMns can trigger the production of Mn(II), which enhances the magnetic resonance imaging signal. Simultaneously, manganese dioxide catalyses the decomposition of toxic hydrogen peroxide into oxygen, which also maintains glucose oxidase (GOx) activity. In an in vivo model of diabetes, PGOxMns is used to monitor glucose levels (0-20 mm) and allowed identification of diabetic mice via T1-weighted MRI. Furthermore, PGOxMns is found to have a high insulin-loading capacity (83.6%), likely due to its positive charge. A single subcutaneous injection of insulin-loaded nanosystem (Ins-PGOxMns) into diabetic mice resulted in a rapid and efficient response to a glucose challenge and prolonged blood glucose level control (< 200 mg dL-1) for up to 50 h. Overall, this proof-of-concept study demonstrates the feasibility of using biomineralised nanosystems to develop patient-friendly strategies for glucose monitoring and control.

Diabetes Technology in People with Type 2 Diabetes: Novel Indications

PURPOSE OF REVIEW

Diabetes technology has been continuously evolving. Current versions of continuous glucose monitors (CGM) use minimally invasive designs, monitor glucose values with high accuracy, and can be used to guide insulin dosing. Extensive evidence supports the use of diabetes technology for monitoring and insulin administration in people with type 1 diabetes. However, there is emerging evidence for people with type 2 diabetes. In this review, we present the different technological devices used to monitor glucose and deliver insulin and the evidence supporting their use in people with type 2 diabetes.

RECENT FINDINGS

The use of CGMs in people with type 2 diabetes treated with insulin or non-insulin therapies has been associated with improvements in glycemic control and time spent in hypoglycemia. Smart insulin pens and smart connected devices are options to track compliance and guide insulin delivery in people who do not require insulin pump therapy. Mechanical patch pumps can be used to reduce the burden of multiple daily insulin injections. Automated insulin delivery algorithms improve glycemic control without an increase in hypoglycemia. The use of technology in the management of type 2 diabetes generates glycemic data previously inaccessible, reduces barriers for insulin initiation, improves glycemic control, tracks adherence to therapy, and improves user satisfaction.

The psychosocial outcomes of advanced hybrid closed-loop system in children and adolescents with type 1 diabetes

The study was carried out to determine the psychosocial outcomes of advanced hybrid closed-loop (AHCL) systems in children and adolescents with type 1 diabetes (T1D). Single-center and cohort study with a duration 6 months consisted of 60 children and adolescents with T1D. Standard clinical procedures, including both glycemic indicators, e.g., sensor-measured time within the 70-180 mg/dL range and glycated hemoglobin (HbA1c) levels, and psychosocial metrics were used for data collection. The psychosocial metrics included the Pediatric Quality of Life Inventory (PedsQL) 3.0 Diabetes Module for both children (8-12 years) and parents; the Quality of Life for Youth scale for adolescents (13-18 years); the Strengths and Difficulties Questionnaire (SDQ); the Hypoglycemia Fear Survey for Children (HFS-C); the Revised Child Anxiety and Depression Scale (R-CADS); and AHCLS-specific DTSEQ satisfaction and expectation survey. These metrics were evaluated at the baseline and after 6 months of AHCL use. Of the 60 children and adolescents with T1D for whom the AHCL system was utilized, 41 of them, 23 female and 18 male, completed the surveys. The mean age of the 41 children and adolescents was 12.5 ± 3.2 (min. 6.7, max. 18) years. The time spent within the target glycemic range, i.e., time-in-range (TIR), improved from 76.9 ± 9% at the baseline to 80.4 ± 5% after 6 months of AHCL system use (p = 0.03). Additionally, HbA1c levels reduced from 7.1% ± 0.7% at the baseline to 6.8% ± 0.8% after 6 months of AHCL system use (p = 0.03). The most notable decline in HbA1c was observed in participants with higher baseline HbA1c levels. All patients' HFS-C and AHCL system-specific DTSEQ satisfaction and expectation survey scores were within the normal range at the baseline and remained unchanged during the follow-up period. No significant difference was found in the R-CADS scores of children and adolescents between baseline and after 6 months of AHCL system use. However, there was a significant decrease in the R-CADS scores of the parents. Patients' PedsQL scores were high both at the baseline and after 6 months. The SDQ scores were high at baseline, and there was no significant improvement at the end of 6 months.  Conclusion: This is the first study to investigate in detail the psychosocial outcomes of AHCL system use in T1D patients and their parents. Although state-of-the-art technologies such as AHCL provide patients with more flexibility in their daily lives and information about glucose fluctuations, the AHCL resulted in a TIR above the recommended target range without a change in QOL, HFS-C, SDQ, and R-CADS scores. The scores obtained from the R-CADS conducted by the parents of the children indicated that the use of pumps caused a psychological improvement in the long term, with a significant decrease in the R-CADS scores of the children and adolescents with T1D. What is Known: • Previous studies focused on clinical outcomes of AHCL systems in pediatric T1D patients, showing glycemic control improvements. • Limited attention given to psychosocial outcomes of AHCL systems in children and adolescents with T1D. • Crucial psychosocial factors like quality of life, emotional well-being, and fear of hypoglycemia underexplored in AHCL system context. What is New: • First study to comprehensively examine psychosocial outcomes of AHCL systems in pediatric T1D patients. • Study's robust methodology sets new standard for diabetes technology research and its impact on qualiy of life.

