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INCORPORATION OF INTRAPERITONEAL INSULIN DELIVERY IN THE UVA/PADOVA TYPE 1 DIABETES SIMULATOR: MODEL PREDICTIVE CONTROL IN SILICO TRIALS VS THE SUBCUTANEOUS ROUTE

Session Name
ARTIFICIAL PANCREAS
Session Type
E-POSTER VIEWING (EXHIBITION HOURS)
Date
20.02.2020, Thursday
Session Time
09:30 - 15:30
Channel
E-Poster Area
Lecture Time
09:54 - 09:55

Abstract

Background and Aims

An Artificial Pancreas usually involves subcutaneous (sc) devices to measure glucose and to infuse insulin with important delays. The intraperitoneal (ip) route is more physiological and would avoid the sc delays, improving glucose control[A]. In these last years, new ip devices have been designed[B] and new modalities of ip insulin delivery, e.g pulsatile, have been tested. The aim here is to present the new simulator and its first use in in silico trial comparing the ip vs. sc insulin delivery route.

[A]Dassau, E. et al. Diabetes,Obesity and Metabolism,19.12(2017):1698-1705.

[B]Iacovacci V. et al. Journal of Medical Devices,13.1(2019):011008.

Methods

The model of the UVA/Padova simulator has been modified to describe ip insulin administration. A Run-to-Run approach is used to adapt the Basal-Bolus Therapy (BBT) of the 100 in silico patients to the new ip site. A new version of the MPC controller [C] is synthesised using the new simulator and the optimized BBT.

[C] Soru P. et al. Annual Reviews in Control,36.1(2012):118-128.

Results

The intraperitoneal controller tested on a 2 days scenario maintains the glucose inside the target range for 93.5% of the time with no time spent below 70 mg/dl and 6.5% above 180 mg/dl. The MPC is able to keep the glycaemia inside the target range during all night.

Conclusions

The ip MPC results are much better than those obtained with the sc MPC. Future development of MPC involves the design of ad hoc constraints and safety. This new MPC in conjunctions with a new ip insulin pump will be tested in animals.

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INCORPORATING PHYSICAL ACTIVITY AND STRESS ESTIMATES TO IMPROVE GLUCOSE PREDICTIONS FOR MULTIVARIABLE ARTIFICIAL PANCREAS SYSTEMS

Abstract

Background and Aims

Maintaining glucose concentration (GC) in the target range in spite of physical activities and events causing acute psychological stress (PS) is challenging for artificial pancreas (AP) systems. PS and physical activities affect GC in different ways; aerobic exercise decreases GC while PS can increase it. Many stressful events and physical activities cannot be manually entered to the AP in a timely manner. Hence, they are unknown disturbances for AP systems and reduce glycemic control. In this work, wristband biosignals are utilized in a novel algorithm to estimate the psychological and physiological state of a subject, and improve the GC prediction for use in AP systems.

Methods

Biosignals from Empatica E4 wristband are collected in real-time and machine learning algorithms are utilized to determine the physical state of a subject, obtain energy expenditure estimates, and predict her/his PS levels. These estimates are incorporated in a GC prediction model along with CGM readings and insulin infusion data from pump. These BGC estimates are compared to estimates from a model that uses only CGM readings and insulin infusion data.

Results

Data from 50 experiments with thirteen different subjects with T1D who performed physical activities and various PS causing events were used and proposed method improved to mean absolute percentage error of GC prediction by 6.5%.

Conclusions

Wristband biosignals used to determine the psychological and physiological state of people with T1D provide valuable information to improve GC estimates and the performance of an AP system in response to unannounced physical activities and stressful events.

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PERFORMANCE OF THE DIABELOOP ARTIFICIAL PANCREAS IS NOT CORRELATED TO AGE, BODY WEIGHT, SEX, OR EXERCISE

Session Name
ARTIFICIAL PANCREAS
Session Type
E-POSTER VIEWING (EXHIBITION HOURS)
Date
20.02.2020, Thursday
Session Time
09:30 - 15:30
Channel
E-Poster Area
Lecture Time
09:51 - 09:52

Abstract

Background and Aims

The aim of this study is to evaluate whether T1D patients’ characteristics such as age, body weight (BW), Sex, and time in physical activity (TPA) have effect on the performance of the Diabeloop Artificial Pancreas (AP) based on data from clinical trial (NCT02987556).

