Automated Insulin Delivery Research Articles

Supervised and Unsupervised Approaches for the Real-Time Detection of Undesired Insulin Suspension Caused by Malfunctions.

Automated insulin delivery (AID) systems, permit improved treatment of type 1 diabetes (T1D). Unfortunately, malfunctioning in the insulin pump or in the infusion set can prevent insulin from being administered, reducing the AID efficacy and posing the patient at risk. Different data-driven methods available in the literature can be used to deal with the problem of automatically detecting complete insulin suspension in real-time. This article investigates both supervised and unsupervised strategies and proposes a fair comparison under either population or personalized settings. Several algorithms are compared using data generated through the UVA/Padova T1D simulator, a computer simulator widely used to test control strategies in silico and accepted by the Food and Drugs Administration (FDA) as a substitute to animal pre-clinical trials. Two synthetic data sets, each consisting of 100 virtual subjects monitored for 1 month, were generated. Occasional faults of the insulin pump are simulated as complete occlusions by suspending the therapy administration. Personalized algorithms are investigated with unsupervised approaches only, since personalized labels are hardly available. In the population scenario, the supervised approach outperforms the unsupervised strategy. In particular, logistic regression and random forest achieves a recall of 72% and 82%, with 0.12 and 0.21 false positives (FP) per day, respectively. In the personalized setting scenario, the unsupervised algorithms are tailored on each patient and outperform the population ones, in particular isolation forest achieves a recall 80% and 0.06 FPs per day. This article suggests that unsupervised personalized approach, by addressing the large variability in glucose response among individuals with T1D, is superior to other one-fits-all approaches in detecting insulin suspensions caused by malfunctioning. Population methodologies can be effectively used while waiting to collect sufficient patient data, when the system is installed on a new patient.

Mitigating Severe Hypoglycemia in Users of Advanced Diabetes Technologies: Impaired Awareness of Hypoglycemia and Unhelpful Hypoglycemia Beliefs as Targets for Interventions.

Objective: A subgroup analysis of the Hypoglycemia Awareness Restoration Programme for people with type 1 diabetes and problematic hypoglycemia persisting despite optimized care (HARPdoc) trial was conducted to explore the impact of Blood Glucose Awareness Training (BGAT, a hypoglycemia awareness training program) and the HARPdoc (a psychoeducation addressing unhelpful hypoglycemia beliefs) in reducing severe hypoglycemia (SH) in individuals using advanced diabetes technologies (ADTs). Methods: Data from trial participants who utilized ADTs, including continuous glucose monitors or automated insulin delivery systems, were extracted. Generalized linear mixed-effects models with Poisson distribution or linear mixed-effects models were used to evaluate SH incidence, and Gold questionnaire, Attitudes to Awareness of Hypoglycemia (A2A), Problem Areas in Diabetes (PAID), Hospital Anxiety and Depress Scale (HADS)-anxiety, and HADS-depression scores as measures of hypoglycemia awareness, unhelpful hypoglycemia beliefs, diabetes distress, and anxiety and depression symptoms, respectively. Results: In the 45 participants using ADTs, the BGAT and HARPdoc interventions both reduced SH incidence by more than 50% (P < 0.0001) and yielded improvements in hypoglycemia awareness (P < 0.05). HARPdoc outperformed BGAT in reducing SH at month 24 (P = 0.01). HARPdoc also mitigated unhelpful hypoglycemia beliefs (P < 0.0001), diabetes distress (P < 0.05), and anxiety symptoms (P < 0.05); BGAT demonstrated no significant impacts in these respects. Neither HARPdoc nor BGAT had significant effects on depression symptoms. Conclusion: Psychoeducation (BGAT and HARPdoc) was effective in reducing SH in people using ADTs. HARPdoc may also provide greater long-term SH reduction and improves psychological well-being in this patient group.

Predicting Blood Glucose Levels with Organic Neuromorphic Micro-Networks.