Efficacy of the hybrid closedloop insulin delivery system in children and adolescents with type 1 diabetes: a meta-analysis with trial sequential analysis

The aim of this study was to assess the efficacy and safety of hybrid closed-loop (HCL) systems for insulin delivery in children and adolescents with type 1 diabetes (T1D). We searched Embase, PubMed, and Cochrane Library for randomized controlled trials (RCTs) published until March 2023 comparing the HCL therapy with control therapies for children and adolescents with T1D. We computed weighted mean differences (WMDs) for continuous outcomes and risk ratios (RRs) with 95% confidence intervals (CIs) for binary endpoints. Four RCTs and 501 patients were included, of whom 323 were randomized to HCL therapy. Compared with control therapies, HCL significantly improved the period during which glucose level was 70-180 mg/dL (WMD 10.89%, 95% CI 8.22-13.56%) and the number of participants with glycated hemoglobin (HbA1c) level < 7% (RR 2.61, 95% CI 1.29-5.28). Also, HCL significantly reduced the time during which glucoselevel was > 180 mg/dL (WMD-10.46%, 95% CI-13.99 to-6.93%) and the mean levels of glucose (WMD-16.67 mg/dL, 95% CI-22.25 to-11.09 mg/dL) and HbA1c (WMD-0.50%, 95% CI-0.68 to-0.31). There were no significant differences between therapies regarding time during which glucose level was < 70 mg/dL or <54 mg/dL or number of episodes of ketoacidosis, hyperglycemia, and hypoglycemia. In this meta-analysis, HCL compared with control therapies was associated with improved time in range and HbA1c control in children and adolescents with T1D and a similar profile of side effects. These findings support the efficacy of HCL in the treatment of T1D in this population.

Type 1 diabetes-related distress: Current implications in care

Type 1 diabetes (T1D) is a complex chronic disease associated with major health and economic consequences, also involving important issues in the psychosocial sphere. In this regard, T1D-related distress, defined as the emotional burden of living with T1D, has emerged as a specific entity related to the disease. Diabetes distress (DD) is an overlooked but prevalent condition in people living with T1D, and has significant implications in both glycemic control and mental health in this population. Although overlapping symptoms may be found between DD and mental health disorders, specific approaches should be performed for the diagnosis of this problem. In recent years, different DD-targeted interventions have been postulated, including behavioral and psychosocial strategies. Moreover, new technologies in this field may be helpful to address DD in people living with T1D. In this article, we summarize the current knowledge on T1D-related distress, and we also discuss the current approaches and future perspectives in its management.

A Real-World Prospective Study of the Effectiveness and Safety of Automated Insulin Delivery Compared With Other Modalities of Type 1 Diabetes Treatment During Ramadan Intermittent Fasting

OBJECTIVE

To compare the fasting experience and glycemic control during Ramadan among people with type 1 diabetes (PWT1D) who use automated insulin delivery (AID) versus other modalities of treatment.

RESEARCH DESIGN AND METHODS

A total of 294 PWT1D who attempted fasting during Ramadan in 2022 were categorized on the basis of treatment modality into one of five groups: 1) AID (n = 62); 2) conventional pump + continuous glucose monitoring (CGM; n = 37); 3) pump + self-monitoring of blood glucose (SMBG; n = 8); 4) multiple daily injections (MDI) + CGM (n = 155); and 5) MDI + SMBG (n = 32). Predictors of fasting most days of Ramadan (i.e., breaking fast ≤2 days because of diabetes) were analyzed using uni- and multivariable logistic regression.

RESULTS

The median numbers of days when fasting was broken because of diabetes were 2, 5, 3, 3.5, and 2.5 for AID, conventional pump + CGM, MDI + CGM, pump + SMBG, and MDI + SMBG users, respectively (P = 0.047). Users of AID had a significantly greater time in range (TIR) and lower glycemia risk index, time below range, and time above range compared with users of conventional pumps and MDI (both P < 0.05). Likewise, 53% of AID users attained the double target of 1) breaking fast ≤2 days because of diabetes and 2) maintaining TIR ≥70% during Ramadan compared with only 3% of the conventional pump users and 44% of the MDI + CGM users (both P < 0.05). Compared with MDI + CGM users, AID users were twice as likely to complete fasting most days of Ramadan.

CONCLUSIONS

Use of AID is associated with the highest rates of fasting and best glycemic control during Ramadan fasting.

Carbohydrate counting knowledge and ambulatory glucose profile in persons living with type 1 diabetes

CONTEXT

The amount of consumed carbohydrates is the strongest factor influencing glucose levels during the four hours following a meal. Our aim was to evaluate the association between carbohydrate counting knowledge and continuous glucose monitoring (CGM) parameters in patients with type 1 diabetes (T1D) using different insulin regimens.

METHOD

In this multicenter prospective study, the GluciQuizz questionnaire was used to evaluate carbohydrate knowledge. CGM data for the 14 days preceding completion of the questionnaire were analyzed. The primary endpoint was evaluation of the correlation between the GluciQuizz total score and time in range (TIR) in the study population.

RESULTS

The mean age of the 170 participants was 40.7 ± 14.8 years and duration of T1D 18.8 ± 12.1 years. The mean GluciQuizz total score for all participants was 66 ± 13 %. Mean TIR was 58.6 ± 18.7 %. GluciQuizz total score positively correlated with TIR (r = 0.3001; p < 0.0001). This correlation was observed in CSII users (r = 0.2526; p < 0.05) but not in MDI (r = 0.2510; p = 0.1134) and HCL users (r = -0.1065; p = 0.4914). TIR was also negatively correlated with the mean carb count error in all study participants (r = -0.2317; p < 0.01).

CONCLUSION

In conclusion, as the Gluciquizz score was associated with metabolic control, this easy-to-use self-administered questionnaire could be used widely on a routine basis to assess the carbohydrate knowledge of T1D patients and to offer them targeted education tailored to their needs.

Time in Range Analysis in Automated Insulin Delivery Era: Should Day and Nighttime Targets be the Same?

