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.

Use of a long-term continuous glucose monitor for predicting sulfonylurea dose in patients with neonatal diabetes mellitus: a case series.

Neonatal diabetes mellitus (NDM) is a monogenic form of diabetes that presents with uncontrolled hyperglycemia during the first 6 months of life. NDM is a rare disease in which gene variants mainly cause ß-cell loss or dysfunction (6q24 duplication, KCNJ11, and ABCC8). Although NDM is primarily treated through insulin therapy, it is highly challenging to manage blood glucose levels using insulin therapy during infancy. In contrast, KCNJ11 and ABCC8 mutant patients received oral sulfonylureas (SU) instead of insulin injections; however, the dose and frequency differ among individuals. Continuous glucose monitoring (CGM) is useful in patients with type 1 diabetes; but reports on patients with NDM are lacking. Herein, we report two cases of NDM with the KCNJ11 variant. We used CGM not only during insulin injection therapy but also after switching to oral SU therapy. The CGM data can also be used to determine the dose and frequency of SU. Furthermore, long-term CGM may be useful for adjusting SU dose and frequency, and maintaining good glycemic control not only during insulin injection but also during oral SU therapy.

Once-weekly insulin icodec compared with daily basal insulin analogues in type 2 diabetes: Participant-level meta-analysis of the ONWARDS 1-5 trials.

AIM: To perform a participant-level post hoc meta-analysis of Phase 3a trials in type 2 diabetes (T2D) to characterize the hypoglycaemia safety and glycaemic efficacy of once-weekly insulin icodec (icodec). MATERIALS AND METHODS: All ONWARDS 1-5 randomized participants were pooled as overall T2D, insulin-naive, an insulin-experienced subgroups, and by once-daily trial comparator (degludec or glargine U100). The main outcomes included incidence and rates of clinically significant and severe hypoglycaemia. Additional endpoints included change in glycated haemoglobin (HbA1c) from baseline and HbA1c target achievement without clinically significant or severe hypoglycaemia. RESULTS: The meta-analysis comprised 3765 participants (1882 icodec vs. 1883 comparators). In the overall T2D pool, clinically significant hypoglycaemia incidence was similar in the icodec group versus the comparator group (17.9% vs. 16.2%, odds ratio [OR] 1.14, 95% confidence interval [CI] 0.94, 1.38); however, rates were low but significantly higher in the icodec group (1.15 vs. 1.00 episodes/participant-year of exposure, estimated rate ratio 1.51 [95% CI 1.24, 1.85]). Fewer severe hypoglycaemic episodes occurred with icodec than with comparators (8 vs. 18). A greater reduction in HbA1c occurred with icodec versus comparators, irrespective of subgroup (estimated treatment difference range [-0.10 to -0.29%]; all p < 0.05). Across subgroups, except for the insulin-experienced subgroup, the odds of achieving HbA1c <53 mmol/mol (7.0%) without clinically significant or severe hypoglycaemia were greater with icodec than with comparators (OR range 1.30-1.55; all p < 0.05). CONCLUSIONS: Icodec was associated with a similar incidence but higher rates of clinically significant hypoglycaemia (equating to one additional hypoglycaemic episode every 6 years) and fewer severe hypoglycaemic episodes versus comparators. Our findings also confirmed the greater efficacy of icodec that was demonstrated in the ONWARDS trial programme.

Seasonal fluctuations of CGM metrics in individuals with type 1 diabetes using an intermittently scanned CGM device or sensor augmented pump.

