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.

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.

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.

Background and Aims

The aim of this study is to evaluate the usability of the artificial pancreas DBLG1 SYSTEM from Diabeloop based on an analysis of the number of parameters’ changes performed by the patient or its caregiver along the weeks of usage.

Methods

DBLG1 SYSTEM allows patients to modulate some parameters (n=5) to adapt system recommendations to their preferences. For each patient, we extracted the number of changes they made each week of the study (figure A).

The entire dataset [1] was composed of 24 women and 39 men wearing the DBLG1 SYSTEM during 12 weeks.

A hierarchical clustering [2] was applied on the dataset to separate all patients according to the number of changes they made per week, which resulted in 4 clusters. We focused on the biggest cluster: 34 patients representing the main trend in parameters changing (figure B)

Results

Patients changed 7 (± 4.4) parameters on average during the first week and only 2 (± 2.4) parameters in the last week of the clinical study. We observed that less than 3 changes per week were made after 3 weeks (figure A).

After clustering, we isolated 54% of patients that changed on average less than 1 parameter per week after 5 weeks (figure B). After week 5, they stayed below 1 on average : 0,80 (± 1,05) change per week.

Conclusions

We may then consider that the DBLG1 SYSTEM is easy to use, since parameters tuning is mostly performed during the first 5 weeks.

Background and Aims

The digestion and absorption processes play a key role in human glucose homeostasis, mainly comprising the coupled work of the stomach and small intestine. Although 85-90% of carbohydrates digestion and 85% of glucose absorption occur in the small intestine, the rate of digestion and absorption is heavily influenced by chyme flow dynamics and composition (proteins, fats, fiber and carbohydrates) in both stomach and small intestine. The aim is to describe glucose concentration dynamics in the portal vein, given the description of an ingested meal, which is a fundamental work for the construction of an artificial pancreas for diabetes mellitus patients.

Methods

A coupled Phenomenological Based Semi-physical Model (PBSM) of the role of the stomach and intestine in the glucose homeostasis is proposed in order to simulate the change of glucose blood levels in portal vein. This model is based on mass and energy balances and can be adapted to the real physiology of the patient using parameters which possess different levels of interpretability.

Results

The simulation allows to obtain data for chyme transit time, rheological properties, glucose consumption, production and absorption, all along the gastrointestinal tract comprised between the stomach and the small intestine. Using this data, the change of glucose concentration in the portal vein is calculated.

Conclusions

The simulated dynamics of chyme flow behave in accordance to physiological data retrieved from literature, allowing to validate the dynamics of glucose concentration in the portal vein. This data can be further included in an integrated model of glucose homeostasis for artificial pancreas systems.

Background and Aims

Bioelectronic medicine aims to provide real-time and patient-specific therapies to diabetes through recording and modulation of peripheral nerves to improve glycemic fluctuations. This pilot study investigates the impact of stimulation frequency on pancreatic secretion and glucose homeostasis.

Methods

Acute bipolar stimulation (biphasic charge-balanced square pulses, 1.75mA amplitude, 0.5ms pulse width) was applied to the intact left cervical vagus nerve in fasted anesthetized healthy Wistar rats. The impact of two stmulation frequencies was studied (5Hz, 10Hz). Blood glucose, and insulin and glucagon serum concentrations were measured and compared with a control group during baseline (15 min), stimulation (20 min) and post-stimulation (50 min).

Results

Both frequencies resulted in an immediate and sustained increase in glucose levels, the highest frequency showing the greatest percentage of change over baseline (5Hz-stim: 41.3±13.7%; 10Hz-stim: 56.27±13.9%). In neither case this increase was accompanied by a meaningful change in insulin (5Hz-stim: 3.02±0.53ng/mL baseline, 3.13±0.48 ng/mL stimulation; 10Hz-stim: 2.53±0.32ng/mL baseline, 2.57±0.13ng/mL stimulation). Glucagon levels exhibited a decrease during the 10Hz-stim period (1.51±0.04pg/mL baseline, 1.10±0.12pg/mL stimulation), which was not observed in the 5Hz-stim (1.57±0.06pg/mL baseline, 1.50±0.06pg/mL stimulation). In the control group, neither the glucose concentration (change over baseline 1.48±8.61%) nor the insulin (2.98±0.14ng/mL baseline, 3.04±0.11ng/mL sham-stimulation) changed meaningfully during sham-stimulation. Glucagon concentration, however, was reduced (1.50±0.13pg/mL baseline, 1.26±0.14pg/mL sham-stimulation).

Conclusions

These results suggest that the rise in glucose levels after stimulation is mediated by an increase of hepatic glucose release. They also motivate the development of new artificial pancreas that incorporate control of the neural signals for optimal glucose management.

