Dual-hormone artificial pancreas for glucose control in type 1 diabetes: A meta-analysis

Real-world glycaemic outcomes of automated insulin delivery in type 1 diabetes: A meta-analysis

AIM

To evaluate the real-world effectiveness of automated insulin delivery (AID) systems in patients with type 1 diabetes (T1D).

MATERIALS AND METHODS

PubMed, Embase, the Cochrane Library, and ClinicalTrials.gov were searched for studies published up until 2 March 2024. We included pragmatic randomized controlled trials (RCTs), cohort studies, and before-after studies that compared AID systems with conventional insulin therapy in real-world settings and reported continuous glucose monitoring outcomes. Percent time in range (TIR; 3.9-10 mmol/L), time below range (TBR; <3.9 mmol/L), time above range (TAR; >10 mmol/L), and glycated haemoglobin (HbA1c) level were extracted. Data were summarized as mean differences (MDs) with 95% confidence interval.

RESULTS

A total of 23 before-after studies (101 704 participants) were included in the meta-analysis. AID systems were associated with an increased percentage of TIR (11.61%, 10.47 to 12.76; p < 0.001). The favourable effect of AID systems was consistently observed when used continuously for 6 (11.76%) or 12 months (11.33%), and in both children (12.16%) and adults (11.04%). AID systems also showed favourable effects on TBR (-0.53%, -0.63 to -0.42), TAR (-9.65%, -10.63 to -8.67) and HbA1c level (-0.42%, -0.47 to -0.37) when compared with previous treatments.

CONCLUSIONS

Similar improvements in glycaemic parameters were observed in real-world settings in RCTs using AID systems in T1D. AID systems benefit both children and adults by increasing TIR for both short- and long-term interventions.

Bihormonal fully closed-loop system for the treatment of type 1 diabetes: a real-world multicentre, prospective, single-arm trial in the Netherlands

BACKGROUND

Management of insulin administration for intake of carbohydrates and physical activity can be burdensome for people with type 1 diabetes on hybrid closed-loop systems. Bihormonal fully closed-loop (FCL) systems could help reduce this burden. In this trial, we assessed the long-term performance and safety of a bihormonal FCL system.

METHODS

The FCL system (Inreda AP; Inreda Diabetic, Goor, Netherlands) that uses two hormones (insulin and glucagon) was assessed in a 1 year, multicentre, prospective, single-arm intervention trial in adults with type 1 diabetes. Participants were recruited in eight outpatient clinics in the Netherlands. We included adults with type 1 diabetes aged 18-75 years who had been using flash glucose monitoring or continuous glucose monitors for at least 3 months. Study visits were integrated into standard care, usually every three months, to evaluate glycaemic control, adverse events, and person-reported outcomes. The primary endpoint was time in range (TIR; glucose concentration 3·9-10·0 mmol/L) after 1 year. The study is registered in the Dutch Trial Register, NL9578.

FINDINGS

Between June 1, 2021, and March 2, 2022, we screened 90 individuals and enrolled 82 participants; 78 were included in the analyses. 79 started the intervention and 71 were included in the 12 month analysis. Mean age was 47.7 (SD 12·4) years and 38 (49%) were female participants. The mean preintervention TIR of participants was 55·5% (SD 17·2). After 1 year of FCL treatment, mean TIR was 80·3% (SD 5·4) and median time below range was 1·36% (IQR 0·80-2·11). Questionnaire scores improved on Problem Areas in Diabetes (PAID) from 30·0 (IQR 18·8-41·3) preintervention to 10·0 (IQR 3·8-21·3; p<0·0001) at 12 months and on World Health Organization-Five Well-Being Index (WHO-5) from 60·0 (IQR 44·0-72·0) preintervention to 76·0 (IQR 60·0-80·0; p<0·0001) at 12 months. Five serious adverse events were reported (one cerebellar stroke, two severe hypoglycaemic, and two hyperglycaemic events).

INTERPRETATION

Real-world data obtained in this trial demonstrate that use of the bihormonal FCL system was associated with good glycaemic control in patients who completed 1 year of treatment, and could help relieve these individuals with type 1 diabetes from making treatment decisions and the burden of carbohydrate counting.

FUNDING

Inreda Diabetic.