Accurate glucose prediction is vital for diabetes management. Artificial intelligence and artificial neural networks (ANNs) are showing promising results for reliable glucose predictions, offering timely warnings for glucose fluctuations. The translation of these software-based ANNs into dedicated computing hardware opens a route toward automated insulin delivery systems ultimately enhancing the quality of life for diabetic patients. ANNs are transforming this field, potentially leading to implantable smart prediction devices and ultimately to a fully artificial pancreas. However, this transition presents several challenges, including the need for specialized, compact, lightweight, and low-power hardware. Organic polymer-based electronics are a promising solution as they have the ability to implement the behavior of neural networks, operate at low voltage, and possess key attributes like flexibility, stretchability, and biocompatibility. Here, the study focuses on implementing software-based neural networks for glucose prediction into hardware systems. How to minimize network requirements, downscale the architecture, and integrate the neural network with electrochemical neuromorphic organic devices, meeting the strict demands of smart implants for in-body computation of glucose prediction is investigated.

Technology for the Management of Type 1 Diabetes Mellitus in Saudi Arabia and MENA Region: A Systematic Review.

Diabetes technology in the form of digital health or medical devices holds a promise for improving the quality of life and glycemic outcomes. A comprehensive insight into diabetes technology and its impact in Saudi Arabia and the MENA region may improve type 1 diabetes mellitus (T1DM) management. This study aimed to assess the impact of different DM-specific technologies: insulin pump therapy, continuous glucose monitoring (CGM), and automated insulin delivery system in terms of glycemic control and QoL among T1DM patients in Saudi Arabia and the MENA region. A systematic literature search was performed in PubMed and Scopus from 2005 until August 2023. The search was based on the PICO strategy, focusing on T1DM patients, diabetes technology, and QoL. The inclusion criteria were studies illustrating the effect of diabetes technologies on glycemic control or quality of life or both among T1DM patients. Systematic reviews, books, letters, or studies, including type 2 diabetes mellitus, were excluded. From 101 articles, eighteen studies were duplicated, and thirty-three studies were excluded after reading the title and abstract. Of the 50 articles analyzed, twenty-five articles did not meet the inclusion criteria. Therefore, 25 articles involving a total of 3088 participants were enrolled in the study. It was shown that a continuous glucose monitoring system and continuous subcutaneous insulin infusion improved the glycemic control and the QoL of T1DM patients. There was a positive impact of insulin pumps, continuous glucose monitoring (CGM) systems, and telemedicine in achieving optimal glucose control and better QoL. Further studies are recommended to clarify the significant role of advanced diabetes technologies.

Long-term assessment of the NHS hybrid closed-loop real-world study on glycaemic outcomes, time-in-range, and quality of life in children and young people with type 1 diabetes

Hybrid closed-loop (HCL) systems seamlessly interface continuous glucose monitoring (CGM) with insulin pumps, employing specialised algorithms and user-initiated automated insulin delivery. This study aimed to assess the efficacy of HCLs at 12 months post-initiation on glycated haemoglobin (HbA1c), time-in-range (TIR), hypoglycaemia frequency, and quality of life measures among children and young people (CYP) with type 1 diabetes mellitus (T1DM) and their caregivers in a real-world setting. Conducted between August 1, 2021, and December 10, 2022, the prospective recruitment took place in eight paediatric diabetes centres across England under the National Health Service England’s (NHSE) HCL pilot real-world study. A cohort of 251 CYP (58% males, mean age 12.3 years) with T1DM participated (89% white, 3% Asian, 4% black, 3% mixed ethnicity, and 1% other). The study utilised three HCL systems: (1) Tandem Control-IQ AP system, which uses the Tandem t:slim X2 insulin pump (Tandem Diabetes Care, San Diego, CA, USA) with the Dexcom G6® CGM (Dexcom, San Diego, CA, USA) sensor; (2) Medtronic MiniMed™ 780G with the Guardian 4 sensor (Medtronic, Northridge, CA, USA); and (3) the CamAPS FX (CamDiab, Cambridge, UK) with the Ypsomed insulin pump (Ypsomed Ltd, Escrick, UK) and Dexcom G6® CGM.All systems were fully funded by the NHS. Results demonstrated significant improvements in HbA1c (average reduction at 12 months 7 mmol/mol; P < 0.001), time-in-range (TIR) (average increase 13.4%; P < 0.001), hypoglycaemia frequency (50% reduction), hypoglycaemia fear, and quality of sleep (P < 0.001) among CYP over a 12-month period of HCL usage. Additionally, parents and carers experienced improvements in hypoglycaemia fear and quality of sleep after 6 and 12 months of use. In addition to the improvements in glycaemic management, these findings underscore the positive impact of HCL systems on both the well-being of CYP with T1DM and the individuals caring for them.