INTRODUCTION

Hybrid closed-loop systems (HCLS) use has shown that time in range (TIR) tends to improve more during the nighttime than during the day. This study aims to compare the conventional TIR, currently accepted as 70 to 180 mg/dL, with a proposed recalculated time in range (RTIR) considering a tighter glucose target of 70 to 140 mg/dL for the nighttime fasting period in T1DM patients under HCLS.

METHODS

We conducted a retrospective study that included adults patients receiving treatment with Tandem t:slim X2 Control-IQ. Daytime TIR was characterized as glucose values between 70 and 180 mg/dL during the 07:01 to 23:59 time frame. Nighttime fasting TIR was specified as glucose values from 70 to 140 mg/dL between 00:00 and 07:00. The combination of the daytime and nighttime fasting glucose targets results in an RTIR, which was compared with the conventional TIR for each patient. The 14 days Dexcom G6 CGM data were downloaded from Tidepool platform and analyzed.

RESULTS

We included 22 patients with a mean age of 49.7 years and diabetes duration of 24.7 years, who had been using automatic insulin delivery (AID) HCLS for a median of 305.3 days. We verified a mean conventional TIR of 68.7% vs a mean RTIR of 60.3%, with a mean percentage difference between these two metrics of -8.4%. A significant decrease in conventional TIR was verified when tighter glucose targets were considered during the nighttime period. No significant correlation was found between the percentage difference values and RTIR, even among the group of patients with the lowest conventional TIR.

CONCLUSIONS

Currently, meeting the conventional TIR metrics may fall short of achieving an ideal level of glycemic control. An individualized strategy should be adopted until further data become available for a precise definition of optimal glucose targets.

Randomized Trial of Assisted Hybrid Closed-Loop Therapy Versus Sensor-Augmented Pump Therapy in Pregnancy

Objective: Examine gestational safety, glycemic and health outcomes, of a hybrid closed-loop (HCL) system without pregnancy-specific glucose targets. Research Design: This was a pilot feasibility investigator-initiated, two-site, single-blind, randomized controlled trial of sensor-augmented pump therapy (SAPT) versus HCL therapy in type 1 diabetes pregnancies. Participants were enrolled in the first trimester and randomized at 14-18 weeks of gestation and used SAPT or HCL until 4-6 weeks postpartum. We compared continuous glucose monitoring (CGM) metrics, severe hypoglycemia (SH), diabetic ketoacidosis (DKA), adverse skin reactions, and pregnancy outcomes between groups. Results: Baseline characteristics were similar between groups (n = 11 HCL and n = 12 SAPT). There was no SH or DKA episode after randomization. Time spent <54 mg/dL did not differ between groups. Time spent <63 mg/dL decreased in both groups, significantly in the HCL group (3.5% [1.3% standard error] second trimester and 2.8% [1.3%] third trimester vs. 7.9% [1.3%] run-in phase, P < 0.05 for both). Mean sensor glucose was lower with SAPT compared to HCL therapy in the third trimester (119 [4] mg/dL SAPT vs. 132 [4] mg/dL HCL, P < 0.05). Third trimester time-in-range (TIR; 63-140 mg/dL) increased with SAPT (68.2% [3.1%] vs. 64.3% [3.1%] run-in phase, P < 0.05). Gestational health outcomes did not differ between groups. The HCL group used assistive techniques, such as fake carbohydrate boluses and exiting HCL overnight. Conclusions: CGM within group differences were seen for time <63 mg/dL favoring HCL therapy and TIR favoring SAPT (third trimester vs. baseline). Safety and adverse pregnancy outcomes were similar between groups.

Does minimed 780GTM insulin pump system affect energy and nutrient intake?: long-term follow-up study

OBJECTIVE

We evaluate the energy and nutrient intake of children, adolescents, and young adults with type 1 diabetes (T1D) who started to use automated insulin delivery (AID) systems before the transition and during follow-up for 6 months in a real-world setting.

RESEARCH DESIGN AND METHODS

Twenty-nine people with T1D (PwD) who started to use MiniMed 780GTM participated in the study. Participants' 3-day food diaries and glycemic outcomes were analyzed at baseline and after (the 3rd and 6th month) switching to an advanced hybrid closed-loop system (a-HCL).

RESULTS

Mean carbohydrate, protein, and fat intake (energy %) at baseline were 49.1 ± 4.5, 17.8 ± 2.3, and 33.0 ± 3.9, respectively, and there were no statistically significant differences during the follow-up period. However, low fiber (<14 g/1000 kcal) and high saturated fat (>10 energy %) intake in PwD, both baseline and follow-up period. The median auto-correction bolus ratio was 14.0 (9.5)% at auto mode after 14 days, 18.0 (11.0)% at the 3rd month, and 19.0 (7.5)% at the 6th month (p < 0.05). A negative correlation was present between auto-correction boluses with TIR in both the 3rd (r:-0.747, p < 0.01) and 6th month (r:-0.395, p < 0.05). A negative correlation was present between auto-correction boluses with TIR in both the 3rd (r:-0.747, p < 0.01) and 6th month (r:-0.395, p < 0.05).

CONCLUSIONS

a-HCLS systems offer better glycemic control. Using the Minimed 780 GTM insulin pump system didn't change the energy and nutrient intake of PwD. This real-world follow-up study suggests that children, adolescents, and young adults with T1D consume saturated fat above and fiber intake lower than recommendations independent of the use of a-HCLS.

CLINICAL TRIALS REGISTRATION NUMBER

NCT05666596.