OBJECTIVE: To elucidate the fluctuations in glucose levels measured using CGM-metrics during the four distinct seasons of the year in individuals with type 1 diabetes mellitus (T1DM) using an intermittently scanned CGM (isCGM) device or sensor augmented pump (SAP). RESEARCH DESIGN AND METHODS: This retrospective, single-center study enrolled 93 individuals with T1DM who were equipped with an isCGM device or SAP at Kobe University Hospital. The subjects had a median age of 47.0 years [interquartile range, 37.0-62.0 years], 25 individuals (26.9%) were male, median body mass index was 22.0 kg/m2 [20.8-23.8 kg/m2], and median hemoglobin A1c level was 7.4% [6.9-8.0%]. CGM data were reviewed from January to December 2019, and the mean sensor glucose (SG) value, time above range (TAR), time in range (TIR), time below range (TBR), and standard deviation (SD) of SG were calculated for each season (spring, March-May; summer, June-August; autumn, September-November; winter, December-February). RESULTS: Seasonal fluctuations were detected for mean SG, TAR, TIR, and SD, with TIR being lower and mean SG, TAR, and SD being higher in cold seasons (spring or winter) than in warm seasons (summer or autumn). CONCLUSION: Seasonal fluctuations in CGM metrics should be taken into account in future studies performed to evaluate the favorable impact of CGM on glycemic management in individuals with T1DM.

Calibration algorithms for continuous glucose monitoring systems based on interstitial fluid sensing.

Continuous glucose monitoring (CGM) is of great importance to the treatment and prevention of diabetes. As a proven commercial technology, electrochemical glucose sensor based on interstitial fluid (ISF) sensing has high sensitivity and wide detection range. Therefore, it has good promotion prospects in noninvasive or minimally-invasive CGM system. However, since there are concentration differences and time lag between glucose in plasma and ISF, the accuracy of this type of sensors are still limited. Typical calibration algorithms rely on simple linear regression which do not account for the variability of the sensitivity of sensors. To enhance the accuracy and stability of CGM based on ISF, optimization of calibration algorithm for sensors is indispensable. While there have been considerable researches on improving calibration algorithms for CGM, they have still received less attention. This article reviews the problem of typical calibration and presents the outstanding calibration algorithms in recent years. Finally, combined with existing research and emerging sensing technologies, this paper makes an outlook on the future calibration algorithms for CGM sensors.

Perspective of Continuous Glucose Monitoring-Based Interventions at the Various Stages of Type 2 Diabetes.

Continuous glucose monitoring (CGM) is now advocated for the clinical management of individuals with type 1 diabetes (T1D). However, this glucose monitoring strategy is not routinely used in type 2 diabetes (T2D), given the large population, significant cost implications and relatively limited supporting evidence. T2D is a more heterogenous condition compared with T1D with various glucose lowering therapies that do not necessarily require CGM to ensure within target glucose levels. While all individuals with T2D may benefit from CGM at certain time points, the whole T2D population does not necessarily require this technology continuously, which should be prioritized based on patient benefit and cost effectiveness. In this pragmatic opinion piece, we describe the rationale and evidence for CGM use in different subgroups of individuals with T2d, divided according to the stage of the condition, glycemic therapies, presence of diabetes complications, or associated co-morbidities. We discuss a total of 16 T2D subgroups and provide a clinical view on CGM use in each, based on current evidence while also highlighting areas of knowledge gaps. This work provides health care professionals with a simple guide to CGM use in different T2D groups and gives suggestion for future studies to justify expansion of this technology.

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.

Continuous glucose monitoring with FreeStyle Libre PRO sensor in patients with type 2 diabetes and end-stage renal failure on haemoDIALysis (FSLPRO-DIAL pilot study).