Comparison between a tubeless, on-body automated insulin delivery system and a tubeless, on-body sensor-augmented pump in type 1 diabetes: a multicentre randomised controlled trial.

This study compares the efficacy and safety of a tubeless, on-body automated insulin delivery (AID) system with that of a tubeless, on-body sensor-augmented pump (SAP). This multicentre, parallel-group, RCT was conducted at 13 tertiary medical centres in South Korea. Adults aged 19-69 years with type 1 diabetes who had HbA1c levels of <85.8 mmol/mol (<10.0%) were eligible. The participants were assigned at a 1:1 ratio to receive a tubeless, on-body AID system (intervention group) or a tubeless, on-body SAP (control group) for 12 weeks. Stratified block randomisation was conducted by an independent statistician. Blinding was not possible due to the nature of the intervention. The primary outcome was the percentage of time in range (TIR), blood glucose between 3.9 and 10.0 mmol/l, as measured by continuous glucose monitoring. ANCOVAs were conducted with baseline values and study centres as covariates. A total of 104 participants underwent randomisation, with 53 in the intervention group and 51 in the control group. The mean (±SD) age of the participants was 40±11 years. The mean (±SD) TIR increased from 62.1±17.1% at baseline to 71.5±10.7% over the 12 week trial period in the intervention group and from 64.7±17.0% to 66.9±15.0% in the control group (difference between the adjusted means: 6.5% [95% CI 3.6%, 9.4%], p<0.001). Time below range, time above range, CV and mean glucose levels were also significantly better in the intervention group compared with the control group. HbA1c decreased from 50.9±9.9 mmol/mol (6.8±0.9%) at baseline to 45.9±7.4 mmol/mol (6.4±0.7%) after 12 weeks in the intervention group and from 48.7±9.1 mmol/mol (6.6±0.8%) to 45.7±7.5 mmol/mol (6.3±0.7%) in the control group (difference between the adjusted means: -0.7 mmol/mol [95% CI -2.0, 0.8 mmol/mol] (-0.1% [95% CI -0.2%, 0.1%]), p=0.366). No diabetic ketoacidosis or severe hypoglycaemia events occurred in either group. The use of a tubeless, on-body AID system was safe and associated with superior glycaemic profiles, including TIR, time below range, time above range and CV, than the use of a tubeless, on-body SAP. Clinical Research Information Service (CRIS) KCT0008398 FUNDING: The study was funded by a grant from the Korea Medical Device Development Fund supported by the Ministry of Science and ICT; the Ministry of Trade, Industry and Energy; the Ministry of Health and Welfare; and the Ministry of Food and Drug Safety (grant number: RS-2020-KD000056).

Optimizing Blood Glucose Regulation in Type 1 Diabetes Patients via Genetic Algorithm-Based Fuzzy Logic Controller Considering Substantial Meal Protocol

Effective management of blood glucose levels in individuals with type 1 diabetes, especially after meals, is crucial for diabetes care. Artificial pancreas systems (APS) perform automated insulin delivery in subjects with type 1 diabetes mellitus (T1DM). In this study, an optimized fuzzy logic controller was designed to achieve a euglycemic range after a substantial meal intake. All in silico simulations were performed using the MATLAB/Simulink environment, leveraging control variability grid analysis (CVGA), and the performance of the controller was evaluated. The proposed controller is based on a fuzzy-logic control law designed in three stages. First, a nonlinear framework of the glucose-insulin regulatory system was identified based on the heavy meal protocol of three patients given as follows: for subject ID 117-1, a total of 295 gCHO; for subject ID 126-1, 236 gCHO; and subject ID 128-1, 394 gCHO over a day. Then, an iterative tree structure was employed to establish a stabilizing control rule for insulin delivery, integrating inputs from two Mamdani Fuzzy Inference System (FIS) objects. Finally, a genetic algorithm refines the control system by fine-tuning the uncertainty of the fuzzy membership functions. Two scenarios were considered for three patients to assess the performance of the proposed controller. The results indicated its effectiveness under various conditions, achieving a time in the range of 61.25%, 71% and 61.10% respectively for the three subjects. The obtained results are analyzed and compared with IMC and multi-objective output feedback controllers. The findings of the study reveal that the proposed controller shows promising advancements in tailored strategies for type 1 diabetes patients, outperforming the other controllers in terms of blood glucose regulation.

