scholarly journals Safety Evaluation of the Omnipod® 5 Automated Insulin Delivery System Over Three Months of Use in Children With Type 1 Diabetes (T1D)

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A454-A454
Author(s):  
Bruce A Buckingham ◽  
Gregory P Forlenza ◽  
Amy B Criego ◽  
David W Hansen ◽  
Bruce W Bode ◽  
...  
Keyword(s):  
Insulin Pump ◽  
Safety Evaluation ◽  
Insulin Delivery ◽  
Time Of Day ◽  
Large Cohort ◽  
Extension Phase ◽  
Target Range ◽  
Pivotal Study ◽  
Glucose Management ◽  
At Home

Abstract Advances in diabetes technology have transformed the treatment paradigm for T1D, yet the burden of the disease remains significant. The pediatric population poses unique challenges to glucose management with unpredictable exercise and food consumption. The Omnipod 5 System is a novel hybrid closed-loop (HCL) system with fully on-body operation. A tubeless insulin pump (pod) containing a personalized Model Predictive Control algorithm communicates directly with a Dexcom G6 continuous glucose monitor (CGM, or sensor) to automate insulin delivery. Therapy customization is enabled through glucose targets from 110–150 mg/dL, adjustable by time of day, which is a critical component to individualize glucose management in children. We report on the first, pivotal outpatient safety evaluation of the Omnipod 5 System in a large cohort of children with T1D. Participants aged 6–13.9y with T1D≥6 months and A1C<10% used the HCL system for 3 months at home after a 14-day run-in phase of their standard therapy (ST, included both pump therapy and multiple daily injections). The primary safety and effectiveness endpoints, respectively, were occurrence of severe hypoglycemia (SH) and diabetic ketoacidosis (DKA), and change in A1C and sensor glucose percent time in target range (TIR) (70–180 mg/dL) during HCL compared with ST. Participants (N=112) were aged (mean±SD) 10.3±2.2y with T1D duration 4.7±2.6y and baseline A1C 7.7±0.9% (range 5.8–10.3%). TIR increased significantly from ST to HCL, from 52.5±15.6% to 68.0±8.1% (p<0.0001), corresponding to an additional 3.7 hours/day in target range. A1C at end of study was reduced by 0.7% to 7.0±0.6% (p<0.0001). Percentages of time in hyperglycemia were reduced: >180 mg/dL from 45.3±16.7% to 30.2±8.7% and ≥250 mg/dL from 19.1±13.1% to 9.6±5.4% (both p<0.0001). Percentages of time in hypoglycemia remained low from ST to HCL: <54 mg/dL from 0.4±0.8% to 0.3±0.3% and <70 mg/dL from 2.2±2.7% to 1.8±1.4% (both p>0.05). Mean glucose decreased from 183±32 to 160±15 mg/dL (p<0.0001). During the HCL phase there was 1 episode of SH (delayed eating after pre-meal bolus) and 1 episode of DKA (suspected infusion site failure) reported. Virtually all participants completing the pivotal study (99%) continued system use during an extension phase. In this multi-center pivotal study in a large cohort of children with T1D, the Omnipod 5 System was safe and effective when used for 3 months at home. There were significant improvements in both TIR and A1C, while time below range (<70 mg/dL) remained low. The beneficial glycemic outcomes are critical for children, given that neurologic outcomes can be negatively impacted by hyperglycemia. The current results and commitment to the extension phase emphasize the safe and effective use of the HCL system, as well as the preference for the Omnipod 5 System over participants’ previous therapy.

scholarly journals Safety Evaluation of the Omnipod® 5 Automated Insulin Delivery System Over Three Months of Use in Adults and Adolescents With Type 1 Diabetes (T1D)

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. A671-A672
Author(s):  
Sue A Brown ◽  
Carol J Levy ◽  
Irl B Hirsch ◽  
Bruce W Bode ◽  
Anders L Carlson ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Delivery System ◽  
Safety Evaluation ◽  
Insulin Delivery ◽  
Large Cohort ◽  
Extension Phase ◽  
Target Range ◽  
Pivotal Study ◽  
Insulin Delivery System

