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Background: A closed‐loop bedside‐type artificial pancreas for perioperative glucose control has previously been introduced. However, artificial pancreas therapy was often interrupted due to continuous blood sampling failure. We developed an interprofessional work manual to reduce the interruption time of artificial pancreatic therapy for perioperative blood glucose control due to continuous blood sampling failure. This study aimed to investigate the usefulness of this manual. Methods: The manual consisted of the following sections: (1) the roles of the professionals in the preparation and management of the artificial pancreas, (2) how to address continuous blood sampling failure, and (3) checkpoints for interprofessional transfer of the artificial pancreas. We compared the results before the introduction of the manual and 2 years after the introduction of the manual. Results: There were 35 and 37 patients in the Before and After groups, respectively. There were no significant differences in patient backgrounds between the two groups, although there was significantly less blood loss in the After group (1164 vs. 366 mL; p < 0.001). The mean artificial pancreas therapy and artificial pancreas therapy interruption times were 847 min and 20 min, respectively. Artificial pancreas therapy interruption time (34 vs. 8 min; p = 0.078) and time per interruption (24 vs. 4 min; p < 0.001) were significantly shorter in the After group than in the Before group. Conclusions: The interprofessional working manual was useful in reducing the artificial pancreatic therapy interruption time for perioperative glucose control. [ABSTRACT FROM AUTHOR]

AbstractThe management of diabetes mellitus has undergone remarkable progress with the introduction of cutting-edge technologies in glucose monitoring and artificial pancreas systems. These innovations have revolutionized diabetes care, offering patients more precise, convenient, and personalized management solutions that significantly improve their quality of life. This review aims to provide a comprehensive overview of recent technological advancements in glucose monitoring devices and artificial pancreas systems, focusing on their transformative impact on diabetes care.A detailed review of the literature was conducted to examine the evolution of glucose monitoring technologies, from traditional invasive methods to more advanced systems. The review explores minimally invasive techniques such as continuous glucose monitoring (CGM) systems and flash glucose monitoring (FGM) systems, which have already proven to enhance glycemic control and reduce the risk of hypoglycemia. In addition, emerging non-invasive glucose monitoring technologies, including optical, electrochemical, and electro-mechanical methods, were evaluated. These techniques are paving the way for more patient-friendly options that eliminate the need for frequent finger-prick tests, thereby improving adherence and ease of use.Advancements in closed-loop artificial pancreas systems, which integrate CGM with automated insulin delivery, were also examined. These systems, often referred to as “hybrid closed-loop” or “automated insulin delivery” systems, represent a significant leap forward in diabetes care by automating the process of insulin dosing. Such advancements aim to mimic the natural function of the pancreas, allowing for better glucose regulation without the constant need for manual interventions by the patient.Technological breakthroughs in glucose monitoring and artificial pancreas systems have had a profound impact on diabetes management, providing patients with more accurate, reliable, and individualized treatment options. These innovations hold the potential to significantly improve glycemic control, reduce the incidence of diabetes-related complications, and ultimately enhance the quality of life for individuals living with diabetes. Researchers are continually exploring novel methods to measure glucose more effectively and with greater convenience, further refining the future of diabetes care. Researchers are also investigating the integration of artificial intelligence and machine learning algorithms to further enhance the precision and predictive capabilities of glucose monitoring and insulin delivery systems. With ongoing advancements in sensor technology, connectivity, and data analytics, the future of diabetes care promises to deliver even more seamless, real-time management, empowering patients with greater autonomy and improved health outcomes. [ABSTRACT FROM AUTHOR]

Background: Biomedical engineering, especially tissue engineering, is trying to provide an alternative solution to generate functional organs/tissues for use in various applications. These include beyond the final goal of transplantation, disease modeling and drug discovery as well. The aim of this study is to comprehensively review the existing literature on hydrogel-based vascularized organ (i.e., liver, pancreas, kidneys, intestine, stomach and spleen) tissue engineering of the abdominal organs. Methods: A comprehensive literature search was conducted on the Scopus database (latest search 1 September 2024). The research studies including hydrogel-based vascularized organ tissue engineering in the organs examined here were eligible for the review. Results: Herein, 18 studies were included. Specifically, 10 studies included the liver or hepatic tissue, 5 studies included the pancreas or pancreatic islet tissue, 3 studies included the kidney or renal tissue, 1 study included the intestine or intestinal or bowel tissue, 1 study included the stomach or gastric tissue, and 0 studies included spleen tissue. Conclusion: Hydrogels are biocompatible materials with ideal characteristics for use as scaffolds. Even though organ tissue engineering is a rapidly growing field, there are still many obstacles to overcome to create a fully functional and long-lasting organ. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Context We propose an artificial-pancreas-like algorithm (AP-A) that could automatically determine the preprandial insulin dose based on intermittently scanned continuous glucose monitoring (isCGM) data trajectories in multiple dose injection (MDI) therapy. Objective We aim to determine whether preprandial insulin dose adjustments guided by the AP-A are as effective and safe as physician decisions. Methods We performed a randomized, single-blind, clinical trial at a tertiary, referral hospital in Beijing, China. Type 2 diabetes participants were eligible if they were aged 18 years or older, with a glycated hemoglobin A1c of 8.0% or higher. Eligible participants were randomly assigned (1:1) to the AP-A arm supervised by physician and the conventional physician treatment arm. The primary objective was to compare percentage time spent with sensor glucose level in 3.9 to 10.0 mmol/L (TIR) between the 2 study arms. Safety was assessed by the percentage time spent with sensor glucose level below 3.0 mmol/L (TBR). Results A total of 140 participants were screened, of whom 119 were randomly assigned to the AP-A arm (n = 59) or physician arm (n = 60). The TIR achieved by the AP-A arm was statistically noninferior compared with the control arm (72.4% [63.3%-82.1%] vs 71.2% [54.9%-81.4%]), with a median difference of 1.33% (95% CI, −6.00 to 10.94, noninferiority margin −7.5%). TBR was also statistically noninferior between the AP-A and control arms (0.0% [0.0%-0.0%] vs 0.0% [0.0%-0.0%]), respectively; median difference (95% CI, 0.00% [0.00%-0.00%], noninferiority margin 2.0%). Conclusion The AP-A–supported physician titration of preprandial insulin dosage offers noninferior glycemic control compared with optimal physician care in type 2 diabetes. [ABSTRACT FROM AUTHOR]