Automated blood glucose regulation for nonlinear model of type-1 diabetic patient under uncertainties: GWOCS type-2 fuzzy approach

Regulating blood glucose level (BGL) for type-1 diabetic patient (T1DP) accurately is very important issue, an uncontrolled BGL outside the standard safe range between 70 and 180 mg/dl results in dire consequences for health and can significantly increase the chance of death. So the purpose of this study is to design an optimized controller that infuses appropriate amounts of exogenous insulin into the blood stream of T1DP proportional to the amount of obtained glucose from food. The nonlinear extended Bergman minimal model is used to present glucose-insulin physiological system, an interval type-2 fuzzy logic controller (IT2FLC) is utilized to infuse the proper amount of exogenous insulin. Superiority of IT2FLC in minimizing the effect of uncertainties in the system depends primarily on the best choice of footprint of uncertainty (FOU) of IT2FLC. So a comparison includes four different optimization methods for tuning FOU including hybrid grey wolf optimizer-cuckoo search (GWOCS) and fuzzy logic controller (FLC) method is constructed to select the best controller approach. The effectiveness of the proposed controller was evaluated under six different scenarios of T1DP using Matlab/Simulink platform. A 24-h scenario close to real for 100 virtual T1DPs subjected to parametric uncertainty, uncertain meal disturbance and random initial condition showed that IT2FLC accurately regulate BGL for all T1DPs within the standard safe range. The results indicated that IT2FLC using GWOCS can prevent side effect of treatment with blood-sugar-lowering medication. Also stability analysis for the system indicated that the system operates within the stability region of nonlinear system.

Efficacy of automated insulin delivery (AID) systems in type 1 diabetes: protocol of a systematic review and network meta-analysis of outpatient randomised controlled trials

INTRODUCTION

Automated insulin delivery (AID), also known as artificial pancreas system or 'closed-loop system', represents a novel option for current treatments for type 1 diabetes (T1D). The objective of this systematic review and meta-analysis is to assess the efficacy of AID systems in comparison with current intensified insulin therapy for glycaemic control and patient-reported outcomes in individuals with T1D.

METHODS AND ANALYSIS

Studies will be eligible if they are randomised controlled trials (RCTs) in people with T1D of all ages, and if they compare an AID system for self-administration during the day and night period with any other type of insulin therapy for at least 3 weeks. The primary outcome will be time in the glucose target range of 70-180 mg/dL. A systematic review will be conducted in the MEDLINE, Embase, Cochrane Central Register of Controlled Trials and ClinicalTrials.gov registries from their inception dates. Two authors will independently screen all references based on titles and abstracts against the eligibility criteria. For data extraction, standard forms will be developed and tested before extraction. All information will be assessed independently by at least two reviewers. The risk of bias of the included studies will be assessed using the Cochrane Risk of Bias 2 tool. The data synthesis will include a random-effects pairwise and network meta-analysis (NMA) in a frequentist framework. Where applicable and if sufficient RCTs are available, sensitivity analyses will be performed, and heterogeneity and publication bias will be assessed. The certainty of evidence from the NMA will be evaluated following the Grading of Recommendations Assessment, Development, and Evaluation working group guidance.

ETHICS AND DISSEMINATION

No ethical approval is needed. The results will be reported to the funder, presented in a peer-reviewed scientific journal and at conferences, and disseminated via press release, social media and public events.

PROSPERO REGISTRATION NUMBER

CRD42023395492.

Intelligent Insulin vs. Artificial Intelligence for Type 1 Diabetes: Will the Real Winner Please Stand Up?

Research in the treatment of type 1 diabetes has been addressed into two main areas: the development of "intelligent insulins" capable of auto-regulating their own levels according to glucose concentrations, or the exploitation of artificial intelligence (AI) and its learning capacity, to provide decision support systems to improve automated insulin therapy. This review aims to provide a synthetic overview of the current state of these two research areas, providing an outline of the latest development in the search for "intelligent insulins," and the results of new and promising advances in the use of artificial intelligence to regulate automated insulin infusion and glucose control. The future of insulin treatment in type 1 diabetes appears promising with AI, with research nearly reaching the possibility of finally having a "closed-loop" artificial pancreas.