AIMS: For end-stage renal disease (ESRD) patients with diabetes on haemodialysis, diabetes control is difficult to achieve. Hypoglycaemia is a major problem in these frailty subjects. Continuous glucose monitoring (CGM) devices appear therefore to be a good tool to help patients monitor their glycaemic control and to help practitioners optimize treatment. We aimed to compare the laboratory value of Hba1c with the sensor-estimated value of Hba1c (= glucose management indicator, GMI) in ESRD patients with type 2 diabetes (T2D) (with or without insulin treatment) on haemodialysis. Secondly, we aimed to identify CGM-derived monitoring parameters [time in range, time in hypo/hyperglycaemia, glycaemic variability (coefficient of variation, CV)] to identify patients at risk of frequent hypo- or hyperglycaemia. METHODS: The FSLPRO-DIAL pilot study (NCT04641650) was a prospective monocentric cohort study including 29 subjects with T2D who achieve the protocol. Inclusion criteria were: age ≥ 18 years, haemodialysis duration for at least 3 months, type 2 diabetes with no change in treatment for at least 3 months. Demographic data and blood sample were collected at the day of inclusion. Freestyle Libre pro IQ sensor (blinded CGM) was inserted for 14 days. After this period, all CGMs data were collected and analysed. RESULTS: Data were available for 27 patients. Mean age was 73 ± 10, mean BMI 27.2 kg/m2, mean duration of diabetes 16.9 years and mean dialysis duration 2.9 years. Twenty-four subjects were treated with insulin. Mean HbA1c was 6.6% (SD 1.2), and mean GMI was 6.7% (SD 0.9) (no significant difference, p = 0.3). Twelve subjects (44.4%) had a discordance between HbA1c and GMI of < 0.5%, 11 (40.8%) had a discordance between 0.5 and 1%, and only 4 (14.8%) had a discordance of > 1%. Mean time in range (70-180 mg/dl) was 71.9%, mean time below range (< 70 mg/dl) was 5.6%, and mean time above range (> 180 mg/dl) was 22.1%. Mean CV was 31.8%. For 13 out of 27 patients, we reduced antidiabetic treatment by stopping treatments or reducing insulin doses. CONCLUSION: In this pilot study, there was no global significant difference between HbA1c and GMI in this particular cohort with very well-controlled diabetes. However, the use of the sensor enabled us to identify an excessive time in hypoglycemia in this fragile population and to adapt their treatment.

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.

Glucose Targets Using Continuous Glucose Monitoring Metrics in Older Adults With Diabetes: Are We There Yet?

The older population is increasing worldwide and up to 30% of older adults have diabetes. Older adults with diabetes are at risk of glucose-related acute and chronic complications. Recently, mostly in type 1 diabetes (T1D), continuous glucose monitoring (CGM) devices have proven beneficial in improving time in range (TIR glucose, 70-180 mg/dL or glucose 3.9-10 mmol/L), glycated hemoglobin (HbA1c), and in lowering hypoglycemia (time below range [TBR] glucose <70 mg/dL or glucose <3.9 mmol/L). The international consensus group formulated CGM glycemic targets relating to older adults with diabetes based on very limited data. Their recommendations, based on expert opinion, were aimed at mitigating hypoglycemia in all older adults. However, older adults with diabetes are a heterogeneous group, ranging from healthy to very complex frail individuals based on chronological, biological, and functional aging. Recent clinical trial and real-world data, mostly from healthy older adults with T1D, demonstrated that older adults often achieve CGM targets, including TIR recommended for non-vulnerable groups, but less often meet the recommended TBR <1%. Existing data also support that hypoglycemia avoidance may be more strongly related to minimization of glucose variability (coefficient of variation [CV]) rather than lower TIR. Very limited data are available for glucose goals in older adults adjusted for the complexity of their health status. Herein, we review the bidirectional associations between glucose and health status in older adults with diabetes; use of diabetes technologies, and their impact on glucose control; discuss current guidelines; and propose a new set of CGM targets for older adults with insulin-treated diabetes that are individualized for health and living status.

Severe dawn phenomenon predicts long-term risk of all-cause mortality in patients with type 2 diabetes.

AIMS: The dawn phenomenon (DP) is an abnormal early morning blood glucose rise without nocturnal hypoglycaemia, which can be more easily and precisely assessed with continuous glucose monitoring (CGM). This prospective study aimed to explore the association between DP and the risk of all-cause mortality in patients with type 2 diabetes. MATERIALS AND METHODS: A total of 5542 adult inpatients with type 2 diabetes in a single centre were analysed. The magnitude of DP (ΔG) was defined as the increment in the CGM-determined glucose value from nocturnal nadir (after 24:00) to prebreakfast. Participants were stratified into four groups by ΔG: ≤1.11, 1.12-3.33, 3.34-5.55, and >5.55 mmol/L. Cox proportional hazard regression models were used to evaluate the impact of DP on all-cause mortality risk. RESULTS: During a median follow-up of 9.4 years, 1083 deaths were identified. The restricted cubic spline revealed a nonlinear (p for nonlinearity = 0.002) relationship between ΔG and the risk of all-cause mortality. A multivariate-adjusted Cox regression model including glycated haemoglobin A1c (HbA1c) showed that ΔG > 5.55 mmol/L was associated with 30% (95% CI, 1.01-1.66) higher risk of all-cause mortality, as compared with ΔG 1.12-3.33 mmol/L. CONCLUSIONS: Higher ΔG is significantly related to an increased risk of all-cause mortality in type 2 diabetes, suggesting that severe DP should be given more attention as a part of glucose management to reduce the risk of long-term adverse outcomes.