Background Diabetes technology, especially advanced hybrid closed-loop (AHCL) systems, is rapidly advancing, offering improved glycemic control, reduced hypoglycemia, and reduced treatment burden for patients with type 1 diabetes (T1D). This study aimed to evaluate the clinical efficiency of an AHCL system—the Medtronic MiniMed 780G insulin pump combined with continuous glucose monitoring—among individuals with T1D in real-world clinical settings. Methods In an observational retrospective study, we identified a cohort of 41 patients (mean age, 47.1 ± 13.7 years; T1D duration, 23.6 ± 13 years; 73.2% female) previously using an insulin pump or those on multiple daily insulin injections, currently using the AHCL system for at least 6 months. Primary outcomes were the changes of the following parameters, before AHCL initiation and at 6 months after treatment; (1) time in range (TIR): time with glucose levels in the range of 70 to 180 mg/dL, (2) time below range (TBR): time with glucose levels below 70 mg/dL, and (3) time above range (TAR): time with glucose levels above 180 mg/dL. Results Data analysis from 41 patients showed a significant 16.5% ± 13.8% increase in TIR (from 56.6 ± 17.9 to 73.1 ± 10.6%, p < 0.001). Both TBR and TAR decreased by 2.9 ± 4.8% (p = 0.004) and 13.6 ± 16.4% (p < 0.001), respectively. Mean glucose concentration, coefficient of variation, and glucose management indicator significantly improved. Conclusion The AHCL system effectively improved glucose control regarding TIR, TBR, and TAR. Enhanced glycemic control metrics highlight the potential for wider adoption of AHCL technology. [ABSTRACT FROM AUTHOR]

A 72-year-old female with type 1 diabetes, a history of interstitial pneumonia, and diabetic ketoacidosis was admitted to our hospital with dysphagia. Endoscopy revealed a circumferential neoplastic lesion in the upper to middle esophagus, and a biopsy revealed squamous cell carcinoma. Computed tomography revealed invasion of the left main bronchus, and induction chemotherapy was initiated with a diagnosis of unresectable locally advanced esophageal cancer. After one course of induction chemotherapy, the tumor size reduced, bronchial invasion improved, and thoracoscopic esophagectomy was performed. During surgery and until 3 days after surgery, the patient's blood glucose level was controlled using an artificial pancreas, and the target blood glucose range was set at 140–180 mg/dL. On the fourth postoperative day, the patient was managed using a sliding scale. Mean blood glucose was 186.7 ± 70.0 mg/dL for 3 days before surgery, 190.5 ± 25.0 mg/dL during artificial pancreas therapy from the surgery to the next day, 169.8 ± 22.0 mg/dL during artificial pancreas therapy on the second to third postoperative days, and 174.5 ± 25.0 mg/dL during sliding scale therapy for 4–15 days after surgery. No hypoglycemia or ketoacidosis was noted. [ABSTRACT FROM AUTHOR]

Abstract In hybrid automatic insulin delivery (HAID) systems, meal disturbance is compensated by feedforward control, which requires the announcement of the meal by the patient with type 1 diabetes (DM1) to achieve the desired glycemic control performance. The calculation of insulin bolus in the HAID system is based on the amount of carbohydrates (CHO) in the meal and patient-specific parameters, i.e. carbohydrate-to-insulin ratio (CR) and insulin sensitivity-related correction factor (CF). The estimation of CHO in a meal is prone to errors and is burdensome for patients. This study proposes a fully automatic insulin delivery (FAID) system that eliminates patient intervention by compensating for unannounced meals. This study exploits the deep reinforcement learning (DRL) algorithm to calculate insulin bolus for unannounced meals without utilizing the information on CHO content. The DRL bolus calculator is integrated with a closed-loop controller and a meal detector (both previously developed by our group) to implement the FAID system. An adult cohort of 68 virtual patients based on the modified UVa/Padova simulator was used for in-silico trials. The percentage of the overall duration spent in the target range of 70–180 mg/dL was $$71.2\%$$ 71.2 % and $$76.2\%$$ 76.2 % , $$180$$ > 180 mg/dL was $$26.7\%$$ 26.7 % and $$21.1\%$$ 21.1 % , respectively, for the FAID system and HAID system utilizing a standard bolus calculator (SBC) including CHO misestimation. The proposed algorithm can be exploited to realize FAID systems in the future.

Background: The Omnipod® 5 Automated Insulin Delivery System was associated with favorable glycemic outcomes for people with type 1 diabetes (T1D) in two pivotal clinical trials. Real-world evidence is needed to explore effectiveness in nonstudy conditions. Methods: A retrospective analysis of the United States Omnipod 5 System users (aged ≥2 years) with T1D and sufficient data (≥90 days of data; ≥75% of days with ≥220 continuous glucose monitor readings/day) available in Insulet Corporation's device and person-reported datasets as of July 2023 was performed. Target glucose setting usage (i.e., 110–150 mg/dL in 10 mg/dL increments) was summarized and glycemic outcomes were examined. Subgroup analyses of those using the lowest average glucose target (110 mg/dL) and stratification by baseline characteristics (e.g., age, prior therapy, health insurance coverage) were conducted. Results: In total, 69,902 users were included. Multiple and higher glucose targets were more commonly used in younger age groups. Median percentage of time in range (TIR; 70–180 mg/dL) was 68.8%, 61.3%, and 53.6% for users with average glucose targets of 110, 120, and 130–150 mg/dL, respectively, with minimal time <70 mg/dL (all median <1.13%). Among those with an average glucose target of 110 mg/dL (n = 37,640), median TIR was 65.0% in children and adolescents (2–17 years) and 69.9% in adults (≥18 years). Subgroup analyses of users transitioning from Omnipod DASH or multiple daily injections and of Medicaid/Medicare users demonstrated favorable glycemic outcomes among these groups. Conclusion: These glycemic outcomes from a large and diverse sample of nearly 70,000 children and adults demonstrate effective use of the Omnipod 5 System under real-world conditions. [ABSTRACT FROM AUTHOR]