Abstract Advances in diabetes technology have transformed the treatment paradigm for type 1 diabetes (T1D), yet the burden of disease remains significant. The Omnipod 5 Automated Insulin Delivery System is a novel hybrid closed-loop (HCL) system with fully on-body operation. The system consists of a tubeless insulin pump (pod) containing a personalized Model Predictive Control algorithm which communicates directly with a Dexcom G6 continuous glucose monitor (CGM, or sensor) to automate insulin delivery. Therapy customization is enabled through glucose targets from 110-150 mg/dL, adjustable by time of day. The system adapts to changing insulin needs with each pod change. We report on the first, pivotal outpatient safety evaluation of the system in a large cohort of adults and adolescents with T1D. Participants aged 14-70y with T1D≥6 months and A1C<10% used the HCL system for 3 months at home after a 14-day run-in phase of their standard therapy (ST). Prior therapy included both pump therapy and multiple daily injections. The primary safety and effectiveness endpoints, respectively, were occurrence of severe hypoglycemia (SH) and diabetic ketoacidosis (DKA), and change in A1C and sensor glucose percent time in target range (TIR) (70-180 mg/dL) during HCL compared with ST. Participants (N=128) were aged (mean±SD) 37±14y with T1D duration 18±12y and baseline A1C 7.2±0.9% (range 5.2-9.8%). There was a significant increase in TIR from ST to HCL, from 64.7±16.6% to 73.9±11.0% (p<0.0001), corresponding to an additional 2.2 hours/day in target range. A1C at end of study was reduced by 0.4%, from 7.2±0.9% to 6.8±0.7% (p<0.0001). Glycemic outcomes for percent of time with CGM readings below and above target range were all reduced (p<0.0001): <54 mg/dL from 0.6±1.2% to 0.2±0.3% (a decrease of 6 minutes/day), <70 mg/dL from 2.9±3.1% to 1.3±1.1% (a decrease of 23 minutes/day), >180 mg/dL from 32.4±17.3% to 24.7±11.2% (a decrease of 1.8 hours/day), and ≥250 mg/dL from 10.1±10.5% to 5.8±5.5% (a decrease of 1.0 hours/day). The mean glucose also decreased from 161±28 to 154±17 mg/dL (p=0.0002). During the 3-month HCL phase there were 2 episodes of SH (both following user-initiated boluses) and no episodes of DKA reported. Most participants completing the pivotal study (92%) opted to continue using the system during an extension phase. In this outpatient, multi-center pivotal study in a large cohort of adults and adolescents with T1D, the Omnipod 5 System was safe and effective when used for 3 months at home. There were significant improvements in both TIR and A1C with use of the system, while time in hypoglycemic ranges was also reduced. The current results and commitment to the extension phase highlight the safe and effective use of the HCL system, as well as the preference for the Omnipod 5 System over participants’ previous therapy.

scholarly journals Control to Range for Diabetes: Functionality and Modular Architecture

2009 ◽  
Vol 3 (5) ◽  
pp. 1058-1065 ◽  
Author(s):  
Boris Kovatchev ◽  
Stephen Patek ◽  
Eyal Dassau ◽  
Francis J. Doyle ◽  
Lalo Magni ◽  
...  
Keyword(s):  
Closed Loop ◽  
Glucose Sensor ◽  
Insulin Pump ◽  
Insulin Delivery ◽  
Open Loop ◽  
Target Range ◽  
Closed Loop Control ◽  
Modular Architecture ◽  
Loop Control ◽  
Range Correction

Background: Closed-loop control of type 1 diabetes is receiving increasing attention due to advancement in glucose sensor and insulin pump technology. Here the function and structure of a class of control algorithms designed to exert control to range, defined as insulin treatment optimizing glycemia within a predefined target range by preventing extreme glucose fluctuations, are studied. Methods: The main contribution of the article is definition of a modular architecture for control to range. Emphasis is on system specifications rather than algorithmic realization. The key system architecture elements are two interacting modules: range correction module, which assesses the risk for incipient hyper- or hypoglycemia and adjusts insulin rate accordingly, and safety supervision module, which assesses the risk for hypoglycemia and attenuates or discontinues insulin delivery when necessary. The novel engineering concept of range correction module is that algorithm action is relative to a nominal open-loop strategy—a predefined combination of basal rate and boluses believed to be optimal under nominal conditions. Results: A proof of concept of the feasibility of our control-to-range strategy is illustrated by using a prototypal implementation tested in silico on patient use cases. These functional and architectural distinctions provide several advantages, including (i) significant insulin delivery corrections are only made if relevant risks are detected; (ii) drawbacks of integral action are avoided, e.g., undershoots with consequent hypoglycemic risks; (iii) a simple linear model is sufficient and complex algorithmic constraints are replaced by safety supervision; and (iv) the nominal profile provides straightforward individualization for each patient. Conclusions: We believe that the modular control-to-range system is the best approach to incremental development, regulatory approval, industrial deployment, and clinical acceptance of closed-loop control for diabetes.