Intermittently scanned continuous glucose monitoring provides no benefit over structured self-monitoring of blood glucose in type 2 diabetes not on prandial insulin, in the context of diabetes self-management education: GLucose monitoring programme SingaporE (GLiMPSE).

OBJECTIVE: We evaluated the impact of intermittently scanned continuous glucose monitoring(is-CGM)over self-monitoring of blood glucose(SMBG) in the context of diabetes self-management education (DSME) in sub-optimally controlled type 2 diabetes(T2D) in a multi-ethnicsetting. RESEARCH DESIGN AND METHOD: Randomized-controlled, open-label trial (NCT04564911), of T2D with HbA1c ≥ 7.5-≤10 %, on oral agents with/without basal insulin was carried out. Intervention arm received 6 weeks(w) continuous is-CGM, followed by one is-CGM/month till 24w. Control arm was advised to perform 4 SMBG/day. Educationwas delivered at weeks 0, 2, 8, 16. PRIMARY OUTCOME: Change in HbA1c from baseline at 24w. Modified intention-to-treat (mITT) analysis with linear mixed-effect model for repeated measurementswas performed. RESULTS: 176 subjects, age 55 ± 10.7 years(y), DM duration 11 ± 7.3y, BMI 27.8 ± 5.9 kg/m2, 58 % Male, 29.5 % basal insulin users were analysed. Within each arm,from baseline to 24w, mean HbA1c decreasedby -0.6 % (-6.6.mmol/mol, p-value < 0.01)and weight decreased(isCGM: -1.44 kg; SMBG: -1.25 kg, both p < 0.01). These changes were sustained to one year. However, there wasno significant difference in these parameters between arms (p-value > 0.05). CONCLUSION: In the context of DSME, use of either SMBG or is-CGM led to improved glycaemia and reduced weight over a period of 24 weeks, sustained to one year.

Improved glycaemic control induced by evening activity breaks does not persist overnight amongst healthy adults: A randomized crossover trial.

AIMS: To compare the effects of 4 hours of laboratory-based regular activity breaks (RABs) and prolonged sitting (SIT) on subsequent 48-h free-living interstitial glucose levels in a group of healthy adults. MATERIALS AND METHODS: In this randomized crossover trial, participants completed two 4-h laboratory-based interventions commencing at ~5:00 pm: (1) SIT and (2) SIT interrupted with 3 min of body weight resistance exercise activity breaks every 30 min (RABs). Continuous glucose monitoring was performed during the intervention and for 48-h after, during which time participants returned to a free-living setting. RESULTS: Twenty-eight adults (female n = 20, mean ± SD age 25.5 ± 5.6 years, body mass index 29.2 ± 6.9 kg/m2) provided data for this analysis. During the intervention period, RABs lowered mean interstitial glucose by 8.3% (-0.47 mmol/L/4 h, 95% confidence interval [CI] -0.74 to -0.20; p = 0.001) and area under the curve (AUC) by 8.9% (-2.01 mmol/L/4 h, 95% CI -3.05 to -0.97; p < 0.001) compared to SIT. Measures of glycaemic variability were not significantly different during the intervention. There were no significant differences in mean glucose and AUC between conditions during the first nocturnal period and 24-h post intervention. When compared to SIT, RABs increased continuous overall net action of glucose at 1 h and SD glucose by 22% (0.18 mmol/L, 95% CI 0.03 to 0.29; p = 0.018) and 26% (95% CI 4.9 to 42.7; p = 0.019) in the first nocturnal period and by 10% (0.09 mmol/L, 95% CI 0.01, 0.17; p = 0.025) and 15% (95% CI 6.6 to 22.4; p = 0.001) in the 24-h post intervention period, respectively. CONCLUSION: Performing activity breaks in the evening results in acute reductions in interstitial glucose concentrations; however, the magnitude of these changes is not maintained overnight or into the following 48 hours.

