Titration of Long-Acting Insulin Using Continuous Glucose Monitoring and Smart Insulin Pens in Type 1 Diabetes: A Model-Based Carbohydrate-Free Approach.

Objective: Multiple daily injections (MDI) therapy is the most common treatment for type 1 diabetes (T1D), consisting of long-acting insulin to cover fasting conditions and rapid-acting insulin to cover meals. Titration of long-acting insulin is needed to achieve satisfactory glycemia but is challenging due to inter-and intra-individual metabolic variability. In this work, a novel titration algorithm for long-acting insulin leveraging continuous glucose monitoring (CGM) and smart insulin pens (SIP) data is proposed.

Alleviating carbohydrate counting with a FiASP-plus-pramlintide closed-loop delivery system (artificial pancreas): Feasibility and pilot studies.

Aim: To assess whether a FiASP-and-pramlintide closed-loop system has the potential to replace carbohydrate counting with a simple meal announcement (SMA) strategy (meal priming bolus without carbohydrate counting) without degrading glycaemic control compared with a FiASP closed-loop system.

Materials And Methods: We conducted a 24-hour feasibility study comparing a FiASP system with full carbohydrate counting (FCC) with a FiASP-and-pramlintide system with SMA. We conducted a subsequent 12-day outpatient pilot study comparing a FiASP-and-placebo system with FCC, a FiASP-and-pramlintide system with SMA, and a FiASP-and-placebo system with SMA.

Fully Automated Artificial Pancreas for Adults With Type 1 Diabetes Using Multiple Hormones: Exploratory Experiments.

Objectives: A fully automated insulin-pramlintide-glucagon artificial pancreas that alleviates the burden of carbohydrate counting without degrading glycemic control was iteratively enhanced until convergence through pilot experiments on adults with type 1 diabetes.

Methods: Nine participants (age, 37±13 years; glycated hemoglobin, 7.7±0.

Modelling glucose dynamics during moderate exercise in individuals with type 1 diabetes.

The artificial pancreas is a closed-loop insulin delivery system that automatically regulates glucose levels in individuals with type 1 diabetes. In-silico testing using simulation environments accelerates the development of better artificial pancreas systems. Simulation environments need an accurate model that captures glucose dynamics during exercise to simulate real-life scenarios.

Reducing the need for carbohydrate counting in type 1 diabetes using closed-loop automated insulin delivery (artificial pancreas) and empagliflozin: A randomized, controlled, non-inferiority, crossover pilot trial.

Aim: To assess whether adding empagliflozin to closed-loop automated insulin delivery could reduce the need for carbohydrate counting in type 1 diabetes (T1D) without worsening glucose control.

Materials And Methods: In an open-label, crossover, non-inferiority trial, 30 adult participants with T1D underwent outpatient automated insulin delivery interventions with three random sequences of prandial insulin strategy days: carbohydrate counting, simple meal announcement (no carbohydrate counting) and no meal announcement. During each sequence of prandial insulin strategies, participants were randomly assigned empagliflozin (25 mg/day) or not, and crossed over to the comparator.

Long-term use of the hybrid artificial pancreas by adjusting carbohydrate ratios and programmed basal rate: A reinforcement learning approach.

Background And Objectives: The hybrid artificial pancreas regulates glucose levels in people with type 1 diabetes. It delivers (i) insulin boluses at meal times based on the meals' carbohydrate content and the carbohydrate ratios (CRs) and (ii) insulin basal, between meals and at night, continuously modulated around individual-specific programmed basal rate. The CRs and programmed basal rate significantly vary between individuals and within the same individual with type 1 diabetes, and using suboptimal values in the hybrid artificial pancreas may degrade glucose control.

A Meal Detection Algorithm for the Artificial Pancreas: A Randomized Controlled Clinical Trial in Adolescents With Type 1 Diabetes.

Objective: We developed a meal detection algorithm for the artificial pancreas (AP+MDA) that detects unannounced meals and delivers automatic insulin boluses.

Research Design And Methods: We conducted a randomized crossover trial in 11 adolescents aged 12-18 years with HbA ≥7.5% who missed one or more boluses in the past 6 months.

Comparison Between Closed-Loop Insulin Delivery System (the Artificial Pancreas) and Sensor-Augmented Pump Therapy: A Randomized-Controlled Crossover Trial.