Three manufacturers sell artificial pancreas systems in the United States for management of Type 1 Diabetes. Given the life-saving task required of an artificial pancreas there needs to be a high level of trust and safety in the devices. This evaluation sought to find the adjusted safety event reporting rate and themes along with device-associated risk in events reported utilizing the MAUDE database. We searched device names in the MAUDE database over the period from 2016 until August 2023 (the date of retrieval). Thematic analysis was performed using dual-reviewer examination with a 96% concurrence. Relative risk (RR) was calculated for injury, malfunction, and overall, for each manufacturer, as well as adjusted event rate per manufacturer. Most events reported related to defects in the manufacturing of the casing materials which resulted in non-delivery of therapy. Tandem Diabetes Care, Inc. had an adjusted event rate of 50 per 100,000 units and RR of 0.0225. Insulet had an adjusted event rate of 300 per 100,000 units and RR of 0.1684. Medtronic has an adjusted event rate of 2771.43 per 100,000 units and RR of 20.7857. The newer Medtronic devices show improvements in likely event rate. While the artificial pancreas is still in its infancy, these event rates are not at an acceptable level for a device which can precipitate death from malfunctions. Further exploration into safety events and much more research and development is needed for devices to reduce the event rates. Improved manufacturing practices, especially the casing materials, are highly recommended. The artificial pancreas holds promise for millions but must be improved before it becomes a true life-saving device that it has the potential to become. [ABSTRACT FROM AUTHOR]

In hybrid automatic insulin delivery (HAID) systems, meal disturbance is compensated by feedforward control, which requires the announcement of the meal by the patient with type 1 diabetes (DM1) to achieve the desired glycemic control performance. The calculation of insulin bolus in the HAID system is based on the amount of carbohydrates (CHO) in the meal and patient-specific parameters, i.e. carbohydrate-to-insulin ratio (CR) and insulin sensitivity-related correction factor (CF). The estimation of CHO in a meal is prone to errors and is burdensome for patients. This study proposes a fully automatic insulin delivery (FAID) system that eliminates patient intervention by compensating for unannounced meals. This study exploits the deep reinforcement learning (DRL) algorithm to calculate insulin bolus for unannounced meals without utilizing the information on CHO content. The DRL bolus calculator is integrated with a closed-loop controller and a meal detector (both previously developed by our group) to implement the FAID system. An adult cohort of 68 virtual patients based on the modified UVa/Padova simulator was used for in-silico trials. The percentage of the overall duration spent in the target range of 70–180 mg/dL was 71.2 % and 76.2 % , < 70 mg/dL was 0.9 % and 0.1 % , and > 180 mg/dL was 26.7 % and 21.1 % , respectively, for the FAID system and HAID system utilizing a standard bolus calculator (SBC) including CHO misestimation. The proposed algorithm can be exploited to realize FAID systems in the future. [ABSTRACT FROM AUTHOR]

Aims/hypothesis: 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). Methods: 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. Results: 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. Conclusions/interpretation: 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. Trial registration: 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). [ABSTRACT FROM AUTHOR]

Background: To evaluate the long-term safety and effectiveness of the Omnipod® 5 Automated Insulin Delivery (AID) System in very young children with type 1 diabetes with up to 2 years of use. Methods: Following a 13-week single-arm, multicenter, pivotal trial that took place after 14 days of standard therapy data collection, participating children (2–5.9 years of age at study enrollment) were provided the option to continue use of the AID system in an extension phase. HbA1c was measured every 3 months, up to 15 months of total use, and continuous glucose monitor metrics were collected through the completion of the extension study (for up to 2 years). Results: Participants (N = 80) completed 18.2 [17.4, 23.4] (median [interquartile range]) total months of AID, inclusive of the 3-month pivotal trial. During the pivotal trial, HbA1c decreased from 7.4% ± 1.0% (57 ± 10.9 mmol/mol) to 6.9% ± 0.7% (52 ± 7.7 mmol/mol, P < 0.0001) and was maintained at 7.0% ± 0.7% (53 ± 7.7 mmol/mol) after 15 months total use (P < 0.0001 from baseline). Time in target range (70–180 mg/dL) increased from 57.2% ± 15.3% during standard therapy to 68.1% ± 9.0% during the pivotal trial (P < 0.0001) and was maintained at 67.2% ± 9.3% during the extension phase (P < 0.0001 from standard therapy). Participants spent a median 97.1% of time in Automated Mode during the extension phase, with one episode of severe hypoglycemia and one episode of diabetic ketoacidosis. Conclusion: This evaluation of the Omnipod 5 AID System indicates that long-term use can safely maintain improvements in glycemic outcomes with up to 2 years of use in very young children with type 1 diabetes. Clinical Trials Registration Number: NCT04476472 [ABSTRACT FROM AUTHOR]

The scientific diagnosis and treatment of patients with diabetes require frequent blood glucose testing and insulin delivery to normoglycemia. Therefore, an artificial pancreas with a continuous blood glucose (BG) monitoring function is an urgent research target in the medical industry. The problem of closed-loop algorithmic control of the BG with a time delay is a key and difficult issue that needs to be overcome in the development of an artificial pancreas. Firstly, the composition, structure, and control characteristics of the artificial pancreas are introduced. Subsequently, the research progress of artificial pancreas control algorithms is reviewed, and the characteristics, advantages, and disadvantages of proportional-integral-differential control, model predictive control, and artificial intelligence control are compared and analyzed to determine whether they are suitable for the practical application of the artificial pancreas. Additionally, key advancements in areas such as blood glucose data monitoring, adaptive models, wearable devices, and fully automated artificial pancreas systems are also reviewed. Finally, this review highlights that meal prediction, control safety, integration, streamlining the optimization of control algorithms, constant temperature preservation of insulin, and dual-hormone artificial pancreas are issues that require further attention in the future. An Excellent Diabetes Treatment: Insulin Pump System [ABSTRACT FROM AUTHOR]