Methods

Linear correlation was computed between age, BW, and TPA (1) vs time in range (TIR (2)), and time in hypoglycemia (TIHYPO (3)), to demonstrate that there is not a linear dependency between performance and age, BW, and TPA. To demonstrate that patient's sex has no effect on performance of the Diabeloop AP the Kruskal-Wallis H-test was computed to evaluate statistical difference.

The dataset is composed of 24 women and 39 men wearing the Diabeloop AP during 3 months. Patients’ characteristics were (mean, std): age (49.21, 13.36) years old, BW (70.11, 11.17) kg, and TPA (1.38, 1.68) %.

Results

There is no linear correlation between TIR and age (r = 0.01), BW (r = 0.25), and TPA (r = 0.02) neither between TIHYPO and age (r = 0.09), BW (r = 0.15), and TPA (r = 0.01). We observe that there is no significant difference between the performance reached by the Diabeloop AP for women and men (p value of 0.38 and 0.6 for TIR and TIHYPO respectively).

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Conclusions

The Diabeloop AP allowed to correctly perform on a variety of T1D patients despite their age, BW, TPA and sex, showing that the Diabeloop’s algorithm is not biased by these factors.

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A PROBABILISTIC FRAMEWORK TO DESIGN REALISTIC MEAL SCENARIOS IN IN SILICO TYPE 1 DIABETES (T1D) FREE-LIVING TRIALS

Session Name
ARTIFICIAL PANCREAS
Session Type
E-POSTER VIEWING (EXHIBITION HOURS)
Date
20.02.2020, Thursday
Session Time
09:30 - 15:30
Channel
E-Poster Area
Lecture Time
09:30 - 09:31

Abstract

Background and Aims

Clinical trials in free-living conditions is key in the development of an Artificial Pancreas (AP) for T1D subjects. Since the scenario plays a key role in the synthesis and validation of AP control algorithms, a probabilistic approach is proposed to automatically design meal scenarios. In particular, we exploit our real-life data to design realistic in silico scenarios.

Methods

The amount and time-of-day of ingested carbohydrates in a 1-month in 13 patients for a total of 1500 meals. have been considered. The joint distribution of these variables has been estimated via a copula function, in order to model their dependence. The use of a copula allows to generate Monte Carlo scenarios by drawing random samples, which represent a pair of amount and time-of-day.

Results

A Gaussian copula resulted suitable for the description of the dependence in the meal dataset with a p-value of 0.005 according to the χ2 test based on Rosenblatt’s transformation. A bootstrap version of the test shows that the estimate of the Spearman correlation coefficient (ρ) is sufficiently accurate with respect to the correlation (ρ) directly computed from the data (ρ=0.13, ρ=0.12).

Conclusions

The availability of a copula statistical model able to represent the food habits of a T1D population allows to design realistic eating patterns to run in silico simulations under free-living conditions.

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INTRAPERITONEAL AND SUBCUTANEOUS GLUCAGON DELIVERY IN ANAESTHETIZED PIGS: EFFECTS ON CIRCULATING GLUCAGON AND GLUCOSE LEVELS

Session Name
ARTIFICIAL PANCREAS
Session Type
E-POSTER VIEWING (EXHIBITION HOURS)
Date
20.02.2020, Thursday
Session Time
09:30 - 15:30
Channel
E-Poster Area
Lecture Time
09:31 - 09:32

Abstract

Background and Aims

Glucagon has received renewed interest, particularly in the development of a dual hormone artificial pancreas (AP). Slow subcutaneous (SC) dynamics motivates for exploration of the intraperitoneal (IP) space both for glucose sensing and hormone delivery. We previously investigated IP glucagon delivery in rats [1]. Now we compared glucose dynamics after IP and SC glucagon delivery in a swine model.

Methods

Ten anaesthetized, non-diabetic, somatostatin-analogue treated pigs (35–50 kg) were, in random order, given glucagon boluses of 0.6 µg/kg IP, 0.3 µg/kg IP, and 0.6 µg/kg SC. At last, 1 mg IP glucagon was given to test maximum glucose response.