Automated Insulin Delivery in Adults With Type 1 Diabetes and Suboptimal HbA1c During Prior Use of Insulin Pump and Continuous Glucose Monitoring: A Randomized Controlled Trial.

Automated insulin delivery (AID) systems offer promise in improving glycemic outcomes for individuals with type 1 diabetes. However, data on those who struggle with suboptimal glycemic levels despite insulin pump and continuous glucose monitoring (CGM) are limited. We conducted a randomized controlled trial to assess the effects of an AID system in this population. Participants with hemoglobin A1c (HbA1c) ≥ 58 mmol/mol (7.5%) were allocated 1:1 to 14 weeks of treatment with the MiniMed 780G system (AID) or continuation of usual care (UC). The primary endpoint was change in time in range (TIR: 3·9-10·0 mmol/L) from baseline to week 14. After this trial period, the UC group switched to AID treatment while the AID group continued using the system. Both groups were monitored for a total of 28 weeks. Forty adults (mean ± SD: age 52 ± 11 years, HbA1c 67 ± 7 mmol/mol [8.3% ± 0.6%], diabetes duration 29 ±13 years) were included. After 14 weeks, TIR increased by 18.7% (95% confidence interval [CI] = 14.5, 22.9%) in the AID group and remained unchanged in the UC group (P < .0001). Hemoglobin A1c decreased by 10.0 mmol/mol (95% CI = 7.0, 13.0 mmol/mol) (0.9% [95% CI = 0.6%, 1.2%]) in the AID group but remained unchanged in the UC group (P < .0001). The glycemic benefits of AID treatment were reproduced after the 14-week extension phase. There were no episodes of severe hypoglycemia or diabetic ketoacidosis during the study. For adults with type 1 diabetes not meeting glycemic targets despite use of insulin pump and CGM, transitioning to an AID system confers considerable glycemic benefits.

Extended Bolus Is No More Needed for Risotto Meal in Children With Type 1 Diabetes Using Automated Insulin Delivery System: A Cohort Study.

Extended Bolus Is No More Needed for Risotto Meal in Children With Type 1 Diabetes Using Automated Insulin Delivery System: A Cohort Study.

Use of the Community-Derived Open-Source Automated Insulin Delivery Loop System in Type 2 Diabetes.

Background: No published data are available on the use of the community-derived open-source Loop hybrid closed-loop controller ("Loop") by individuals with type 2 diabetes (T2D). Methods: Through social media postings, we invited individuals with T2D currently using the Loop system to join an observational study. Thirteen responded of whom seven were eligible for the study, were using the Loop algorithm, and provided data. Results: Mean (±standard deviation) age was 61 ± 13 years, and mean body mass index was 31 ± 5 kg/m2. All but one participant were using noninsulin glucose-lowering medications. Self-reported mean hemoglobin A1c decreased from 7.3% ± 1.1% before starting Loop to 6.0% ± 0.5% on Loop. Time in range 70-180 mg/dL increased from 84% to 93%. The amount of time in hypoglycemia was extremely low before and with Loop (time <54 mg/dL was 0.04% ± 0.06% vs. 0.09% ± 0.07%, respectively). No severe hypoglycemia or diabetic ketoacidosis events were reported while using Loop. Conclusion: These data, though limited, suggest that the Loop system is likely to be effective when used by individuals with T2D and should be evaluated in large-scale studies. Clinical Trial Registration numbers: NCT05951569.

Concordance of Blood Glucose and CGM During a Pilot Trial of Automated Insulin Delivery in Type 1 Diabetes Pregnancies.

Customized and standard automated insulin delivery (AID) systems for use in pregnancies of women with preexisting type 1 diabetes (T1D) are being developed and tested to achieve pregnancy appropriate continuous glucose monitoring (CGM) targets. Guidance on the use of CGM for treatment decisions during pregnancy in the United States is limited. Ten pregnant women with preexisting T1D participated in a trial evaluating at-home use of a pregnancy-specific AID system. Seven-point self-monitoring of blood glucose (SMBG) was compared to the closest sensor glucose (Dexcom G6 CGM) value biweekly to assess safety and reliability based on the 20%/20 mg/dL criteria. All participants completed the study with 7 participants satisfying the safety and reliability criteria with a mean absolute relative difference of 10.3%. Three participants did not fulfill the criteria, mainly because the frequency of SMBG did not meet the requirements. Dexcom G6 CGM is safe and accurate in the real-world setting for use in pregnant women with preexisting T1D with reduced SMBG testing as part of a pregnancy-specific AID system.