Abstract Background Type 1 diabetes (T1D) is an autoimmune disease leading to destruction of insulin-producing pancreatic beta cells. Both genetic and environmental factors contribute to pathogenesis. The incidence of T1D is increasing worldwide, with significant geographic and ethnic variations. Patients present with symptoms of hyperglycemia and diabetes complications. Main body In T1D, autoreactive T cells and autoantibodies destroy beta cells, causing insulin deficiency. Exogenous insulin therapy is essential but cannot replicate normal physiology. Management requires intensive lifestyle education on diet, exercise, glucose monitoring and avoiding complications, in addition to insulin. Novel therapies like immunotherapy, cell transplantation, artificial pancreas devices and AI algorithms aim to improve care. Strategies for reversing T1D involve combination immunotherapies to block autoimmunity and regenerate beta cells via stem cells or xenotransplantation. Conclusion While type 1 diabetes remains challenging, ongoing research provides hope. Elucidating individualized disease mechanisms and translating findings into precision prevention and treatment approaches are critical to improving long-term outcomes. Innovative and multi-targeted therapies may fundamentally change the trajectory of T1D.

Abstract Purposes Subtotal esophagectomy for esophageal cancer (EC) is associated with high morbidity rates. Tight glycemic control using an artificial pancreas (AP) is one of the promising strategies to reduce postoperative inflammation and morbidities. However, the effects of tight glycemic control using AP in patients with EC are yet to be fully elucidated. Method This study reviewed 96 patients with EC who underwent subtotal esophagectomy. The postoperative inflammation parameters and morbidity rates were compared between patients who used the AP (n = 27) or not (control group, n = 69). AP is a closed-loop system that comprises a continuous glucose monitor and an insulin pump. Results The numbers of white blood cells (WBC) and Neutrophils (Neut) were noted to be lower in the AP group than in the control group, but with no significant difference. The ratio in which the number of WBC, Neut, and CRP on each postoperative day (POD) was divided by those tested preoperatively was used to standardize the results. The ratio of WBC and Neut on 1POD was significantly lower in the AP group than in the control group. The rate of surgical site infection was lower in the AP group than in the control group. Conclusion AP significantly decreased WBC and Neut on 1POD; this suggests the beneficial effects of AP in alleviating postoperative inflammation.

Purpose: Advanced hybrid closed loop (AHCL) systems have the potential to improve glycemia and reduce burden for people with type 1 diabetes (T1D). Children and youth, who are at particular risk for out-of-target glycemia, may have the most to gain from AHCL. However, no randomized controlled trial (RCT) specifically targeting this age group with very high HbA1c has previously been attempted. Therefore, the CO-PILOT trial (Closed lOoP In chiLdren and yOuth with Type 1 diabetes and high-risk glycemic control) aims to evaluate the efficacy and safety of AHCL in this group. Methods: A prospective, multicenter, parallel-group, open-label RCT, comparing MiniMed™ 780G AHCL to standard care (multiple daily injections or continuous subcutaneous insulin infusion). Eighty participants aged 7–25 years with T1D, a current HbA1c ≥ 8.5% (69 mmol/mol), and naïve to automated insulin delivery will be randomly allocated to AHCL or control (standard care) for 13 weeks. The primary outcome is change in HbA1c between baseline and 13 weeks. Secondary outcomes include standard continuous glucose monitor glycemic metrics, psychosocial factors, sleep, platform performance, safety, and user experience. This RCT will be followed by a continuation phase where the control arm crosses over to AHCL and all participants use AHCL for a further 39 weeks to assess longer term outcomes. Conclusion: This study will evaluate the efficacy and safety of AHCL in this population and has the potential to demonstrate that AHCL is the gold standard for children and youth with T1D experiencing out-of-target glucose control and considerable diabetes burden. Trial registration: This trial was prospectively registered with the Australian New Zealand Clinical Trials Registry on 14 November 2022 (ACTRN12622001454763) and the World Health Organization International Clinical Trials Registry Platform (Universal Trial Number U1111-1284-8452). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Type 1 diabetes (T1D) is an autoimmune disease leading to destruction of insulin-producing pancreatic beta cells. Both genetic and environmental factors contribute to pathogenesis. The incidence of T1D is increasing worldwide, with significant geographic and ethnic variations. Patients present with symptoms of hyperglycemia and diabetes complications. Main body: In T1D, autoreactive T cells and autoantibodies destroy beta cells, causing insulin deficiency. Exogenous insulin therapy is essential but cannot replicate normal physiology. Management requires intensive lifestyle education on diet, exercise, glucose monitoring and avoiding complications, in addition to insulin. Novel therapies like immunotherapy, cell transplantation, artificial pancreas devices and AI algorithms aim to improve care. Strategies for reversing T1D involve combination immunotherapies to block autoimmunity and regenerate beta cells via stem cells or xenotransplantation. Conclusion: While type 1 diabetes remains challenging, ongoing research provides hope. Elucidating individualized disease mechanisms and translating findings into precision prevention and treatment approaches are critical to improving long-term outcomes. Innovative and multi-targeted therapies may fundamentally change the trajectory of T1D. [ABSTRACT FROM AUTHOR]