Results

Only 17 of 28 IP boluses and nine of 10 SC boluses had a glucose increasing effect. We believe this is due to prolonged fasting causing depletion of hepatic glycogen. Hence, we excluded four pigs from further analysis. The mean maximum effect on glucose for the remaining six pigs was 2.4, 2.2 and 1.6 mmol/L for 0.6 µg/kg IP, 0.3 µg/kg IP and 0.6 µg/kg SC glucagon, respectively.

Glucose increase after 14 to 30 minutes was significantly larger for the 0.6 µg/kg IP bolus compared to the equally sized SC bolus. In some pigs, a marked “first-pass-effect” is observed after IP glucagon.

Conclusions

Results indicates that adequate glucose responses by IP glucagon is achieved by smaller doses, potentially avoiding side effects of glucagon treatment by resembling physiologic glucagon secretion and distribution [2].

Further data on glucagon levels in blood following the different boluses will be presented.

References:

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BACKSTEPPING CONTROLLER DESIGN FOR AUTOMATIC STABILIZATION OF BLOOD-GLUCOSE LEVEL USING ARTIFICIAL PANCREAS IN TYPE 1 DIABETES

Session Name
ARTIFICIAL PANCREAS
Session Type
E-POSTER VIEWING (EXHIBITION HOURS)
Date
20.02.2020, Thursday
Session Time
09:30 - 15:30
Channel
E-Poster Area
Lecture Time
09:32 - 09:33

Abstract

Background and Aims

To regulate blood glucose of a diabetic patient; artificial pancreas is used to externally infuse insulin in the patient body. This work presents the design and analysis of the nonlinear controller that enables the automatic regulation of blood glucose level in type-1 diabetic patients.

Methods

We have proposed a Lyapunov based nonlinear Backstepping controller. In Berman’s Minimal Model, the meal disturbance phenomenon is considered as fixed value. One of the enhancements that we have introduced is the annexure of the variable meal disturbance as a dynamic state to the existing BMM. The asymptotic stability of the system is proven via mathematical analysis using Lyapunov theory.

Results

To demonstrate the performance of the proposed controller, simulations are carried out through MATLAB/Simulink and results of the proposed controller has been compared with PID controller.

Conclusions

The propsed nonlinear controller enables the automatic regulation of blood glucose level far better than PID controller.

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SLIDING MODE PLUS BACKSTEPPING CONTROLLER FOR ARTIFICIAL PANCREAS IN TYPE 1 DIABETES

Session Name
ARTIFICIAL PANCREAS
Session Type
E-POSTER VIEWING (EXHIBITION HOURS)
Date
20.02.2020, Thursday
Session Time
09:30 - 15:30
Channel
E-Poster Area
Lecture Time
09:33 - 09:34

Abstract

Background and Aims

Diabetes Type 1 is caused when body is deficient of required insulin quantity to maintain blood glucose level; due to unavailability of Pancreatic
beta cells. Artificial Pancreas facilitates Type 1 diabetes Mellitus to have automatic stabilization of blood glucose level using some controller. In this research work, we have proposed Backstepping Sliding Mode Controller for Artificial Pancreas in Type 1 diabetes Mellitus.

Methods

We have used Extended Bergman’s Minimal Model that presents the relation between glucose and insulin for Type 1 Diabetic patient with fixed known meal disturbance but have meal disturbance as a 4th state. Then we designed Lyapunov based robust backstepping nonlinear controller for stabilization of blood-glucose level.

Results

The analysis through Lyapunov theory proves the global asymptotic stability of the system. The proposed controller has been compared with PID controller in MATLAB/Simulink.

Conclusions

The performance of the proposed controller has been proved to be far better than conventional PID controller.

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EFFECTS OF SLEEP ON DAYTIME GLYCEMIC CONTROL IN PEOPLE WITH TYPE 1 DIABETES

Abstract

Background and Aims

There is a complex relationship between sleep and diabetes. Most research reported focuses on changes in insulin sensitivity and type 2 diabetes. Relationships between sleep and daytime glycemic control in people with type 1 diabetes (T1D) must be understood in a similar quantitative way to incorporate new modules into a multivariable artificial pancreas (mAP) to achieve better glycemic regulation.