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

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

Reducing Diabetes Burden in Medtronic's Automated Insulin Delivery Systems

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

Early Real-World Performance of the MiniMed™ 780G Advanced Hybrid Closed-Loop System and Recommended Settings Use in the United States

Background: The MiniMed™ 780G system (MM780G) with Guardian™ 4 sensor includes a 100 mg/dL glucose target (GT) and automated insulin corrections up to every 5 min and was recently approved for use in the United States. In the present study, early real-world MM780G performance and the use of recommended system settings (100 mg/dL GT with an active insulin time of 2 h), by individuals with type 1 diabetes, were evaluated. Methods: CareLink™ personal data uploaded between the launch of the MM780G to August 22, 2023 were aggregated and underwent retrospective analysis (based on user consent) and if users had ≥10 days of continuous glucose monitoring (CGM) data. The 24-h day CGM metrics, including mean glucose, percentage of time spent in (%TIR), above (%TAR), and below (%TBR) target range (70-180 mg/dL), in addition to delivered insulin and closed-loop (CL) exits, were compared between an overall group (n = 7499) and individuals who used recommended settings (each, for >95% of the time). An analysis of the same metrics for MiniMed™ 770G system (MM770G) users (n = 3851) who upgraded to the MM780G was also conducted (paired t-test or Wilcoxon signed-rank test, P < 0.05 considered statistically significant). Results: For MM780G users, CGM use, and time in CL were >90% and all MM780G CGM metrics exceeded consensus-recommended goals. With recommended settings (22% of all users), mean %TIR and %TITR (70-140 mg/dL) were 81.4% and 56.4%, respectively. For individuals who upgraded from the MM770G, %TIR and %TITR increased from 73.2% to 78.3% and 45.8% to 52.6%, respectively, while %TAR reduced from 25.1% to 20.2% (P < 0.001, for all three). CL exits/week averaged <1, for all MM780G users. Conclusions: Early real-world MM780G use in the United States demonstrated a high percentage of time in range with low time above and below range. These outcomes are similar to those observed for real-world MM780G use in other countries.

Real-World Evidence of Automated Insulin Delivery System Use

Objective: Pivotal trials of automated insulin delivery (AID) closed-loop systems have demonstrated a consistent picture of glycemic benefit, supporting approval of multiple systems by the Food and Drug Administration or Conformité Européenne mark receipt. To assess how pivotal trial findings translate to commercial AID use, a systematic review of retrospective real-world studies was conducted. Methods: PubMed and EMBASE were searched for articles published after 2018 with more than five nonpregnant individuals with type 1 diabetes (T1D). Data were screened/extracted in duplicate for sample size, AID system, glycemic outcomes, and time in automation. Results: Of 80 studies identified, 20 met inclusion criteria representing 171,209 individuals. Time in target range 70-180 mg/dL (3.9-10.0 mmol/L) was the primary outcome in 65% of studies, with the majority of reports (71%) demonstrating a >10% change with AID use. Change in hemoglobin A1c (HbA1c) was reported in nine studies (range 0.1%-0.9%), whereas four reported changes in glucose management indicator (GMI) with a 0.1%-0.4% reduction noted. A decrease in HbA1c or GMI of >0.2% was achieved in two-thirds of the studies describing change in HbA1c and 80% of articles where GMI was described. Time below range <70 mg/dL (<3.9 mmol/L) was reported in 16 studies, with all but 1 study showing stable or reduced levels. Most systems had >90% time in automation. Conclusion: With larger and more diverse populations, and follow-up periods of longer duration (∼9 months vs. 3-6 months for pivotal trials), real-world retrospective analyses confirm pivotal trial findings. Given the glycemic benefits demonstrated, AID is rapidly becoming the standard of care for all people living with T1D. Individuals should be informed of these systems and differences between them, have access to and coverage for these technologies, and receive support as they integrate this mode of insulin delivery into their lives.

A Diabetes Pregnancy Technology Roadmap: The 2023 Norbert Freinkel Award Lecture

Norbert Freinkel emphasized the need for "more aggressive therapy with exogenous insulin" during type 1 diabetes (T1D) pregnancy. Recent advances in diabetes technology, continuous glucose monitoring (CGM), and hybrid closed-loop (HCL) insulin delivery systems allow us to revisit Freinkel's observations from a contemporary perspective. The Continuous Glucose Monitoring in Women With Type 1 Diabetes in Pregnancy Trial (CONCEPTT) led to international recommendations that CGM be offered to all pregnant women with T1D to help them meet their pregnancy glucose targets and improve neonatal outcomes. However, despite CGM use, only 35% of trial participants reached the pregnancy glucose targets by 35 weeks' gestation, which is too late for optimal obstetric and neonatal outcomes. The constant vigilance to CGM data and insulin dose adjustment, with perpetual worry about the impact of hyperglycemia on the developing fetal structures, leave many pregnant women feeling overwhelmed. HCL systems that can adapt to marked gestational changes in insulin sensitivity and pharmacokinetics may help to bridge the gap between the nonpregnant time in range glycemic targets (70-180 mg/dL) and the substantially more stringent pregnancy-specific targets (TIRp) (63-140 mg/dL) required for optimal obstetric and neonatal outcomes. Use of HCL (CamAPS FX system) was associated with a 10.5% higher TIRp, 10.2% less hyperglycemia, and 12.3% higher overnight TIRp. Clinical benefits were accompanied by 3.7 kg (8 lb) less gestational weight gain and consistently achieved across a representative patient population of insulin pump or injection users, across trial sites, and across maternal HbA1c categories. Working collaboratively, women, HCL technology, and health care teams achieved improved glycemia with less worry, less work, and more positive pregnancy experiences.