Background: Silicon nanopore membrane‐based implantable bioartificial organs are dependent on arteriovenous implantation of a mechanically robust and biocompatible hemofilter. The hemofilter acts as a low‐resistance, high‐flow network, with blood flow physiology similar to arteriovenous shunts commonly created for hemodialysis access. A mock circulatory loop (MCL) that mimics shunt physiology is an essential tool for refinement and durability testing of arteriovenous implantable bioartificial organs and silicon blood‐interfacing membranes. We sought to develop a compact and cost‐effective MCL to replicate flow conditions through an arteriovenous shunt and used data from the MCL and swine to inform a bond graph mathematical model of the physical setup. Methods: Flow physiology through bioartificial organ prototypes was obtained in the MCL and during extracorporeal attachment to swine for biologic comparison. The MCL was tested for stability overtime by measuring pressurewave variability over a 48‐h period. Data obtained in vitro and extracorporeally informed creation of a bond graph model of the MCL. Results: The arteriovenous MCL was a cost‐effective, portable system that reproduced flow rates and pressures consistent with a pulsatile arteriovenous shunt as measured in swine. MCL performance was stable over prolonged use, providing a cost‐effective simulator for enhanced testing of peripherally implanted bioartificial organ prototypes. The corresponding bond graph model recapitulates MCL and animal physiology, offering a tool for further refinement of the MCL system. [ABSTRACT FROM AUTHOR]

This technical note is concerned with the event-triggered H∞ blood glucose regulation issue of type 1 diabetes by using networked artificial pancreas (AP). In order to improve the service life of AP, an integral-event-triggered scheme (IETS) is presented to reduce the releasing rate of control signal and the updating times of insulin pump. Compared with the normal event-triggered scheme (ETS), the proposed scheme can generate a larger interevent time by utilizing the integration of the triggering condition in normal ETS. To maintain the blood glucose concentration (BGC) within standard range, the co-design conditions of triggering parameter and H∞ controller are derived by linear matrix inequalities (LMIs). Finally, the validity of the developed strategy is verified through some simulation results. [ABSTRACT FROM AUTHOR]

This article provides an overview of the development and future of automated insulin delivery (AID) systems, which include insulin pumps, continuous glucose monitoring (CGM), and smart algorithms. It discusses the advancements in insulin pump technology, from the first portable pump in 1963 to the smaller, wearable pumps introduced in the 1980s and beyond. The article also explores the integration of CGM with insulin pumps and the introduction of AID systems that automatically deliver insulin based on real-time glucose data. It highlights specific AID systems, such as the MiniMed™ 670G and 780G, and the t:slim X2™ with Control-IQ technology. The document further provides an overview of various artificial pancreas systems for the management of type 1 diabetes (T1D), including the Tandem AHCL Control-IQ, OmniPod 5 HCL, Diabeloop generation 1, CamAPS FX, Tidepool Loop, and Beta Bionics iLet. It discusses the results of clinical trials and real-world data for these systems and addresses barriers to adoption, such as cost and user experience. The article concludes that the use of artificial pancreas systems improves glucose control and reduces the burden of diabetes, with the potential to prevent long-term complications. [Extracted from the article]

The MiniMed™ 780G system (780G) received Conformité Européenne mark in June 2020 and was, recently, approved by the U.S. Food and Drug Administration (April 2023). Clinical trials and real-world analyses have demonstrated MiniMed™ 780G system safety and effectiveness and that glycemic outcomes (i.e., time in range) improve with recommended settings use. In this publication, we will explain the iterative development of the 780G algorithm and how this technology has simplified diabetes management. [ABSTRACT FROM AUTHOR]

The presence of diabetic ketoacidosis (DKA) at diagnosis of type 1 diabetes (T1D) is associated with higher glycated hemoglobin levels over time. We evaluated whether hybrid-closed loop (HCL) therapy from onset of T1D could prevent the adverse impact of DKA at diagnosis on long-term glycemic outcomes. This was a posthoc analysis from 51 adolescents using HCL from diagnosis of T1D as part of the CLOuD trial (NCT02871089). We compared glycemic and insulin metrics between adolescents with (n = 17) and without (n = 34) DKA at diagnosis. Participants with and without DKA at diagnosis had similar time in target glucose range 3.9–10.0 mmol/L (70–180 mg/dL), time below range (<3.9 mmol/L, <70 mg/dL) and HbA1c at 6, 12, and 24 months. While insulin requirements at 6 months were higher in those with DKA at diagnosis, this was not statistically significant after adjusting for bodyweight. Residual C-peptide secretion was similar between groups. We conclude that HCL therapy may mitigate against the negative glycemic effects of DKA at T1D diagnosis. [ABSTRACT FROM AUTHOR]

Purposes: Subtotal esophagectomy for esophageal cancer (EC) is associated with high morbidity rates. Tight glycemic control using an artificial pancreas (AP) is one of the promising strategies to reduce postoperative inflammation and morbidities. However, the effects of tight glycemic control using AP in patients with EC are yet to be fully elucidated. Method: This study reviewed 96 patients with EC who underwent subtotal esophagectomy. The postoperative inflammation parameters and morbidity rates were compared between patients who used the AP (n = 27) or not (control group, n = 69). AP is a closed-loop system that comprises a continuous glucose monitor and an insulin pump. Results: The numbers of white blood cells (WBC) and Neutrophils (Neut) were noted to be lower in the AP group than in the control group, but with no significant difference. The ratio in which the number of WBC, Neut, and CRP on each postoperative day (POD) was divided by those tested preoperatively was used to standardize the results. The ratio of WBC and Neut on 1POD was significantly lower in the AP group than in the control group. The rate of surgical site infection was lower in the AP group than in the control group. Conclusion: AP significantly decreased WBC and Neut on 1POD; this suggests the beneficial effects of AP in alleviating postoperative inflammation. [ABSTRACT FROM AUTHOR]