Methods

Subjects with T1D ages 18-65 are monitored for the weekdays of three weeks. Each participant wore an at-home automatic sleep-staging device and a CGM. Participants maintained constant activity schedules and meal compositions across the study. Quantitative descriptive features, including insulin sensitivity, were developed with the meal, insulin and CGM data along with the corresponding previous night of sleep data. K-means clustering and linear regression was used to determine relationships between sleep characteristics and daytime glycemic control. Analysis was done across the entire group and on each individual participant.

Results

When analyzed together, there were no common effects sleep characteristics had on daytime glycemic control. However, when analyzed individually, participants all had distinct clusters of data that showed sleep influenced their next day glycemic regulation. Furthermore, most individuals exhibited unique relationships with differing sleep quality characteristics including measures such as sleep efficiency, time in light sleep and total sleep time.

Conclusions

These results suggest that sleep has distinct individualized effects in people with T1D. These results show a potential need for personalized sleep effect models to be implemented in mAP systems to enhance daytime glycemic control.

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REAL-LIFE USE AND PERFORMANCE OF THE MINIMEDTM 670G SYSTEM IN EUROPE

Session Name
ARTIFICIAL PANCREAS
Session Type
E-POSTER VIEWING (EXHIBITION HOURS)
Date
20.02.2020, Thursday
Session Time
09:30 - 15:30
Channel
E-Poster Area
Lecture Time
09:36 - 09:37

Abstract

Background and Aims

Auto Mode use during the MiniMedTM 670G system clinical trials, in patients with type 1 diabetes (T1D) aged ≥7 years, demonstrated improved glycated hemoglobin levels and time spent in the target glucose range of 70-180 mg/dL (TIR), compared to Manual Mode (sensor-augmented pump therapy).1,2 Following the introduction of the system in Europe on October 2018, a performance assessment of real-life MiniMed™ 670G system use was conducted.

Methods

Data uploaded voluntarily to CareLinkTM Personal software from 01 October 2018 to 14 August 2019 by individuals living in Europe, who provided consent for their data to be aggregated, were analyzed. The percentage of time spent in the various glycemic ranges, mean sensor glucose (SG) levels, and the associated Glucose Management Indicator (GMI, the calculated estimate of HbA1c) were assessed when Auto Mode was turned OFF and when Auto Mode was turned ON.

Results

Data from 4’959 individuals living in 10 different countries were included in the analysis. When the Auto Mode feature was turned ON (4’369 individuals), mean SG was 151 mg/dL, corresponding to a GMI of 6.9%. The TIR was 73.1%, time spent <70 mg/dL was 2.3%, and time spent >180 mg/dL was 24.7%. Time spent at <54 mg/dL was 0.6%, representing less than10 minutes per day. These outcomes were similar for each of the countries.

Conclusions

European individuals using the MiniMed™ 670G system with the Auto Mode feature turned ON achieved internationally-recommended goals of glycemic control with TIR >70% and a GMI of <7%, while minimizing hypoglycemia.

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THE METABOLIC EFFECTS OF CONTINUOUS INTRA-PERITONEAL INSULIN INFUSION, A SYSTEMATIC REVIEW

Session Name
ARTIFICIAL PANCREAS
Session Type
E-POSTER VIEWING (EXHIBITION HOURS)
Date
20.02.2020, Thursday
Session Time
09:30 - 15:30
Channel
E-Poster Area
Lecture Time
09:37 - 09:38

Abstract

Background and Aims

Continuous intraperitoneal insulin administration (CIPII) has been used for decades but in a limited number of patients with type 1 diabetes mellitus (DM1). There exist many reports regarding the effects of CIPII, mostly compared to treatment with continuous subcutaneous insulin infusion (CSII) and/or multiple daily injections (MDI). However, a systematic review comparing metabolic effects of CIPII and CSII is missing.

Methods

In this systematic review we addressed all available studies which has been published before October 1, 2019, comparing metabolic effects between CIPII and CSII in DM1 patients.

No restrictions were made regarding age, gender or any other patient characteristics. Main comparators were long-term glucose control (at least 3 months on IPII) measured by HbA1c and short-term (one day for each intervention) for insulin absorption. For comparison for randomized studies, the Cochrane collaboration tools were used; for observational studies, the STROBE statement checklist was used; for case reports and case series IHE the Quality appraisal checklist was used.