Decreasing the Burden of Carbohydrate Counting and Meal Announcement with Automated Insulin Delivery, Meal Recognition, and Autocorrection Doses: A Case Study

The use of automated insulin delivery (AID) has led to a decrease in the burden of diabetes, allowing for better sleep, decreased anxiety about hypoglycemia, and automatic corrections doses, and meal recognition algorithms have provided "forgiveness" for imprecise carbohydrate (CHO) entries and missed or late meal boluses. We provide a case report and review of the current literature assessing the effect of AID on the burden of meal bolus. The case also demonstrates how sensor and pump data provide insight into insulin bolus behavior, and access to integrated cloud-based data has allowed for virtual patient visits. Glucose sensor metrics provides time in range and time below range, and the sensor-derived glucose management indicator provides an assessment of the long-term risk of complications when a laboratory glycated hemoglobin is not available.

Postprandial Glucose Excursions with Ultra-Rapid Insulin Analogs in Hybrid Closed-Loop Therapy for Adults with Type 1 Diabetes

Objective: To evaluate postprandial glucose control when applying (1) faster-acting insulin aspart (Fiasp) compared to insulin aspart and (2) ultra-rapid insulin lispro (Lyumjev) compared to insulin lispro using the CamAPS FX hybrid closed-loop algorithm. Research Design and Methods: We undertook a secondary analysis of postprandial glucose excursions from two double-blind, randomized, crossover hybrid closed-loop studies contrasting Fiasp to standard insulin aspart, and Lyumjev to standard insulin lispro. Endpoints included incremental area under curve (iAUC)-2h, iAUC-4h, 4 h postprandial time in target range, time above range, and time below range. It was approved by independent research ethics committees. Results: Two trials with 8 weeks of data from 51 adults with type 1 diabetes were analyzed and 7137 eligible meals were included. During Lyumjev compared with insulin lispro, iAUC-2h and iAUC-4h were significantly decreased following breakfast (mean difference 92 mmol/L per 2 h (95% confidence interval [CI]: 56 to 127); P < 0.001 and 151 mmol/L per 4 h (95% CI: 74 to 229); P < 0.001, respectively) and the evening meal (P < 0.001 and P = 0.011, respectively). Mean time in target range (3.9-10.0 mmol/L) for 4 h postprandially significantly increased during Lyumjev with a mean difference of 6.7 percentage points (95% CI: 3.3 to 10) and 5.7 percentage points (95% CI: 1.4 to 9.9) for breakfast and evening meal, respectively. In contrast, there were no significant differences in iAUC-2h, iAUC-4h, and the other measures of postprandial glucose control between insulin aspart and Fiasp during breakfast, lunch, and evening meal (P > 0.05). Conclusion: The use of Lyumjev with CamAPS FX closed-loop system improved postprandial glucose excursions compared with insulin lispro, while the use of Fiasp did not provide any advantage compared with insulin aspart. Clinical Trial Registration numbers: NCT04055480, NCT05257460.

Retrospective Comparison of Commercially Available Automated Insulin Delivery With Open-Source Automated Insulin Delivery Systems in Type 1 Diabetes

BACKGROUND

Automated insulin delivery (AID) systems have shown to improve glycemic control in a range of populations and settings. At the start of this study, only one commercial AID system had entered the Austrian market (MiniMed 670G, Medtronic). However, there is an ever-growing community of people living with type 1 diabetes (PWT1D) using open-source (OS) AID systems.

MATERIALS AND METHODS

A total of 144 PWT1D who used either the MiniMed 670G (670G) or OS-AID systems routinely for a period of at least three to a maximum of six months, between February 18, 2020 and January 15, 2023, were retrospectively analyzed (116 670G aged from 2.6 to 71.8 years and 28 OS-AID aged from 3.4 to 53.5 years). The goal is to evaluate and compare the quality of glycemic control of commercially available AID and OS-AID systems and to present all data by an in-depth descriptive analysis of the population. No statistical tests were performed.

RESULTS

The PWT1D using OS-AID systems spent more time in range (TIR)70-180 mg/dL (81.7% vs 73.9%), less time above range (TAR)181-250 mg/dL (11.1% vs 19.6%), less TAR>250 mg/dL (2.5% vs 4.3%), and more time below range (TBR)54-69 mg/dL (2.2% vs 1.7%) than PWT1D using the 670G system. The TBR<54 mg/dL was comparable in both groups (0.3% vs 0.4%). In the OS-AID group, median glucose level and glycated hemoglobin (HbA1c) were lower than in the 670G system group (130 vs 150 mg/dL; 6.2% vs 7.0%).

CONCLUSION

In conclusion, both groups were able to achieve satisfactory glycemic outcomes independent of age, gender, and diabetes duration. However, the PWT1D using OS-AID systems attained an even better glycemic control with no clinical safety concerns.

The double burden: type 1 diabetes and heart failure-a comprehensive review

Heart failure (HF) is increasing at an alarming rate, primary due to the rising in aging, obesity and diabetes. Notably, individuals with type 1 diabetes (T1D) face a significantly elevated risk of HF, leading to more hospitalizations and increased case fatality rates. Several risk factors contribute to HF in T1D, including poor glycemic control, female gender, smoking, hypertension, elevated BMI, and albuminuria. However, early and intensive glycemic control can mitigate the long-term risk of HF in individuals with T1D. The pathophysiology of diabetes-associated HF is complex and multifactorial, and the underlying mechanisms in T1D remain incompletely elucidated. In terms of treatment, much of the evidence comes from type 2 diabetes (T2D) populations, so applying it to T1D requires caution. Sodium-glucose cotransporter 2 inhibitors have shown benefits in HF outcomes, even in non-diabetic populations. However, most of the information about HF and the evidence from cardiovascular safety trials related to glucose lowering medications refer to T2D. Glycemic control is key, but the link between hypoglycemia and HF hospitalization risk requires further study. Glycemic variability, common in T1D, is an independent HF risk factor. Technological advances offer the potential to improve glycemic control, including glycemic variability, and may play a role in preventing HF. In summary, HF in T1D is a complex challenge with unique dimensions. This review focuses on HF in individuals with T1D, exploring its epidemiology, risk factors, pathophysiology, diagnosis and treatment, which is crucial for developing tailored prevention and management strategies for this population.