Dual hormone fully closed loop in type 1 diabetes: a randomised trial in the Netherlands - study protocol

INTRODUCTION

The management of type 1 diabetes (T1DM) has undergone significant advancements with the availability of novel technologies, notably continuous and flash glucose monitoring (CGM and FGM, respectively) and hybrid closed loop (HCL) therapy. The dual hormone fully closed loop (DHFCL) approach with insulin and glucagon infusion has shown promising effects in small studies on glycaemic regulation and quality of life in T1DM.

METHODS AND ANALYSIS

The Dual Hormone Fully Closed Loop for Type 1 Diabetes (DARE) study is a non-commercial 12-month open-label, two-arm randomised parallel-group trial. The primary aim of this study is to determine the long-term effects on glycaemic control, patient-reported outcome measurements and cost-effectiveness of the DHFCL compared with usual care, that is, HCL or treatment with multiple daily insulin injections+FGM/CGM. We will include 240 adult patients with T1DM in 14 hospitals in the Netherlands. Individuals will be randomised 1:1 to the DHFCL or continuation of their current care.

ETHICS AND DISSEMINATION

Ethical approval has been obtained from the Medical Research Ethics Committee NedMec, Utrecht, the Netherlands. Findings will be disseminated through peer-reviewed publications and presentations at local, national and international conferences.

TRIAL REGISTRATION NUMBER

NCT05669547.

The Artificial Pancreas and Type 1 Diabetes

Diabetes technologies represent a paradigm shift in type 1 diabetes care. Continuous subcutaneous insulin infusion (CSII) pumps and continuous glucose monitors (CGM) improve glycated hemoglobin (HbA1c) levels, enhance time in optimal glycemic range, limit severe hypoglycemia, and reduce diabetes distress. The artificial pancreas or closed-loop system connects these devices via a control algorithm programmed to maintain target glucose, partially relieving the person living with diabetes of this constant responsibility. Automating insulin delivery reduces the input required from those wearing the device, leading to better physiological and psychosocial outcomes. Hybrid closed-loop therapy systems, requiring user-initiated prandial insulin doses, are the most advanced closed-loop systems commercially available. Fully closed-loop systems, requiring no user-initiated insulin boluses, and dual hormone systems have been shown to be safe and efficacious in the research setting. Clinical adoption of closed-loop therapy remains in early stages despite recent technological advances. People living with diabetes, health care professionals, and regulatory agencies continue to navigate the complex path to equitable access. We review the available devices, evidence, clinical implications, and barriers regarding these innovatory technologies.

Problem-based shared decision-making in diabetes care: a secondary analysis of video-recorded encounters

OBJECTIVES

To describe the range of collaborative approaches to shared decision-making (SDM) observed in clinical encounters of patients with diabetes and their clinicians.

DESIGN

A secondary analysis of videorecordings obtained in a randomised trial comparing usual diabetes primary care with or without using a within-encounter conversation SDM tool.

SETTING

Using the purposeful SDM framework, we classified the forms of SDM observed in a random sample of 100 video-recorded clinical encounters of patients with type 2 diabetes in primary care.

MAIN OUTCOME MEASURES

We assessed the correlation between the extent to which each form of SDM was used and patient involvement (OPTION12-scale).

RESULTS

We observed at least one instance of SDM in 86 of 100 encounters. In 31 (36%) of these 86 encounters, we found only one form of SDM, in 25 (29%) two forms, and in 30 (35%), we found ≥3 forms of SDM. In these encounters, 196 instances of SDM were identified, with weighing alternatives (n=64 of 196, 33%), negotiating conflicting desires (n=59, 30%) and problemsolving (n=70, 36%) being similarly prevalent and developing existential insight accounting for only 1% (n=3) of instances. Only the form of SDM focused on weighing alternatives was correlated with a higher OPTION12-score. More forms of SDM were used when medications were changed (2.4 SDM forms (SD 1.48) vs 1.8 (SD 1.46); p=0.050).

CONCLUSIONS

After considering forms of SDM beyond weighing alternatives, SDM was present in most encounters. Clinicians and patients often used different forms of SDM within the same encounter. Recognising a range of SDM forms that clinicians and patients use to respond to problematic situations, as demonstrated in this study, opens new lines of research, education and practice that may advance patient-centred, evidence-based care.