Diabetic ketoacidosis (DKA) is a life-threatening complication of pediatric diabetes mellitus (DM). A bedside closed-loop artificial pancreas (AP) (STG-55; NIKKISO, Tokyo, Japan) maintains the blood glucose (BG) levels within the target range via automatic infusion of insulin and glucose. We report the application of the closed-loop AP to safely control the BG levels of a pediatric patient with DKA. A 12-year-old child with an unremarkable medical history presented with fever and restlessness. The patient was diagnosed with DKA secondary to fulminant type 1 DM and was treated with insulin infusion. He presented with Glasgow Coma Scale of E2V3M4. Arterial blood gas analysis revealed metabolic acidosis and BG levels of 489 mg/dL. His urine test was positive for ketones. Along with infusion therapy, automatic BG control using a closed-loop AP was initiated after ICU admission. This was adjusted to maintain BG levels within 100 mg/dL/6 h or less. After 24 h in the ICU, the patient regained consciousness and recovered from the metabolic acidosis. His general condition improved, and he was prescribed a diet treatment. The treatment was shifted to continuous insulin infusion, and he was transferred to the general ward, and was discharged on the 33rd day of hospitalization. The closed-loop AP prevented repetitive blood extractions, achieved prompt glycemic control, and prevented cerebral edema in a pediatric patient with DKA. This is the first report of successful treatment of DKA using a bedside closed-loop AP. [ABSTRACT FROM AUTHOR]

Background: Automated insulin delivery (AID) systems have proven effective in increasing time-in-range during both clinical trials and real-world use. Further improvements in outcomes for single-hormone (insulin only) AID may be limited by suboptimal insulin delivery settings. Methods: Adults (≥18 years of age) with type 1 diabetes were randomized to either sensor-augmented pump (SAP) (inclusive of predictive low-glucose suspend) or adaptive zone model predictive control AID for 13 weeks, then crossed over to the other arm. Each week, the AID insulin delivery settings were sequentially and automatically updated by an adaptation system running on the study phone. Primary outcome was sensor glucose time-in-range 70-180 mg/dL, with noninferiority in percent time below 54 mg/dL as a hierarchical outcome. Results: Thirty-five participants completed the trial (mean age 39 ± 16 years, HbA1c at enrollment 6.9% ± 1.0%). Mean time-in-range 70-180 mg/dL was 66% with SAP versus 69% with AID (mean adjusted difference +2% [95% confidence interval: -1% to +6%], P = 0.22). Median time

Diabetes is a metabolic disorder due to insufficient insulin synthesis or inadequate insulin sensitivity. The Bergman’s minimal model describes the dynamics of blood glucose levels in type 1 diabetics. The model has control inputs in the form of insulin injections and covers external disturbance factors in the form of meal disturbances. This research developed a control design using an sliding mode adaptive control to reduce blood glucose levels in hyperglycemic patients and keep it within normal glucose levels. Sliding mode adaptive control is an adaptive controller updates the model based on measured performance while in operation. A numerical simulation of the proposed controller is carried out by giving eating disorders three times, namely at breakfast, lunch, and dinner. Based on the numerical simulation, to lower the high blood glucose in the hyperglicemic patient, the insulin injection should be given starting at 30 minutes before breakfast for the next four hour, with a maximal dose of injection is 13 mU/min. It can decrease the high blood pressure until 54.83%.

Open source closed loop automated insulin delivery (CL-AID) systems are increasingly used in the treatment of diabetes. Not being officially approved, such systems are used by patients on their own initiative. Accordingly, the medical community has very little information about the treatment satisfaction and needs of patients that use these systems. We conducted an anonymous internet survey of Russian users of open source CL-AID systems. Ninety-five respondents reported using AndroidAPS (60%), FreeAPS X (16.6%), Loop (10.5%), FreeAPS (5.3%), OpenAPS (3.2%), and Omnia (2.1%). The duration of use of the systems ranged from 0.1 to 6 years (median 2.1 years). The mean HbA1c in users was 6.1% v.s. 7.3% on previous therapy. Most respondents reported an increase in Time in Range (88%), a decrease in the number of hypoglycemic episodes (73%), an improvement in the sleep quality (76%), general well-being (73%), social adaptation (56%) and self-confidence (69%), as well as a decrease in stress levels (56%) after switching to the systems. Ninety (94%) survey participants reported increase in the treatment satisfaction. The majority of respondents (68%) consider themselves advanced gadget users. However, 79% of them had technical difficulties when setting up the system for the first time, 46% had difficulty understanding the settings of the algorithm / program, and 35% spent a lot of effort studying the system. Support from the attending physician was reported by 27% of respondents, 35% noted the neutral attitude to the use of the system, and in 18% of cases the doctor was not aware of its use. All respondents, with the exception of two who found it difficult to answer, plan to continue using the system. Thus, from the patient's point of view, open source CL-AID systems have a positive effect on glycemic control and quality of life. The medical community should pay more attention to the needs of patients using these systems in treatment.