Reducing Inequity in the Use of Automated Insulin Delivery Systems by Adults With Type 1 Diabetes: Key Learnings From a Safety Net Diabetes Clinic Program

BackgroundRecent advancements in diabetes technology have significantly improved Type 1 diabetes (T1D) management, but disparities persist, particularly in the adoption of automated insulin delivery (AID) systems within minoritized communities. We aimed to improve patient access to AID system training and overcome clinical inertia to referral. MethodsWe report on a transformative program implemented at Boston Medical Center, the largest safety-net hospital in New England, aimed at reducing disparities in AID system utilization. We employed a multidisciplinary team and quality improvement principles to identify barriers and develop solutions. Strategies included increasing access to diabetes educators, creating a referral system, and developing telemedicine education classes. We also made efforts to raise clinician awareness and confidence in recommending AID therapy. ResultsAt baseline, 13.5% of our clinic T1D population was using an insulin pump. The population referred included 97 people with T1D (49% female, mean A1c 8.7%, 68% public insurance beneficiaries, 25% Hispanic and 25% non-Hispanic Black). Results from the first year showed a 166% increase in AID system use rates, with 64% of referred patients starting on AID. Notably, 78% of patients with A1c >8.5% adopted AID systems, addressing a gap in representation observed in clinical efficacy trials. The initiative successfully narrowed disparities in AID use among minoritized populations. ConclusionsThe program's success among minoritized patients underscores the significance of tailored, collaborative, team-based care and targeted educational initiatives. Our experience provides a foundation for future efforts to ensure equitable access to diabetes technologies, emphasizing the potential of local quality improvement interventions.

Automated Insulin Delivery in Women With Pregnancy Complicated by Type 1 Diabetes

(Abstracted from N Engl J Med 2023;389:1566–1578 Hyperglycemia during pregnancy is an important risk factor for complications, such as preterm birth, large birth weight, and admission to the intensive care unit. Those at highest risk already have glycated hemoglobin above target levels at the start of pregnancy.

Comparative Effectiveness of Hybrid Closed-Loop Automated Insulin Delivery Systems Among Patients with Type 1 Diabetes.

Clinical trials have demonstrated the efficacy and safety of hybrid closed-loop (HCL) systems, yet few studies have compared outcomes in the real-world setting. This retrospective study analyzed patients from an academic endocrinology practice between January 1, 2018, and November 18, 2022. The inclusion criteria were diagnosis code for type I diabetes (T1D), >18 years of age, new to any HCL system [Medtronic 670G/770G (MT), Tandem Control IQ (CIQ), or Omnipod 5 (OP5)], and availability of a pump download within three months. The outcomes included %time in range (TIR) of 70 to 180 mg/dL, %time below range (TBR) <70 mg/dL at 90 days, and HbA1c for 91 to 180 days. Of the 176 participants, 47 were MT, 74 CIQ, and 55 OP5. Median (25%, 75%) change in HbA1c was -0.1 (-0.8, 0.3), -0.6 (-1.1, -0.15), and -0.55 (-0.98, 0)% for MT, CIQ, and OP5, respectively, (P = .04). TIR was 70 (57, 76), 67 (59, 75), and 68 (60, 76)% (P = .95) at 90 days while TBR was 2 (1, 3), 1 (0, 2), and 1 (0, 1)%, respectively, (P = .002). The %time in automated delivery was associated with TIR and change in HbA1c. After controlling other factors including %time in automated delivery, HCL type was not an independent predictor of change in HbA1c nor TIR but remained a significant predictor of TBR. There were significant reductions in HbA1c in CIQ and OP5. TIR was similar across pumps, but TBR was highest with MT. The %time in automated delivery likely explains differences in change in HbA1c but not TBR between HCL systems.

Prevalence, Safety, and Metabolic Control Among Danish Children and Adolescents with Type 1 Diabetes Using Open-Source Automated Insulin Delivery Systems.