Safety and Feasibility Evaluation of Automated User Profile Settings Initialization and Adaptation With Control-IQ Technology

BACKGROUND

Optimization of automated insulin delivery (AID) settings is required to achieve desirable glycemic outcomes. We evaluated safety and efficacy of a computerized system to initialize and adjust insulin delivery settings for the t:slim X2 insulin pump with Control-IQ technology in adults with type 1 diabetes (T1D).

METHODS

After a 2-week continuous glucose monitoring (CGM) run-in period, adults with T1D using multiple daily injections (MDI) (N = 33, mean age 36.1 years, 57.6% female, diabetes duration 19.7 years) were transitioned to 13 weeks of Control-IQ technology usage. A computerized algorithm generated recommendations for initial pump settings (basal rate, insulin-to-carbohydrate ratio, and correction factor) and weekly follow-up settings to optimize glycemic outcomes. Physicians could override the automated settings changes for safety concerns.

RESULTS

Time in range 70 to 180 mg/dL improved from 45.7% during run-in to 69.1% during the last 30 days of Control-IQ use, a median improvement of 18.8% (95% confidence interval [CI]: 13.6-23.9, P < .001). This improvement was evident early in the study and was sustained over 13 weeks. Time <70 mg/dL showed a gradual decreasing trend over time. Percentage of participants achieving HbA1c <7% went from zero at baseline to 55% at study end (P < .001). Only six of the 318 automated settings adaptations (1.9%) were overridden by study investigators.

CONCLUSIONS

Computerized initiation and adaptation of Control-IQ technology settings from baseline MDI therapy was safe in adults with T1D. The use of this simplified system for onboarding and optimizing Control-IQ technology may be useful to increase uptake of AID and reduce staff and patient burden in clinical care.

Should people with type 2 diabetes treated by multiple daily insulin injections with home health care support be switched to hybrid closed-loop? The CLOSE AP+ randomized controlled trial

AIM

The study aim was to evaluate the feasibility, safety and efficacy of automated insulin delivery (AID) assisted by home health care (HHC) services in people with type 2 diabetes unable to manage multiple daily insulin injections (MDI) at home on their own.

PATIENTS AND METHODS

This was an open label, multicentre, randomized, parallel group trial. In total, 30 adults with type 2 diabetes using MDI and requiring nursing support were randomly allocated to AID or kept their usual therapy over a 12-week period. Both treatments were managed with the support of HHC services. The primary outcome was the percentage time in the target glucose range of 70-180 mg/dl (TIR). Secondary outcomes included other continuous glucose monitoring metrics, glycated haemoglobin (HbA1c) levels, daily insulin doses, body weight, and of quality of life scores, fear of hypoglycaemia and satisfaction questionnaires.

RESULTS

Age (69.7 vs. 69.3 years) and HbA1c (9.25 vs. 9.0) did not differ in MDI and AID at baseline. Compared with MDI, AID resulted in a significant increase in TIR by 27.4% [95% CI (15.0-39.8); p < .001], a decrease in time above range by 27.7% and an unchanged time below range of <1%. A between-group difference in HbA1c was 1.3% favouring AID. Neither severe hypoglycaemia nor ketoacidosis occurred in either group. Patient and caregiver satisfaction with AID was high.

CONCLUSIONS

AID combined with tailored HHC services significantly improved glycaemic control with no safety issues in people with type 2 diabetes previously under an MDI regimen with HHC. AID should be considered a safe option in these people when lacking acceptable glucose control.

Does Insulin Delivery Technology Change Our Relationship with Foods? A Scoping Review

Introduction: Automated insulin delivery (AID) systems reduce burden and improve glycemic management for people with type 1 diabetes (PwT1D) by automatically adjusting insulin as a response to measured glucose levels. There is a lack of evidence on AID and nutrition variables such as dietary intake, eating behaviors, and disordered eating. Objectives: This scoping review aims to provide a summary of the literature regarding AID and nutrition variables and to identify gaps that require further investigation. Methods: Two researchers conducted a blinded search of Medline (OVID) and PubMed for studies, including AID use (compared to non-AID use) and nutrition variables. Studies from January 2000 to July 2023 were included, as were PwT1D of all ages. Results: A total of 3132 articles were screened for appropriateness. After exclusions, 7 studies were included (2017-2023): 4 qualitative, 1 crossover, 1 randomized controlled, and 1 observational. Studies included adolescents (n = 1), adults (n = 3) or both (n = 2), and all ages (n = 1). In quantitative studies, AID was associated with lower eating distress (-0.43 ± 0.12, P = 0.004) and higher quality of life (3.1, 95% confidence interval [CI]: 0.8-5.4, P = 0.01), but not grams of carbohydrates at meals (1.0; 95% CI: -0.7 to 3.0; P = 0.24) and snacks (0.004; 95% CI: -0.8 to 0.8; P = 0.99) compared to non-AID use. In qualitative studies, AID increased the frequency and portions of food intake and led to less dietary control from parents. AID users reported eating foods higher in energy density. PwT1D were less worried about achieving accurate carbohydrate counting (CC) when using AID. Conclusions: AID use appears to influence eating behaviors, dietary patterns, and CC, although evidence was limited. AID may reduce food management burden due to the perception that AID can correct for CC inaccuracy. Significance: Further research needs to determine if AID allows for simplification of CC and improves eating behaviors while maintaining glycemic stability.