The Artificial Pancreas: What School Nurses Need to Know

2018 ◽  
Vol 34 (2) ◽  
pp. 86-89 ◽  
Author(s):  
Jennifer Latham
Keyword(s):  
Delivery System ◽  
Closed Loop ◽  
Insulin Pump ◽  
Artificial Pancreas ◽  
Insulin Delivery ◽  
School Nurses ◽  
Continuous Glucose Monitor ◽  
Insulin Delivery System ◽  
Future Direction ◽  
Glucose Management

The hybrid closed-loop insulin delivery system, a form of “artificial pancreas,” is composed of an insulin pump, a standardized algorithm, and a continuous glucose monitor. The system streamlines insulin delivery by connecting continuous glucose monitor data with an insulin pump and an algorithm to drive basal insulin delivery. The hybrid closed-loop insulin delivery system, approved by the Food and Drug Administration in 2016 for children older than 7 years, is a major improvement in the management of type 1 diabetes. The purpose of this article is to educate school nurses about the components of the hybrid closed-loop insulin delivery system, the relevance to care, and the future direction of blood glucose management.

730-P: At-Home Randomized Crossover Comparison of Automated Insulin Delivery vs. Conventional Therapy with Scheduled Meal Challenges

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 730-P
Author(s):  
JORDAN E. PINSKER ◽  
SUNIL DESHPANDE ◽  
MEI MEI CHURCH ◽  
MOLLY PIPER ◽  
CAMILLE C. ANDRE ◽  
...  
Keyword(s):  
Conventional Therapy ◽  
Insulin Delivery ◽  
Crossover Comparison ◽  
At Home

scholarly journals Self-Care IoT Platform for Diabetic Mellitus

2021 ◽  
Vol 11 (5) ◽  
pp. 2006
Author(s):  
Jai-Chang Park ◽  
Seongbeom Kim ◽  
Je-Hoon Lee
Keyword(s):  
Blood Glucose ◽  
Self Care ◽  
Target Range ◽  
Process Data ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
Iot Platform ◽  
Number Of Patients ◽  
Glucose Management ◽  
The Relationship

Diabetes mellitus is a severe chronic disease, and the number of patients has increased. To manage blood glucose levels, patients should frequently measure their blood glucose and analyze which lifestyle habits affect blood glucose levels. However, it is hard to record and analyze the relationship between their blood glucose levels and lifestyle. The internet of things (IoT) is useful to interconnect, monitor, obtain, and process data between various devices used in everyday life to fulfill a common objective. This paper proposes an intelligent self-care platform using IoT technology that helps patients with chronic diabetes manage their blood glucose levels in their target range. In particular, we developed various devices called the self-care IoT pack. It consists of five different types of devices to obtain blood glucose levels, physical activities, food intake, medication, sleeping, and so on. They can collect blood glucose levels with lifestyles that automatically impact the patient’s blood glucose level. We also devised a self-care application to display and analyze the data obtained from the IoT pack. Consequently, the proposed self-care IoT platform collects the blood glucose levels and the lifestyles without any burden of record. By reviewing the accumulated information, the patients can find bad habits in blood glucose management and improve their lifestyle.

scholarly journals Lower Volumes, Higher Speeds: Changes to Crash Type, Timing, and Severity on Urban Roads from COVID-19 Stay-at-Home Policies

2021 ◽  
pp. 036119812110444
Author(s):  
Jonathan Stiles ◽  
Armita Kar ◽  
Jinhyung Lee ◽  
Harvey J. Miller
Keyword(s):  
Logistic Regression ◽  
Traffic Safety ◽  
Travel Demand ◽  
Multinomial Logistic Regression ◽  
High Volume ◽  
Time Of Day ◽  
Bayesian Hierarchical ◽  
Crash Data ◽  
The Road ◽  
At Home