Background: Treatment of type 1 diabetes mellitus (T1DM) has become increasingly technical with rapid developments in integration of pumps and sensors to regulate insulin dosage, and patient-initiated solutions as open-source automated insulin delivery (OS-AID) systems, have gained popularity in people with diabetes. Studies have shown increased glycemic control and mental wellbeing in users of OS-AID systems. The aim of this study was to estimate the prevalence, the effect on metabolic control, the risk, and the effect on everyday life for users and their parents of OS-AID systems in Danish children and adolescents with T1DM. Methods: This retrospective cohort study recruited participants through pediatric diabetes outpatient clinics and social media. Surveys were distributed and current and retrospective data on glycemic control (HbA1c, time in range [TIR] etc.) were collected. Results: Fifty-six users of OS-AID systems out of 2950 Danish children and adolescents with T1DM were identified from all outpatient clinics in Denmark. Thirty-one responded on contact and were included (55% of the identified), median age 12 [interquartile range: 11-14] years, 51% females, and mean duration of use of OS-AID systems 2.37 ± 0.86 years. Glycemic control increased significantly with TIR increasing from mean 62.29% ± 13.68% to 70.12% ± 10.08%, *P < 0.01, and HbA1c decreasing from mean 50.13 ± 5.76 mmol/mol (6.7% ± 2.7%) to 47.86 ± 6.24 mmol/mol (6.5% ± 2.7%), **P < 0.05. No changes were found in safety parameters. Parents reported better quality of sleep evaluated by Pittsburgh Sleep Quality Index. Conclusion: This study is the first to provide knowledge on pediatric users of OS-AID systems in Denmark and found a prevalence of 1.89% for OS-AID systems, improved TIR, and no increased risk associated with use of OS-AID systems.

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

To investigate whether the positive effects on glycaemic outcomes of 3-month automated insulin delivery (AID) achieved in 2- to 6-year-old children endure over an extended duration and how AID treatment affects time in tight range (TITR), defined as 3.9-7.8 mmol/L. We analysed 18 months of follow-up data from a non-randomized, prospective, single-arm clinical trial (n = 35) conducted between 2021 and 2023. The main outcome measures were changes in time in range (TIR), glycated haemoglobin (HbA1c), time above range (TAR), TITR, and mean sensor glucose (SG) value during follow-up visits (at 0, 6, 12 and 18 months). The MiniMed 780G AID system in SmartGuard Mode was used for 18 months. Parental diabetes distress was evaluated at 3 and 18 months with the validated Problem Areas in Diabetes-Parent, revised (PAID-PR) survey. Between 0 and 6 months, TIR and TITR increased, and HbA1c, mean SG value and TAR decreased significantly (p < 0.001); the favourable effect persisted through 18 months of follow-up. Between 3 and 18 months, PAID-PR score declined significantly (0 months: mean score 37.5; 3 months: mean score 28.6 [p = 0.06]; 18 months: mean score 24.6 [p < 0.001]). Treatment with AID significantly increased TITR and TIR in young children. The positive effect of AID on glycaemic control observed after 6 months persisted throughout the 18 months of follow-up. Similarly, parental diabetes distress remained reduced during 18 months follow-up. These findings are reassuring and suggest that AID treatment improves glycaemic control and reduces parental diabetes distress in young children over an extended 18-month follow-up.

Characteristics Associated With Elevated Time Below Range in Elderly Patients With Type 1 Diabetes Using an Automated Insulin Delivery System.

This study investigated the characteristics associated with an increased risk of hypoglycemia, in elderly patients with type 1 diabetes mellitus (T1D) using automated insulin delivery (AID) systems. Cross-sectional observational study including patients >60 years, using sensor-augmented insulin pump therapy with predictive low-glucose management (SAPT-PLGM), hybrid closed-loop (HCL), and advanced hybrid closed-loop (AHCL), for more than three months. A geriatric assessment was performed, and body composition was determined to investigate its association with achieving time below range (TBR) <70 mg/dL goals. The study included 59 patients (47.5% of men, mean age of 67.6 years, glycated hemoglobin [HbA1c] of 7.5 ± 0.6%, time in range (TIR) 77.8 ± 9.9%). Time below range <70 and <54 mg/dL were 2.2 ± 2.3% and 0.4 ± 0.81%, respectively. Patients with elevated TBR <70 mg/dL (>1%) had higher HbA1c levels, lower TIR, elevated time above range (TAR), and high glycemic variability. Regarding body composition, greater muscle mass, grip strength, and visceral fat were associated with a lower TBR <70 mg/dL. These factors were independent of the type of technology used, but TIR was higher when using AHCL systems compared with SAPT-PLGM and HCL systems. In elderly patients treated with AID systems with good functional status, lower lean mass, lower grip strength, and lower visceral fat percentage were associated with TBR greater than 1%, regardless of the device used. A similar finding along was found with CGM indicators such as higher HbA1c levels, lower TIR, higher TAR, and higher CV. Geriatric assessment is crucial for personalizing patient management.