The role of real-time continuous glucose monitoring in diabetes management and how it should link to integrated personalized diabetes management.

Diabetes is a complex metabolic condition that demands tailored, individualized approaches for effective management. Real-time continuous glucose monitoring (rtCGM) systems have improved in terms of design, usability and accuracy over the years and play a pivotal role in the delivery of integrated personalized diabetes management (iPDM). iPDM is a comprehensive multidisciplinary approach that combines individualized care strategies utilizing technologies and interventions and encourages the active involvement of the person with diabetes in the care provided. The use of stand-alone rtCGM and its integration with other diabetes technologies, such as hybrid automated insulin delivery, have enabled improved glycaemic and quality of life outcomes for people with diabetes. As the uptake of rtCGM and associated technologies is increasing and becoming the standard of care for people with diabetes, it is important that efforts are focused on associated goals such as reducing health inequalities in terms of access, aligning structured education with rtCGM usage, choosing the right technology based on needs and preferences, and minimizing burden while aiming for optimal glucose outcomes. Utilizing rtCGM in other settings than outpatients and in diabetes cohorts beyond type 1 and type 2 diabetes needs further exploration. This review aims to provide an overview of the role of rtCGM and how best to link rtCGM to iPDM, highlighting its role in enhancing personalized treatment strategies.

Bridging dose of U-100 glargine with first dose of insulin degludec improves glycaemia in the 48 h after transition in twice-daily glargine users.

AIMS: To study the effects of a bridging dose of U-100 glargine (U-100G) with the first dose of degludec in type 1 diabetes (T1D) patients transitioning from glargine to degludec, by comparing the glucose metrics 48 h before and after the transition. MATERIALS AND METHODS: Patients with T1D on a stable U-100G regimen and with glycated haemoglobin concentration <75 mmol/mol were randomized (double-blind) to one dose of placebo or U-100G with first dose of degludec, administered at 9:00 pm. Patients on once-daily U-100G at baseline received 50% of total U-100G dose (bridging dose), while patients on twice-daily U-100G received 50% of the evening U-100G dose. Participants wore a continuous glucose monitor during the study. RESULTS: Forty participants were randomized, of whom 37 completed the study. The cohort was 65% male, the mean age was 47 years, duration of T1D 22 years, BMI 26 kg/m2, HbA1c 51 mmol/mol and total daily insulin dose 0.7 units/kg body weight. The bridging group included 19 participants (once-daily U-100G: n = 12; twice-daily U-100G: n = 7) and the placebo group included 18 participants (once-daily U-100G: n = 12; twice-daily U-100G: n = 6). Change in time in range (TIR) was not significantly different between the two treatment groups. In secondary analyses, among twice-daily U-100G users, TIR (3.9-10 mmol/L) increased 8% in the bridging group in the 48 h after first dose of degludec compared to the preceding 48 h, while participants in the placebo group had a 9.5% decrease (p = 0.027). CONCLUSIONS: A subgroup of well-controlled twice-daily U-100G users transitioning to degludec benefited from a 50% bridging dose of evening U-100G with the first dose of degludec in a small pilot study.

Exploring the Impact of Glycemic Control on Diabetic Retinopathy: Emerging Models and Prognostic Implications.

This review addresses the complexities of type 1 diabetes (T1D) and its associated complications, with a particular focus on diabetic retinopathy (DR). This review outlines the progression from non-proliferative to proliferative diabetic retinopathy and diabetic macular edema, highlighting the role of dysglycemia in the pathogenesis of these conditions. A significant portion of this review is devoted to technological advances in diabetes management, particularly the use of hybrid closed-loop systems (HCLSs) and to the potential of open-source HCLSs, which could be easily adapted to different patients' needs using big data analytics and machine learning. Personalized HCLS algorithms that integrate factors such as patient lifestyle, dietary habits, and hormonal variations are highlighted as critical to reducing the incidence of diabetes-related complications and improving patient outcomes.

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.