Results

We give an overview of all available articles of CIPII and CSII, we summarize all observed metabolic effects, and the prevalence of technical complications where this was reported.

First main finding was that HbA1c levels tend to improve in both routes (CIPII and CSII) when DM1 patients are followed up throughout the period of time. Second main finding was that values of free insulin tend to be more rapid, increase higher with shorter period of elevation and shows lower level in plasma when used intraperitoneal route.

Conclusions

More information will be provided at the ATTD.

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DIETARY FAT AND GLUCOSE EXCURSIONS IN PATIENTS USING A CLOSED LOOP SYSTEM

Session Name
ARTIFICIAL PANCREAS
Session Type
E-POSTER VIEWING (EXHIBITION HOURS)
Date
20.02.2020, Thursday
Session Time
09:30 - 15:30
Channel
E-Poster Area
Lecture Time
09:38 - 09:39

Abstract

Background and Aims

Currently most hybrid closed-loop (HCL) insulin delivery systems base the meal bolus solely on the carbohydrate (CHO) content. We explored the glycemic response to dinners with high fat (>30 grams: HF) compared to non-high fat meals (<=30 grams: non-HF) for 8 hours following dinners during a HCL study. The study design required at least half the meals to be high fat.

Methods

There were twenty participants ages 6-61 years old (45% female) in an outpatient, supervised clinical trial. The CHO, protein and fat content of each meal was recorded by the medical staff, using food labels. We used regression techniques to evaluate whether high fat meals were associated with a delayed peak glucose and the time to peak. Because of repeated measurements within participants, we used a generalized linear mixed model.

Results

There were 25 HF dinners and 12 non-HF dinners. Using linear regression, adjusted for carbohydrate content and insulin dosing, there was no association between peak glucose and time to peak and the fat content. We observed a significant difference HF and non-HF meals in glucose levels at each time point between 75 to 205 minutes.

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Conclusions

In this analysis there was no delay in the time to peak glucose with HF meals, mainly because there was no early peak in glucose with non-HF meals. This may be due to the small non-HF meal sample size, with 7 of the 12 meals having 25-30 grams of fat. Further studies with lower fat meals are required.

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DIABELOOP CLOSED LOOP SYSTEM ALLOWS PATIENTS WITH DIABETES TYPE 1 (DT1) TO PRACTICE PHYSICAL ACTIVITY (PA) WITHOUT INCREASING HYPOGLYCAEMIC RISK

Abstract

Background and Aims

Is the closed-loop system DBLG1 able to reduce hypoglycaemic risk in case of physical activity (PA) in patients with T1D ?

Methods

We conducted a 3 months crossover trial where patients were using either a hybrid monohormonal system (CellNovo® or Kaleido® pump and Dexcom G5® sensor) using MPC-based algorithm and centralized remote monitoring, or an open loop. Patients were encouraged to practice PA, but it was recommended to announce in advance to the system, the occurrence, intensity and duration of PA.

Results

68 patients (27 men, age 47.2±13.4 years, HbA1c 7.6±0.9%, were included, and 63 were analyzed (mITT). The median number of PA events per patient during the study was 10, median duration 60 mn, intensity light (40%), medium (42%) intense (19%). Time in range (TIR) (70-180 mg/dl) was similar with (68.2 ± 1.1%) or without (69.1 ± 1.1%) PA, as was TIR<70 mg/dl during the day (2.3 ± 0.2% v 2.4 ± 0.2%) or the night (1.2 ± 0.2% v 1.6 ± 0.2%). TIR<70 mg/dl was 1.9, 2.1, 1.9 and 2.0% following PA duration of <30mn, 30 to 60, 60 to 90 or >90 mn, and 1.6, 2.2 or 2.2% following light, medium or intense PA. TIR<70 mg/dl was 2.2, 2.3 and 1.7% with announcement <30, 30 to 60 and > 60 mn before PA and 2.3% with none.

Conclusions

The Diabeloop’s DBLG1 System is able to maintain good glycemic control even in the case of PA practice. Duration, intensity or PA announcement demonstrated modest impact.

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