Background and Aims

Interest in artificial pancreas (AP) systems has increased as hybrid-APs have become available for use in daily life. These first-generation systems require manual announcements of meals and exercise, causing management burden to users. Interest in use of additional signals such as heart rate or accelerometer signals to automate and improve AP performance during physical activities is growing. While T1D simulators which accurately model glucose-insulin dynamics exist, they do not provide physiological signals to allow for rapid-prototyping of multivariable AP systems. A multivariable simulator enables rapid advances in multivariable AP research.

Methods

The effect of exercise on glucose dynamics is combined with the Hovorka glucose-insulin dynamic model. Additional models compute physiological signals (heart rate, energy expenditure, and accelerometer values) with their dynamics driven by physical activity. Data for these signals was collected in clinical studies of people with T1D and are used to characterize the interpatient variability and determine realistic parameters for the virtual subjects.

Results

The root mean square error for the original Hovorka model (12.86±6.37mg/dL) is reduced (9.85±5.13mg/dL) when validated against 18 adults with T1D (p=6.4x10^-7). This simulator (mGIPsim) is freely available for academic research. Users of mGIPsim provide the meal and exercise scenarios and insulin infusions. Model equations are then solved to yield the output variables (physiological biosignals, blood glucose concentration, CGM, and plasma insulin concentration).

Conclusions

A multivariable T1D simulator allows for rapid prototyping of physical activity-oriented AP system that can utilize physiological signals such as heart rate or energy expenditure in their algorithms.

Background and Aims

For an artificial pancreas (AP) to effectively limit postprandial glucose excursions, it is necessary that the insulin’s glucose lowering effect starts early in relation to meal onset. Automated and reliable early meal onset detection could therefore enhance the control outcome of APs.

A typical AP depends on continuous glucose monitoring (CGM) for insulin dosing. Because of the slow dynamics of the glucose sensing, current CGM based meal detection approaches typically exhibit a delay of 10 minutes between actual meal onset and reliable detection. In contrast, the processes of ingestion and digestion produce sounds even before meal glucose enters the blood.

Therefore, the focus of the present work is towards the early meal onset detection based on abdominal sounds (AS).

Methods

In this work we employ AS recorded in two healthy volunteers with a condenser microphone, and present an automated approach. We use the Mel-frequency cepstral coefficients and wavelet entropy as features. These features are fed to a feed forward neural network for discriminating the “meal” and “no-meal” classes

Results

This approach detects meal onset with an average delay of 4.3 minutes in our limited number of subjects. Importantly, it provides lesser delay than the state-of-the-art CGM based approach .

Conclusions

Preliminary results indicate that the AS-based approach [1] may provide early meal onset information. This can be exploited in an AP through allowable earlier meal insulin boluses, resulting in improved glycemic control.

References:

Background and Aims

The founder of Inreda Diabetic, manufacturer of a fully-automated bihormonal artificial pancreas system (AP) suffers from type 1 diabetes himself. After further improvements of the AP tested before in ten patients at home, he started AP therapy in November 2018 and has been using it ever since. To our knowledge a bihormonal AP has not yet been used for such a long period.

Methods

This case report describes self-experimentation during daily life. Patient’s treatment before using the AP consisted of multiple daily insulin injections and SMBG. The AP, which uses two sensors that continuously monitor the glucose level and administers insulin or glucagon accordingly, stores the glucose values and sends this to a secured server. HbA1c values were measured during regular hospital visits.

Results

Presented values are median [IQR] values over the period from November 18, 2018 until September 30, 2019. The daily time in range (3.9-10 mmol/l) was 92.6 [88.1 – 96.7]% , the median glucose was 7.1 [6.7 – 7.5] mmol/l. The daily time in hypoglycemia was 0.0 [0.0 – 1.0]%. Last measured HbA1c before AP therapy was 66 mmol/mol. Six weeks after the start of AP therapy the HbA1c was 54 mmol/mol and then remained stable.

Conclusions

The bihormonal AP provides good long-term glucose control in this patient. The improved HbA1c values indicate clear health benefits for this patient. Although long-term data is only available for one patient, we expect that the AP will provide good long-term glucose control in other patients with type 1 diabetes as well.

Background and Aims

Artificial pancreas is considered as the state-of-the-art treatment for type-I diabetes while islets transplantation (IT) is the only curative method. IT is associated with significant drawbacks, primarily tissue availability and mandatory use of immunosuppressive drug therapy. The first could be met by employing stem-cell-derived products or porcine islets, the second – by separating the graft from the host immune system. Using parting approach renders the graft avascular so nutrients and waste products are transferred across the membrane by diffusion only. Exercising minimally invasive surgery, encapsulated islets are implanted into an oxygen-poor subcutaneous site. Islets cells, however, are metabolically active and their functionality is oxygen-dependent.

Methods

To meet regulatory, medical and functional requests, we developed a retrievable BAP macro-device - the βAir. It includes three modules: islets, air chamber, and membrane. Gaseous oxygen is supplied to the islets from the air chamber.

Results

We evaluated the potency of the βAir BAP to cure experimental diabetes in allogeneic small animal models for a period of six months. Xenogeneic islets were implanted into mini-swine and monkeys with remarkable results. Two clinical trials, using minimal islets dose demonstrated clear clinical advantage.