Stay-at-home policies in response to COVID-19 transformed high-volume arterials and highways into lower-volume roads, and reduced congestion during peak travel times. To learn from the effects of this transformation on traffic safety, an analysis of crash data in Ohio’s Franklin County, U.S., from February to May 2020 is presented, augmented by speed and network data. Crash characteristics such as type and time of day are analyzed during a period of stay-at-home guidelines, and two models are estimated: (i) a multinomial logistic regression that relates daily volume to crash severity; and (ii) a Bayesian hierarchical logistic regression model that relates increases in average road speeds to increased severity and the likelihood of a crash being fatal. The findings confirm that lower volumes are associated with higher severity. The opportunity of the pandemic response is taken to explore the mechanisms of this effect. It is shown that higher speeds were associated with more severe crashes, a lower proportion of crashes were observed during morning peaks, and there was a reduction in types of crashes that occur in congestion. It is also noted that there was an increase in the proportion of crashes related to intoxication and speeding. The importance of the findings lay in the risk to essential workers who were required to use the road system while others could telework from home. Possibilities of similar shocks to travel demand in the future, and that traffic volumes may not recover to previous levels, are discussed, and policies are recommended that could reduce the risk of incapacitating and fatal crashes for continuing road users.

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 Concept and Implementation of a Novel Patch Pump for Insulin Delivery

2019 ◽  
Vol 14 (2) ◽  
pp. 324-327 ◽  
Author(s):  
Sina Ulbrich ◽  
Delia Waldenmaier ◽  
Cornelia Haug ◽  
Guido Freckmann ◽  
Til Rendschmidt ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Insulin Pump ◽  
Insulin Delivery ◽  
The Body ◽  
Customer Needs ◽  
Acting Insulin ◽  
Glucose Meter ◽  
Blood Glucose Meter

With the motivation to provide a small and discreet patch pump that complies with several customer needs, the recently CE-marked Accu-Chek® Solo micropump system was designed. The system consists of a tubeless insulin pump wirelessly controlled by the so-called diabetes manager. Via diabetes manager, basal rates and boluses are programmed; an integrated blood glucose meter and bolus calculator supports users in bolusing and offers several diary functions. The micropump features a quick bolus button for bolus initiation directly on the pump and is complemented by a disposable reservoir holding up to 200 U of rapid-acting insulin. The assembled pump is attached to the body via a pump holder containing soft cannula. The modular principle enables independent replacement of the single components if necessary.

The Predictive Low Glucose Management System in Prevention of Clinically Significant Hypoglycemia in Type 1 Diabetes. A Preliminary Study Identifying the Most Common Events Leading Up to Hypoglycemia During Insulin Pump Therapy

2019 ◽  
Author(s):  
Petros Thomakos ◽  
Asimina Mitrakou ◽  
Olga Kepaptsoglou ◽  
Ibrahim Taraoune ◽  
Carol Barreto ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Insulin Pump ◽  
Insulin Pump Therapy ◽  
Insulin Pumps ◽  
Pump System ◽  
High Blood Glucose ◽  
Low Glucose ◽  
Clinically Significant ◽  
Glucose Management

Abstract Background/aim Prevention of hypoglycemia remains a major challenge in diabetic management, despite the introduction of modern insulin pumps in daily clinical practice. The Low Glucose Suspend (LGS) and the newer Predictive Low Glucose Management (PLGM) systems incorporated in the Medtronic insulin pumps have shown promising results in prevention of hypoglycemia. Our aim was to evaluate the effect of the 2 systems relative to the frequency of clinically significant hypoglycemia in Type 1 diabetes (T1DM). In addition, we investigated the events preceding clinically significant hypoglycemia episodes. Methods A cross-sectional study was conducted in 30 T1DM patients using the MiniMed 640G vs. 30 using the MiniMed Veo sensor-augmented insulin pump. All data was recorded during patients’ normal daily activity and living conditions. The patients were matched for age and duration of diabetes. Results PLGM use was associated with lower incidence of clinically significant hypoglycemia (1.9±1.4 vs. 3.6±1.9 episodes per week), along with reduced exposure to hypoglycemia. The data indicated that both pump systems are effective in preventing severe hypoglycemic episodes. In both groups the most common events preceding hypoglycemic episodes included adjustment of hyperglycemia, basal rate increase and miscalculation of carbohydrates. Conclusions The results indicated that the use of the Minimed 640G pump system can help reduce the frequency of clinically significant hypoglycemia. Management of hyperglycemia must be addressed in diabetes education programs in order to encourage proper adjustment of high blood glucose levels. Future studies would be useful in exploring the details of the events preceding hypoglycemia episodes in insulin pump users.

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