Background: The Omnipod® 5 Automated Insulin Delivery (AID) System was shown to be safe and effective following 3 months of use in people with type 1 diabetes (T1D); however, data on the durability of these results are limited. This study evaluated the long-term safety and effectiveness of Omnipod 5 use in people with T1D during up to 2 years of use. Materials and Methods: After a 3-month single-arm, multicenter, pivotal trial in children (6–13.9 years) and adolescents/adults (14–70 years), participants could continue system use in an extension phase. HbA1c was measured every 3 months for up to 15 months; continuous glucose monitor metrics were collected for up to 2 years. Results: Participants (N = 224) completed median (interquartile range) 22.3 (21.7, 22.7) months of AID. HbA1c was reduced in the pivotal trial from 7.7% ± 0.9% in children and 7.2% ± 0.9% in adolescents/adults to 7.0% ± 0.6% and 6.8% ± 0.7%, respectively, (P < 0.0001), and was maintained at 7.2% ± 0.7% and 6.9% ± 0.6% after 15 months (P < 0.0001 from baseline). Time in target range (70–180 mg/dL) increased from 52.4% ± 15.6% in children and 63.6% ± 16.5% in adolescents/adults at baseline to 67.9% ± 8.0% and 73.8% ± 10.8%, respectively, during the pivotal trial (P < 0.0001) and was maintained at 65.9% ± 8.9% and 72.9% ± 11.3% during the extension (P < 0.0001 from baseline). One episode of diabetic ketoacidosis and seven episodes of severe hypoglycemia occurred during the extension. Children and adolescents/adults spent median 96.1% and 96.3% of time in Automated Mode, respectively. Conclusion: Our study supports that long-term use of the Omnipod 5 AID System can safely maintain improvements in glycemic outcomes for up to 2 years of use in people with T1D. Clinical Trials Registration Number: NCT04196140 [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Evaluate the impact of the MiniMed™ 780G advanced hybrid closed-loop (AHCL) system on the glucose profile of pregnant women with type 1 diabetes (T1D) and maternal–neonatal complications. Methods: From April 2021 to September 2022, pregnant women with T1D treated with the AHCL system were included in an observational multicenter retrospective study. Continuous glucose monitoring parameters were analyzed monthly during pregnancy as well as maternal–neonatal complications. Results: Thirteen pregnant women, including a twin pregnancy (age: 33 ± 3 years, hemoglobin A1c [HbA1c]: 7.3% ± 0.7%, insulin doses: 0.72 ± 0.21 U/kg/day) were analyzed. At delivery, gestational age was 37 ± 2 weeks. During first 2 weeks of pregnancy, time in range (TIR, 63–140 mg/dL) was 46% (34–55) and increased to 54% (51–59) (P < 0.01), 64% (48–68) (P < 0.01), and 66% (60–70) (P < 0.001) during the first, second, and third trimester, respectively. During the night, TIR (63–140 mg/dL) was >70% throughout pregnancy. Time below the range <63 mg/dL increased from 0.5% (0–2) to 1.3% (0.7–2.2), 2% (1.2–3.5) (P < 0.05), and 1.3% (1.31–3) (P < 0.05) during the first, second, and third trimester, respectively. At delivery, insulin doses increased to 0.89 ± 0.35 IU/kg/day (P < 0.01), and HbA1c decreased to 6.4% ± 0.6% (P = 0.005). The reported carbohydrate amount increased from 167 ± 363 g/d during early pregnancy to 243 ± 106 g/d (P < 0.01) at delivery. The birthweight was 3134 ± 711 g, with 5/14 macrosomia and 2/14 neonatal hypoglycemia. Moreover, 5/13 patients had a preeclampsia and 9/13 a cesarean section, including three cases of scarred uterus. The Clinical Trial Registration number is: CE-2022-55. Conclusion: The AHCL system provided good glucose control during pregnancy and recommendation targets were reached during the nocturnal period only. The maternal and neonatal complications remained high. [ABSTRACT FROM AUTHOR]

Introduction: To evaluate hybrid closed-loop with ultra-rapid insulin lispro (Lyumjev) compared with hybrid closed-loop with standard insulin lispro in adults with type 1 diabetes. Materials and Methods: In a single-center, double-blind, randomized, crossover study, 28 adults with type 1 diabetes (mean ± standard deviation [SD]: age 44.5 ± 10.7 years, glycated hemoglobin (HbA1c) 7.1 ± 0.9% [54 ± 10 mmol/mol]) underwent two 8-week periods comparing hybrid closed-loop with ultra-rapid insulin lispro and hybrid closed-loop with standard insulin lispro in random order. The same CamAPS FX closed-loop algorithm was used in both periods. Results: In an intention-to-treat analysis, the proportion of time sensor glucose was in target range (3.9–10 mmol/L [70–180 mg/dL]; primary endpoint) was greater with ultra-rapid lispro compared with standard insulin lispro (mean ± SD: 78.7 ± 9.8% vs. 76.2 ± 9.6%; mean difference 2.5 percentage points [95% confidence interval 0.8 to 4.2]; P = 0.005). Mean sensor glucose was lower with ultra-rapid lispro compared with standard insulin lispro (7.9 ± 0.8 mmol/L [142 ± 14 mg/dL] vs. 8.1 ± 0.9 mmol/L [146 ± 16 mg/dL]; P = 0.048). The proportion of time with sensor glucose <3.9 mmol/L [70 mg/dL] was similar between interventions (median [interquartile range] ultra-rapid lispro 2.3% [1.3%–2.7%] vs. standard insulin lispro 2.1% [1.4%–3.3%]; P = 0.33). No severe hypoglycemia or ketoacidosis occurred. Conclusions: The use of ultra-rapid lispro with CamAPS FX hybrid closed-loop increases time in range and reduces mean glucose with no difference in hypoglycemia compared with standard insulin lispro in adults with type 1 diabetes. ClinicalTrials.gov: Trial registration number NCT05257460. [ABSTRACT FROM AUTHOR]

Closed-loop insulin delivery systems are fast becoming the standard of care in the management of type 1 diabetes and have led to significant improvements in diabetes management. Nevertheless, there is still room for improvement for the closed-loop systems to optimize treatment and meet target glycemic control. Adjunct treatments have been introduced as an alternative method to insulin-only treatment methods to overcome diabetes treatment challenges and improve clinical and patient reported outcomes during closed-loop treatment. The adjunct treatment agents mostly consist of medications that are already approved for type 2 diabetes treatment and aim to complete the missing physiologic factors, such as the entero-endocrine system, that regulate glycemia in addition to insulin. This paper will review many of these adjunct therapies, including the basic mechanisms of action, potential benefits, side effects, and the evidence supporting their use during closed-loop treatment.