Conclusions

Altogether, the capacity of the technology to achieve close to normal control over blood glucose in diabetic models was demonstrated. The direction towards a commercial BAP is understood. We now present Gen2 BAP in which building materials were optimized; the one-piece device was separated into its components – the islets module and the air chamber. Clinical trials using this device will commence in two years.

Background and Aims

Exercise remains challenging to current generation closed-loop (CL) systems relying on glucose as the sole measured input determining insulin delivery. Interstitial lactate may be an additional signal modulating insulin delivery with exercise. We aimed to explore the feasibility of continuous interstitial lactate measurements and their relationship to venous lactate in individuals with T1D during exercise.

Methods

Six adults with T1D (mean ± SD; age: 40.0 ± 9.5y; HbA_1c: 7.6 ± 1.3%) had a prototype optochemical continuous lactate monitor (CLM) inserted subcutaneously in their flank. All participants undertook 40min high intensity exercise. Forearm venous samples for lactate measurement by YSI analyser were collected at 20min intervals from exercise commencement until 240min post-exercise. Exploratory comparisons between CLM and venous lactate profiles included comparisons of time-to-peak and lag-time.

Results

Preliminary data was analysed from six participants. Unacceptable signal loss occurred in two participants post-exercise, with data only included for time-to-peak analysis. There was high variability in lag-time of CLM versus venous lactate, with a difference in time-to-peak ranging from -11 (faster in CLM) to +47 min (n=6) and lactate clearance ranging from -40 (faster in CLM) to +114min (n=4).

Conclusions

This early data suggests that interstitial lactate as measured by a prototype CLM in T1D participants undertaking high intensity exercise mirrored the rise and fall in venous lactate with variable lag. This lag appeared greater when lactate levels were falling post-exercise. These differences between interstitial and venous lactate may have implications for interstitial lactate as a CL additional signal candidate.

Background and Aims

INTRODUCTION: Diabetes technology improves glycaemic control. However, hypoglycaemia remains the main challenge for optimizing it. Integrated systems such as Do It Yourself (DIY) Artificial Pancreas (AP), known worldwide although not FDA approved, can be a major breakthrough in overcoming this barrier.

Methods

METHODS: We present data from a patient using DIY AP (hybrid closed-loop system) consisting of a Roche Combo pump with faster insulin aspart (Fiasp), linked to Dexcom G6 CGM and an open source app that acts as an AP system (Android APS). Real time access to CGM data is provided via Nightscout Open Source (CGM in the cloud). We compare glycaemic data before and after AP system.

Results

RESULTS: 42-year-old male with type 1 DM. Diabetes duration of 28 years, basal-bolus insulin therapy Degludec/Lispro, with good metabolic control but high frequency of hypoglycaemias. Last 3 months FreeStyle Libre Flash CGM readings showed: Mean of 15 scans/day. Estimated Hba1c 5.5%.228 low glucose events. 104 min of time spent in hypoglycaemia. Time in range (TIR) 77% (70-180 mg/dl), 16% below and 7% above target. Hypoglycaemic events were systematically more than 3/day, several of them <54 mg/dl, various were severe. With AP system, Nightscout 3 months reporting showed a significant improve in TIR (77% to 93.2%), and in low values (16% to 4.0%), these averaged 61.1 +/- 6.9 mg/dl. Estimated Hba1c 5.4%.0 severe hypoglycaemias.

Conclusions

CONCLUSION: Elimination of hypoglycaemia is a major challenge in type 1 DM. AP system shows promising results demonstrating a reduction in hypoglycaemia, improving glycaemic control and quality of life.

Background and Aims

Light-emitting diode (LED) phototherapy regenerates pancreatic islets and alters carbohydrate metabolism Phototherapy has shown good results for cell proliferation and regeneration.We investigated the effects of LED (LED) irradiation in the pancreas injured to induction of experimental diabetes and we evaluated the morphological changes in pancreatic β cells.

Methods

For the experiment, we used twenty randomly selected Wistar rats in three groups: non-diabetic diabetic and diabetic control treated with LED Diabetes was induced by injection of streptozotocin. The irradiated group was treated with LED (λ = 805 nm; 40 mW, 22 s; 0.88 J), applied to the anatomical area of the pancreas for 5 consecutive days and evaluated after 30 days.

Results

Islet and duct regeneration in the pancreas was observed after 30 days in the diabetic group treated with LED, and this regeneration was statistically significant when compared to the control group (p = 0.01). In the diabetic control group, hepatic glycogen content was lower when compared to diabetics with LED (p = 0.03). When performing the intraperitoneal insulin tolerance test, we observed differences between diabetic control and diabetic treatment groups (p = 0.03).

Conclusions

This study demonstrated that LED phototherapy allowed regeneration of pancreatic tissue, especially pancreatic islets and altered carbohydrate metabolism in an experimental model.