A Multicenter Prospective Evaluation of the Benefits of Two Advanced Hybrid Closed-Loop Systems in Glucose Control and Patient-Reported Outcomes in a Real-world Setting

OBJECTIVE

Advanced hybrid closed-loop systems (AHCL) have been shown to improve glycemic control and patient-reported outcomes in type 1 diabetes. The aim was to analyze the outcomes of two commercially available AHCL in real life.

RESEARCH DESIGN AND METHODS

A prospective study was performed, including adolescents and adults with type 1 diabetes, AHCL naïve, from 14 centers, who initiated the use of MM780G with SmartGuard or Tandem t:slimX2 with Control-IQ. Baseline and 3-month evaluations were performed, assessing HbA1c, time in different glycemic ranges, and patient-reported outcomes. The primary outcome was the between-group time in range 70-180 mg/dL difference from beginning to end of follow-up.

RESULTS

One hundred fifty participants were included, with 75 initiating each system (age: 39.9 ± 11.4 years [16-72]; 64% female; diabetes duration: 21.6 ± 11.9 years). Time in range increased from 61.53 ± 14.01% to 76.17 ± 9.48% (P < 0.001), with no between-group differences (P = 0.591). HbA1c decreased by 0.56% (95% CI 0.44%, 0.68%) (6 mmol/mol, 95% CI 5, 7) (P < 0.001), from 7.43 ± 1.07% to 6.88 ± 0.60% (58 ± 12 to 52 ± 7 mmol/mol) in the MM780G group, and from 7.14 ± 0.70% to 6.56 ± 0.53% (55 ± 8 to 48 ± 6 mmol/mol) in the Control-IQ group (both P < 0.001 to baseline, P = 0.819 between groups). No superiority of one AHCL over the other regarding fear of hypoglycemia or quality of life was found. Improvement in diabetes-related distress was higher in Control-IQ users (P = 0.012). Sleep quality was improved (PSQI: from 6.94 ± 4.06 to 6.06 ± 4.05, P = 0.004), without differences between systems. Experience with AHCL, evaluated by the INSPIRE measures, exceeded the expectations.

CONCLUSIONS

The two AHCL provide significant improvement in glucose control and satisfaction, with no superiority of one AHCL over the other.

New advances in type 1 diabetes

Type 1 diabetes is an autoimmune condition resulting in insulin deficiency and eventual loss of pancreatic β cell function requiring lifelong insulin therapy. Since the discovery of insulin more than 100 years ago, vast advances in treatments have improved care for many people with type 1 diabetes. Ongoing research on the genetics and immunology of type 1 diabetes and on interventions to modify disease course and preserve β cell function have expanded our broad understanding of this condition. Biomarkers of type 1 diabetes are detectable months to years before development of overt disease, and three stages of diabetes are now recognized. The advent of continuous glucose monitoring and the newer automated insulin delivery systems have changed the landscape of type 1 diabetes management and are associated with improved glycated hemoglobin and decreased hypoglycemia. Adjunctive therapies such as sodium glucose cotransporter-1 inhibitors and glucagon-like peptide 1 receptor agonists may find use in management in the future. Despite these rapid advances in the field, people living in under-resourced parts of the world struggle to obtain necessities such as insulin, syringes, and blood glucose monitoring essential for managing this condition. This review covers recent developments in diagnosis and treatment and future directions in the broad field of type 1 diabetes.

Individualized intensive insulin therapy of diabetes: Not only the goal, but also the time

Intensive insulin therapy has been extensively used to control blood glucose levels because of its ability to reduce the risk of chronic complications of diabetes. According to current guidelines, intensive glycemic control requires individualized glucose goals rather than as low as possible. During intensive therapy, rapid blood glucose reduction can aggravate microvascular and macrovascular complications, and prolonged overuse of insulin can lead to treatment-induced neuropathy and retinopathy, hypoglycemia, obesity, lipodystrophy, and insulin antibody syndrome. Therefore, we need to develop individualized hypoglycemic plans for patients with diabetes, including the time required for blood glucose normalization and the duration of intensive insulin therapy, which deserves further study.

Artificial Intelligence and Machine Learning for Improving Glycemic Control in Diabetes: Best Practices, Pitfalls, and Opportunities

OBJECTIVE

Artificial intelligence and machine learning are transforming many fields including medicine. In diabetes, robust biosensing technologies and automated insulin delivery therapies have created a substantial opportunity to improve health. While the number of manuscripts addressing the topic of applying machine learning to diabetes has grown in recent years, there has been a lack of consistency in the methods, metrics, and data used to train and evaluate these algorithms. This manuscript provides consensus guidelines for machine learning practitioners in the field of diabetes, including best practice recommended approaches and warnings about pitfalls to avoid.

METHODS

Algorithmic approaches are reviewed and benefits of different algorithms are discussed including importance of clinical accuracy, explainability, interpretability, and personalization. We review the most common features used in machine learning applications in diabetes glucose control and provide an open-source library of functions for calculating features, as well as a framework for specifying data sets using data sheets. A review of current data sets available for training algorithms is provided as well as an online repository of data sources.

SIGNIFICANCE

These consensus guidelines are designed to improve performance and translatability of new machine learning algorithms developed in the field of diabetes for engineers and data scientists.

Automated Insulin Delivery for Pregnant Women With Type 1 Diabetes: Where do we stand?