Open source closed loop automated insulin delivery (CL-AID) systems are increasingly used in the treatment of diabetes. Assembled on a do-it-yourself (DIY) basis, these systems integrate insulin pumps, continuous glucose monitoring devices, and algorithms that control the rate of insulin delivery based on glucose levels. In this review, we consider the technological features of open source CL-AID systems (OpenAPS, AndroidAPS, Loop, etc.), advantages and barriers to their use in clinical practice. Advantages of open source CL-AID systems over commercially available ones included lower cost, a choice of devices, a wide range of user settings, as well as continuous improvement of algorithms. A growing body of evidence indicates that open source CL-AID systems, such as OpenAPS, AndroidAPS, and Loop, provide an excellent time in range with minimal risk of hypoglycaemia and increase treatment satisfaction in patients with type 1 diabetes. A wide range of settings makes open source systems an effective tool for managing diabetes in situations with rapidly changing insulin requirement. However, some technological, medical, legal and ethical issues associated with the use of non-commercial CL-AID systems still need to be addressed. Assembling the system requires skills in diabetes technology. The issue of cybersecurity is also relevant. Lack of official approvals, low awareness of medical professionals, and reimbursement issues are slowing down the introduction of the technology into clinical practice. The professional medical community at the international and national levels needs to determine its position regarding the use of open source CL-AID systems in the treatment of diabetes.

Automated insulin delivery systems, also known as closed-loop o r ‘artificial pancreas’ systems, are transforming the management of type 1 diabetes. These systems consist of an algorithm which responds to real-time glucose sensor levels by automatically modulating insulin delivery through an insulin pump. We review the rapidly changing landscape of automated insulin-delivery systems over recent decades, from initial prototypes to the different hybrid closed-loop systems commercially available today. We discuss the growing body of clinical trials and real-world evidence demonst rating their glycaemic and psychosocial benefits. We also address future directions in auto mated insulin delivery such as dual-hormone systems and adjunct therapy as well as the chal lenges around ensuring equitable access to closed-loop technology.

ABSTRACT: Background: Slow insulin absorption prevents the development of a fully automated artificial pancreas with subcutaneous insulin delivery. Objective: We have hypothesized that glucagon could be used as a vasodilator to accelerate insulin absorption in a bihormonal subcutaneous artificial pancreas. The present proof-of-concept study is the first study to investigate the pharmacokinetics of insulin after subcutaneous administration of a low dose of glucagon at the site of subcutaneous insulin injection. Methods: Twelve anesthetized pigs were randomized to receive a subcutaneous injection of 10 IU insulin aspart with either 100 µg glucagon or the equivalent volume of placebo (0.9% saline solution) injected at the same site. Arterial samples were collected for 180 minutes to determine insulin, glucagon, and glucose concentrations. Results: Glucagon did not influence the insulin concentration Tmax in plasma. The plasma insulin AUC0–∞ was significantly larger after glucagon administration (P < 0.01). The glucagon group had significantly higher glucose concentrations in the first 30 minutes after insulin administration (P < 0.05). Conclusions: This proof-of-concept study indicates that glucagon may increase the total absorption of a single dose of subcutaneously injected insulin. This is a novel observation. However, we did not observe any reduction in insulin concentration Tmax, as we had hypothesized. Further, glucagon induced a significant, undesirable increase in early blood glucose concentrations.

Abstract The controller is important for the artificial pancreas to guide insulin infusion in diabetic therapy. However, the inter- and intra-individual variability and time delay of glucose metabolism bring challenges to control glucose within a normal range. In this study, a multivariable identification based model predictive control (mi-MPC) is developed to overcome the above challenges. Firstly, an integrated glucose-insulin model is established to describe insulin absorption, glucose-insulin interaction under meal disturbance, and glucose transport. On this basis, an observable glucose-insulin dynamic model is formed, in which the individual parameters and disturbances can be identified by designing a particle filtering estimator. Next, embedded with the identified glucose-insulin dynamic model, a mi-MPC method is proposed. In this controller, plasma glucose concentration (PGC), an important variable and indicator of glucose regulation, is estimated and controlled directly. Finally, the method was tested on 30 in-silico subjects produced by the UVa/Padova simulator. The results show that the mi-MPC method including the model, individual identification, and the controller can regulate glucose with the mean value of 7.45 mmol/L without meal announcement. [ABSTRACT FROM AUTHOR]

Patients with type 1 diabetes must continually decide how much insulin to inject before each meal to maintain blood glucose levels within a healthy range. Recent research has worked on a solution for this burden, showing the potential of reinforcement learning as an emerging approach for the task of controlling blood glucose levels. In this paper, we test and evaluate several deep Q-learning algorithms for automated and personalized blood glucose regulation in an in silico type 1 diabetes patient with the goal of estimating and delivering proper insulin doses. The proposed algorithms are model-free approaches with no prior information about the patient. We used the Hovorka model with meal variation and carbohydrate counting errors to simulate the patient included in this work. Our experiments compare different deep Q-learning extensions showing promising results controlling blood glucose levels, with some of the proposed algorithms outperforming standard baseline treatment. [ABSTRACT FROM AUTHOR]

Objectives: To describe the trends and characteristics of the worldwide scientific production on the use of artificial pancreas (AP) in the management of diabetes mellitus (DM). Materials and Methods: Scientific papers published between 2017 and 2022 were retrieved from the Scopus database using relevant keywords. Only original articles, reviews, and short surveys were included. The metadata were exported to the SciVal software for retrieving quantitative data and the main characteristics such as journals, authors, institutions, journal metrics by quartiles, subcategories, and collaborative networks were extracted. Results: A total of 642 articles were included after applying the inclusion/exclusion criteria: original articles, 489; reviews, 151; and short surveys, 2. The most common type of collaboration was at the national level (38.3%; citations per publication: 22.3; field-weighted citation index [FWCI]: 2.2) followed by international collaboration (29.4%; citations per publication: 19.6; FWCI: 1.94). More than 70% of articles in each year were published in journals listed in Q1. Two journals, Diabetes Technology and Therapeutics and Journal of Diabetes Science and Technology, accounted for about 22% of all publications. Six of the top 10 universities were from the United States, with The University of Virginia having the most publications (n = 54; 59 authors; citations per publication: 38.4; FWCI: 3.73). Conclusions: The findings of this study highlight that most research on this topic is published in high-quality journals and has a good citation impact. Notably, most research has been conducted in developed countries, thereby indicating the need for research efforts in this field from developing countries. [ABSTRACT FROM AUTHOR]