Surface Engineered PLGA Nanoparticle for Threshold Responsive Glucose Monitoring and “Self-Programmed” Insulin Delivery

2021 ◽  
Vol 7 (9) ◽  
pp. 4645-4658
Author(s):  
Gaurav Ranjan Dey ◽  
Arindam Saha
Keyword(s):  
Glucose Monitoring ◽  
Insulin Delivery ◽  
Plga Nanoparticle

Comparing Patch vs. Pen Bolus Insulin Delivery in Type 2 Diabetes Using Continuous Glucose Monitoring Metrics and Profiles

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 73-LB
Author(s):  
MARY L. JOHNSON ◽  
DARLENE M. DREON ◽  
BRIAN L. LEVY ◽  
SARA RICHTER ◽  
DEBORAH MULLEN ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
Insulin Delivery ◽  
Bolus Insulin

136-OR: Nocturnal Hypoglycemia Prevention Strategies Used by People with Type 1 Diabetes According to Their Insulin Delivery and Blood Glucose Monitoring Technology

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 136-OR
Author(s):  
MERYEM K. TALBO ◽  
VIRGINIE MESSIER ◽  
KATHERINE DESJARDINS ◽  
RÉMI RABASA-LHORET ◽  
ANNE-SOPHIE BRAZEAU ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Blood Glucose ◽  
Glucose Monitoring ◽  
Insulin Delivery ◽  
Blood Glucose Monitoring ◽  
Prevention Strategies ◽  
Monitoring Technology ◽  
Nocturnal Hypoglycemia

scholarly journals An Insulin Bolus Advisor for Type 1 Diabetes Using Deep Reinforcement Learning

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5058 ◽  
Author(s):  
Taiyu Zhu ◽  
Kezhi Li ◽  
Lei Kuang ◽  
Pau Herrero ◽  
Pantelis Georgiou
Keyword(s):  
Type 1 Diabetes ◽  
Reinforcement Learning ◽  
Glucose Monitoring ◽  
Insulin Delivery ◽  
Target Range ◽  
Average Percentage ◽  
Learning Framework ◽  
Policy Gradient ◽  
Bolus Insulin

(1) Background: People living with type 1 diabetes (T1D) require self-management to maintain blood glucose (BG) levels in a therapeutic range through the delivery of exogenous insulin. However, due to the various variability, uncertainty and complex glucose dynamics, optimizing the doses of insulin delivery to minimize the risk of hyperglycemia and hypoglycemia is still an open problem. (2) Methods: In this work, we propose a novel insulin bolus advisor which uses deep reinforcement learning (DRL) and continuous glucose monitoring to optimize insulin dosing at mealtime. In particular, an actor-critic model based on deep deterministic policy gradient is designed to compute mealtime insulin doses. The proposed system architecture uses a two-step learning framework, in which a population model is first obtained and then personalized by subject-specific data. Prioritized memory replay is adopted to accelerate the training process in clinical practice. To validate the algorithm, we employ a customized version of the FDA-accepted UVA/Padova T1D simulator to perform in silico trials on 10 adult subjects and 10 adolescent subjects. (3) Results: Compared to a standard bolus calculator as the baseline, the DRL insulin bolus advisor significantly improved the average percentage time in target range (70–180 mg/dL) from 74.1%±8.4% to 80.9%±6.9% (p<0.01) and 54.9%±12.4% to 61.6%±14.1% (p<0.01) in the the adult and adolescent cohorts, respectively, while reducing hypoglycemia. (4) Conclusions: The proposed algorithm has the potential to improve mealtime bolus insulin delivery in people with T1D and is a feasible candidate for future clinical validation.

scholarly journals The road from intermittently scanned continuous glucose monitoring to hybrid closed-loop systems. Part B: results from randomized controlled trials

2019 ◽  
Vol 10 ◽  
pp. 204201881987190 ◽  
Author(s):  
Francesca De Ridder ◽  
Marieke den Brinker ◽  
Christophe De Block
Keyword(s):  
Randomized Controlled Trials ◽  
Continuous Glucose Monitoring ◽  
Closed Loop ◽  
Glucose Monitoring ◽  
Insulin Delivery ◽  
Controlled Trials ◽  
Randomized Controlled ◽  
Closed Loop Systems ◽  
Adults And Children

Background: Advances in diabetes technology have been exponential in the last few decades. With evolution in continuous glucose monitoring (CGM) systems and its progressive automation in control of insulin delivery, these advances have changed type 1 diabetes mellitus (T1DM) management. These novel technologies have the potential to improve glycated haemoglobin (HbA1c), reduce hypoglycaemic events, increase time spent in range and improve quality of life (QoL). Our aim was to evaluate the sustained effects in free-living unsupervised conditions of CGM systems (intermittently scanned and real time) and insulin delivery [from multiple daily injections, via sensor-augmented pump therapy and (predictive) low-glucose insulin suspension to hybrid closed-loop systems] on glucose control and QoL in adults and children with T1DM. Methods: We performed a systematic review of randomized controlled trials (RCTs), using PubMed and the Cochrane library up to 30 May 2019. Inclusion of RCTs was based on type of intervention (comparing glucose-monitoring devices and insulin-delivery devices), population (nonpregnant adults and children with T1DM), follow-up (outpatient setting for at least 8 weeks) and relevant outcomes [HbA1c, time in range (TIR), time in target, time in hypoglycaemia and QoL]. Exclusion of RCTs was based on intervention (exercise, only overnight use). The Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines were used to score the quality of the papers and for the final selection of the articles. Results: Our search resulted in 214 articles, of which 19 were eligible. Studies on advanced use in adults and children with T1DM reported increased TIR (all 9 studies); decreased time in hypoglycaemia (13 out of 15 studies); lowered HbA1c levels (5 out of 15 studies); improved QoL (10 of 16 studies) and treatment satisfaction (7 studies). Conclusions: Recent technologies have dramatically changed the course of T1DM. They are proving useful in controlling glycaemia in patients with T1DM, without increasing the treatment burden.

scholarly journals Old syndrome–new approach: Mauriac syndrome treated with continuous insulin delivery

2018 ◽  
Vol 6 ◽  
pp. 2050313X1878551 ◽  
Author(s):  
Mirjana Kocova ◽  
Liljana Milenkova
Keyword(s):  
Clinical Presentation ◽  
Glucose Monitoring ◽  
Insulin Delivery ◽  
Diabetes Mellitus Type 1 ◽  
Delayed Puberty ◽  
Growth Delay ◽  
New Approach ◽  
Mauriac Syndrome

Mauriac syndrome has rarely been reported in children and adolescents with a poorly controlled diabetes mellitus type 1. However, it still occurs despite the worldwide improvements of metabolic control. The risks have not been elucidated. We present a 13.5-year-old boy with a typical clinical presentation of Mauriac syndrome consisting of growth delay, cushingoid appearance, hepatomegaly, and delayed puberty. A stepwise correction of glycemic control was introduced using continuous insulin delivery. All symptoms improved during the 2.5-year follow-up. No retinopathy occurred. This patient with Mauriac syndrome followed with continuous glucose monitoring and treated with continuous insulin delivery, resulting in no retinopathy after 2.5 years of follow-up. We suggest that this approach should be recommended in patients with Mauriac syndrome.

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