Several studies have shown that closed-loop automated insulin delivery (the artificial pancreas) improves glucose control compared with sensor-augmented pump therapy. We aimed to confirm these findings using our automated insulin delivery system based on the iPancreas platform. We conducted a two-center, randomized crossover trial comparing automated insulin delivery with sensor-augmented pump therapy in 36 adults with type 1 diabetes.

A Model-Based Insulin Dose Optimization Algorithm for People With Type 1 Diabetes on Multiple Daily Injections Therapy.

Objective: Multiple daily injections (MDI) therapy is the most common treatment for type 1 diabetes (T1D) including basal insulin doses to keep glucose levels constant during fasting conditions and bolus insulin doses with meals. Optimal insulin dosing is critical to achieving satisfactory glycemia but is challenging due to inter- and intra-individual variability. Here, we present a novel model-based iterative algorithm that optimizes insulin doses using previous-day glucose, insulin, and meal data.

Postprandial hyperglycaemia following insulin suspensions by the artificial pancreas: Implications for bolus calculators.

Conventional bolus calculators apply negative prandial corrections when premeal glucose levels are low. However, no study has evaluated the need for this negative correction with closed-loop systems. We analysed data retrospectively from a cohort study evaluating a closed-loop artificial pancreas system conducted in a diabetes camp over a period of 11 days.

A pilot non-inferiority randomized controlled trial to assess automatic adjustments of insulin doses in adolescents with type 1 diabetes on multiple daily injections therapy.

Background: Multiple daily injections (MDI) therapy for type 1 diabetes involves basal and bolus insulin doses. Non-optimal insulin doses contribute to the lack of satisfactory glycemic control. We aimed to evaluate the feasibility of an algorithm that optimizes daily basal and bolus doses using glucose monitoring systems for MDI therapy users.

A Novel Dual-Hormone Insulin-and-Pramlintide Artificial Pancreas for Type 1 Diabetes: A Randomized Controlled Crossover Trial.

Objective: The rapid insulin-alone artificial pancreas improves glycemia in type 1 diabetes but daytime control remains suboptimal. We propose two novel dual-hormone artificial pancreas systems.

Research Design And Methods: We conducted a randomized crossover trial comparing a rapid insulin-alone artificial pancreas with rapid insulin-and-pramlintide and with regular insulin-and-pramlintide artificial pancreas systems in adults with type 1 diabetes.

Accuracy of FreeStyle Libre in Adults with Type 1 Diabetes: The Effect of Sensor Age.

FreeStyle Libre is a factory-calibrated continuous 14-day glucose sensor. Little is known about the accuracy of FreeStyle Libre as a function of sensor age. We assessed the accuracy of FreeStyle Libre in 14 adults with type 1 diabetes.

The Efficacy of Basal Rate and Carbohydrate Ratio Learning Algorithm for Closed-Loop Insulin Delivery (Artificial Pancreas) in Youth with Type 1 Diabetes in a Diabetes Camp.

Optimizing programmed basal rates and carbohydrate ratios may improve the performance of the artificial pancreas. We tested, in a diabetes camp, the efficacy of a learning algorithm that updates daily basal rates and carbohydrate ratios in the artificial pancreas. We conducted a randomized crossover trial in campers and counselors aged 8-21 years with type 1 diabetes on pump therapy.

The potential impact of intelligent power wheelchair use on social participation: perspectives of users, caregivers and clinicians.

Purpose: To explore power wheelchair users', caregivers' and clinicians' perspectives regarding the potential impact of intelligent power wheelchair use on social participation.

Methods: Semi-structured interviews were conducted with power wheelchair users (n = 12), caregivers (n = 4) and clinicians (n = 12). An illustrative video was used to facilitate discussion.

Exploring powered wheelchair users and their caregivers' perspectives on potential intelligent power wheelchair use: a qualitative study.

Power wheelchairs (PWCs) can have a positive impact on user well-being, self-esteem, pain, activity and participation. Newly developed intelligent power wheelchairs (IPWs), allowing autonomous or collaboratively-controlled navigation, could enhance mobility of individuals not able to use, or having difficulty using, standard PWCs. The objective of this study was to explore the perspectives of PWC users (PWUs) and their caregivers regarding if and how IPWs could impact on current challenges faced by PWUs, as well as inform current development of IPWs.