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

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. 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. 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. 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.

Cost-Effectiveness of Closed-Loop Automated Insulin Delivery Using the Cambridge Hybrid Algorithm in Children and Adolescents with Type 1 Diabetes: Results from a Multicenter 6-Month Randomized Trial.

The main objective of this study is to evaluate the incremental cost-effectiveness (ICER) of the Cambridge hybrid closed-loop automated insulin delivery (AID) algorithm versus usual care for children and adolescents with type 1 diabetes (T1D). This multicenter, binational, parallel-controlled trial randomized 133 insulin pump using participants aged 6 to 18 years to either AID (n = 65) or usual care (n = 68) for 6 months. Both within-trial and lifetime cost-effectiveness were analyzed. Analysis focused on the treatment subgroup (n = 21) who received the much more reliable CamAPS FX hardware iteration and their contemporaneous control group (n = 24). Lifetime complications and costs were simulated via an updated Sheffield T1D policy model. Within-trial, both groups had indistinguishable and statistically unchanged health-related quality of life, and statistically similar hypoglycemia, severe hypoglycemia, and diabetic ketoacidosis (DKA) event rates. Total health care utilization was higher in the treatment group. Both the overall treatment group and CamAPS FX subgroup exhibited improved HbA1C (-0.32%, 95% CI: -0.59 to -0.04; P = .02, and -1.05%, 95% CI: -1.43 to -0.67; P < .001, respectively). Modeling projected increased expected lifespan of 5.36 years and discounted quality-adjusted life years (QALYs) of 1.16 (U.K. tariffs) and 1.52 (U.S. tariffs) in the CamAPS FX subgroup. Estimated ICERs for the subgroup were £19 324/QALY (United Kingdom) and -$3917/QALY (United States). For subgroup patients already using continuous glucose monitors (CGM), ICERs were £10 096/QALY (United Kingdom) and -$33 616/QALY (United States). Probabilistic sensitivity analysis generated mean ICERs of £19 342/QALY (95% CI: £15 903/QALY to £22 929/QALY) (United Kingdom) and -$28 283/QALY (95% CI: -$59 607/QALY to $1858/QALY) (United States). For children and adolescents with T1D on insulin pump therapy, AID using the Cambridge algorithm appears cost-effective below a £20 000/QALY threshold (United Kingdom) and cost saving (United States).

Glucometrics and device satisfaction in children and adolescents with type 1 diabetes using different treatment modalities: A multicenter real-world observational study

AimsTo analyze metabolic outcomes, diabetes impact and device satisfaction in children and adolescents with type 1 diabetes in Italy who used different treatment modalities for diabetes care in a real-life context. MethodsIn this multicenter, nationwide, cross-sectional study, 1464 participants were enrolled at a routine visit. The following treatment modalities were considered MDI + SMBG; MDI + CGM; Sensor Augmented Pump Therapy; predictive management of low glucose; Hybrid Closed Loop (HCL); Advanced Hybrid Closed Loop (AHCL). Health related quality of life was evaluated by the Italian version of the Diabetes Impact and Device Satisfaction Scale (DIDS) questionnaire. ResultsPatients treated with AID systems were more likely to have HbA1c ≤ 6.5 %, higher percentage of time with glucose levels between 70 and 180 mg/dL, lower percentage of time with glucose levels above 180 mg/dL, higher device satisfaction, and reduced impact of diabetes. All the therapeutic modalities with respect to MDI + CGM, except for MDI + SMBG, contributed to increase the device satisfaction. HCL and AHCL respect to MDI + CGM were associated with lower diabetes impact. ConclusionReal-life use of automated insulin delivery systems is associated with reduced type 1 diabetes impact, increased device satisfaction, and achievement of glycemic goals.