Automated insulin delivery (AID) systems mimic an artificial pancreas via a predictive algorithm integrated with continuous glucose monitoring (CGM) and an insulin pump, thereby providing AID. Outside of pregnancy, AID has led to a paradigm shift in the management of people with type 1 diabetes (T1D), leading to improvements in glycemic control with lower risk for hypoglycemia and improved quality of life. As the use of AID in clinical practice is increasing, the number of women of reproductive age becoming pregnant while using AID is also expected to increase. The requirement for lower glucose targets than outside of pregnancy and for frequent adjustments of insulin doses during pregnancy may impact the effectiveness and safety of AID when using algorithms for non-pregnant populations with T1D. Currently, the CamAPS® FX is the only AID approved for use in pregnancy. A recent randomized controlled trial (RCT) with CamAPS® FX demonstrated a 10% increase in time in range in a pregnant population with T1D and a baseline glycated hemoglobin (HbA1c) ≥ 48 mmol/mol (6.5%). Off-label use of AID not approved for pregnancy are currently also being evaluated in ongoing RCTs. More evidence is needed on the impact of AID on maternal and neonatal outcomes. We review the current evidence on the use of AID in pregnancy and provide an overview of the completed and ongoing RCTs evaluating AID in pregnancy. In addition, we discuss the advantages and challenges of the use of current AID in pregnancy and future directions for research.

Glucose and Psychosocial Outcomes 12 Months Following Transition from Multiple Daily Injections to Advanced Hybrid Closed Loop in Youth with Type 1 Diabetes and Suboptimal Glycemia

Objective: To investigate 12-month glycemic and psychosocial changes following transition from multiple daily injections (MDI) to advanced hybrid closed-loop (AHCL) therapy in youth (aged 13-25 years) with type 1 diabetes and suboptimal glycemia (glycated hemoglobin [HbA1c] ≥8.5% [69 mmol/mol]). Research Design and Methods: Prospective, single arm, dual-center study in 20 participants. Extension phase outcomes reported after 12 months, including HbA1c, time in glycemic ranges, AHCL system performance, and psychosocial questionnaires assessing quality of life, diabetes treatment, and sleep. Results: After 12 months, 19 out of 20 participants continued to use AHCL. Average time-in-range 70-180 mg/dL (3.9-10.0 mmol/L) improved from 27.6% ± 13.2% to 62.5% ± 11.4%. This translated to an average 2.5 percentage-point (27.1 mmol/mol) improvement in HbA1c from 10.5% ± 2.1% (91.2 mmol/mol) at baseline to 8.0% ± 0.9% (64.1 mmol/mol) at 12 months. Psychosocial questionnaires and very high HbA1c at study entry indicated significant diabetes-associated burden for both individuals and parents. After 12 months, improvements were observed in general and diabetes-specific health-related quality of life, as well as in diabetes treatment satisfaction. Safety data were reassuring with a diabetic ketoacidosis rate of 0.15 per participant-year after 12 months of AHCL (compared to 0.25 per participant-year in the 12 months before the study). Conclusions: After 12 months of AHCL usage, this study highlights the potential for substantial and sustained glycemic and psychosocial improvements among individuals experiencing considerable diabetes burden and suboptimal glycemia, following their switch from MDI to AHCL.

9. Pharmacologic Approaches to Glycemic Treatment: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

7. Diabetes Technology: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

5. Facilitating Positive Health Behaviors and Well-being to Improve Health Outcomes: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

The Hybrid Closed-Loop System Tandem t:slim X2™ with Control-IQ Technology: Expert Recommendations for Better Management and Optimization

Technological advances in the management of diabetes, especially type 1 diabetes (T1D), have played a main role in significantly improving glycemic control of these patients in recent years. Undoubtedly, the most important advance has been the commercialization of hybrid closed-loop systems (HCL). Their effectiveness places them in the different guidelines from scientific societies as the gold standard for the treatment of people with T1D. However, obtaining the maximum performance from these systems requires a degree of expertise from the professionals who care for these patients. Specifically, the Tandem X2:slim with Control-IQ technology system, due to its features and configuration options and adjustments, allows T1D patients to better adapt the management of diabetes to multiple circumstances in their day-to-day life. It is necessary, however, to follow a systematic process to start the system and also for the subsequent follow-up, which allows its optimization in the shortest possible time. This expert recommendation reviews the main features of this HCL system, suggesting how to implement it and optimize its use after gaining experience treating many patients.

Comparison of Control-IQ and open-source AndroidAPS automated insulin delivery systems in adults with type 1 diabetes: The CODIAC study

AIM

To compare open-source AndroidAPS (AAPS) and commercially available Control-IQ (CIQ) automated insulin delivery (AID) systems in a prospective, open-label, single-arm clinical trial.

METHODS

Adults with type 1 diabetes who had been using AAPS by their own decision entered the first 3-month AAPS phase then were switched to CIQ for 3 months. The results of this treatment were compared with those after the 3-month AAPS phase. The primary endpoint was the change in time in range (% TIR; 70-80 mg/dL).

RESULTS

Twenty-five people with diabetes (mean age 34.32 ± 11.07 years; HbA1c 6.4% ± 3%) participated in this study. CIQ was comparable with AAPS in achieving TIR (85.72% ± 7.64% vs. 84.24% ± 8.46%; P = .12). Similarly, there were no differences in percentage time above range (> 180 and > 250 mg/dL), mean sensor glucose (130.3 ± 13.9 vs. 128.3 ± 16.9 mg/dL; P = .21) or HbA1c (6.3% ± 2.1% vs. 6.4% ± 3.1%; P = .59). Percentage time below range (< 70 and < 54 mg/dL) was significantly lower using CIQ than AAPS. Even although participants were mostly satisfied with CIQ (63.6% mostly agreed, 9.1% strongly agreed), they did not plan to switch to CIQ.

CONCLUSIONS

The CODIAC study is the first prospective study investigating the switch between open-source and commercially available AID systems. CIQ and AAPS were comparable in achieving TIR. However, hypoglycaemia was significantly lower with CIQ.