The challenges of achieving postprandial glucose control using closed-loop systems in patients with type 1 diabetes

Postprandial Glucose Control With Different Hybrid Closed-Loop Systems According to Type of Meal in Adults With Type 1 Diabetes

BACKGROUND

Hybrid Closed-Loop Systems (HCLs) may not perform optimally on postprandial glucose control. We evaluated how first-generation and advanced HCLs manage meals varying in carbohydrates, fat, and protein.

METHOD

According to a cross-sectional design, seven-day food records and HCLs reports from 120 adults with type 1 diabetes (MiniMed670G: n = 40, MiniMed780G: n = 49, Control-IQ [C-IQ]: n = 31) were analyzed. Breakfasts (n = 570), lunches (n = 658), and dinners (n = 619) were divided according to the median of their carbohydrate (g)/fat (g) plus protein (g) ratio (C/FP). After breakfast (4-hour), lunch (6-hour), and dinner (6-hour), continuous glucose monitoring (CGM) metrics and early and late glucose incremental area under the curves (iAUCs) and delivered insulin doses were evaluated. The association of C/FP and HCLs with postprandial glucose and insulin patterns was analyzed by univariate analysis of variance (ANOVA) with a two-factor design.

RESULTS

Postprandial glucose time-in-range 70 to 180 mg/dL was optimal after breakfast (78.3 ± 26.9%), lunch (72.7 ± 26.1%), and dinner (70.8 ± 27.3%), with no significant differences between HCLs. Independent of C/FP, late glucose-iAUC after lunch was significantly lower in C-IQ users than 670G and 780G (P < .05), with no significant differences at breakfast and dinner. Postprandial insulin pattern (Ins3-6h minus Ins0-3h) differed by type of HCLs at lunch (P = .026) and dinner (P < .001), being the early insulin dose (Ins0-3h) higher than the late dose (Ins3-6h) in 670G and 780G users with an opposite pattern in C-IQ users.

CONCLUSIONS

Independent of different proportions of dietary carbohydrates, fat, and protein, postprandial glucose response was similar in users of different HCLs, although obtained through different automatic insulin delivery patterns.

An Automated Insulin Delivery System with Automatic Meal Bolus Based on a Hand-Gesturing Algorithm

Background: Carbohydrate counting (CC) and meal announcements, before eating, introduce a significant burden for individuals managing type 1 diabetes (T1D). An automated insulin delivery system with automatic bolusing that eliminates the need for CC and premeal bolusing (i.e., a hands-free closed-loop [HFCL] system) was assessed in a feasibility trial of adults with T1D. Methods: The system included the MiniMed™ 780G pump and a smartphone-paired smartwatch with the Klue application (Klue, Inc.) that detects eating and drinking gestures. A smartphone algorithm converted gestures into carb amounts that were transmitted to the pump for automatic bolusing. For 5 days, participants (N = 17, 18-75 years of age) used the system at home with meal announcements based on traditional CC, with the Klue application disabled (Home-stay phase). Thereafter, participants moved to a supervised hotel setting, where the Klue application was enabled for 5 days and meals were not announced (Hotel-stay phase). Participants consumed the same eight test meals (six solid and two liquid) of varying caloric and carb size at the same time and day of the week for both phases, and glycemic metrics were compared. Otherwise, there were no other meal restrictions. Results: The overall time in range (70-180 mg/dL) was 83.4% ± 7.0% and 80.6% ± 6.7% for the Home-stay and Hotel-stay, respectively (P = 0.08). The average time at <70 mg/dL was 3.1% and 3.0% (P = 0.9144), respectively, and the average time at >180 mg/dL was 13.5% and 16.3% (P = 0.1046), respectively. Postprandial glycemia following low-carb test meals was similar between the two phases. The system's ability to accommodate high-carb meals was somewhat limited. There were no episodes of severe hypoglycemia or diabetic ketoacidosis. Conclusion: Preliminary findings show that a HFCL system was safe and maintained overall glycemic control, similar to that observed with traditional CC and manual meal bolusing. By eliminating these daily T1D burdens, a HFCL system may improve quality of life for individuals with T1D. ClinicalTrials.gov number: NCT04964128.

Delayed prandial insulin boluses are an important determinant of blood glucose control and relate to fear of hypoglycemia in people with type 1 diabetes on advanced technologies

AIMS

Automated insulin delivery systems improve blood glucose control in patients with type 1 diabetes (T1D). However, optimizing their performance requires patient's proper compliance to meal insulin bolus administration. We explored real-life prevalence of delayed prandial boluses (DBs) in adults with T1D on advanced technologies, and their association with glycemic control and fear of hypoglycemia (FH).

METHODS

In the last two-week web-based reports of 152 adults with T1D on Hybrid Closed Loop Systems (HCLS) or Sensor Augmented Pump (SAP), DBs were identified when a steep increase in blood glucose occurred at CGM before the prandial bolus, and CGM metrics were evaluated. All participants completed an online questionnaire on FH.

RESULTS

Mean DBs over two weeks were 10.2 ± 4.7 (M ± SD, range 1-23) and more frequent in women than men (11.0 ± 4.6 vs. 9.4 ± 4.7, p = 0.036). Participants with more DBs (>12) showed significantly lower Time-In-Range (62.4 ± 13.8 vs. 76.6 ± 9.0 %) than those with less DBs (<7.7), along with higher Time-Above-Range, GMI, and Coefficient-of-Variation (ANOVA, p < 0.001 for all). Participants with higher FH score showed more DBs (11.6 ± 5.0) than those in lower tertiles (9.57 ± 4.59 and 9.47 ± 4.45, ANOVA p = 0.045).

CONCLUSIONS

In patients on advanced technologies, delayed boluses are extremely common, and associate with significantly worse glycemic control. Utmost attention is needed to bolus timing, mainly tackling fear of hypoglycemia.

T1DiabetesGranada: a longitudinal multi-modal dataset of type 1 diabetes mellitus

Type 1 diabetes mellitus (T1D) patients face daily difficulties in keeping their blood glucose levels within appropriate ranges. Several techniques and devices, such as flash glucose meters, have been developed to help T1D patients improve their quality of life. Most recently, the data collected via these devices is being used to train advanced artificial intelligence models to characterize the evolution of the disease and support its management. Data scarcity is the main challenge for generating these models, as most works use private or artificially generated datasets. For this reason, this work presents T1DiabetesGranada, an open under specific permission longitudinal dataset that not only provides continuous glucose levels, but also patient demographic and clinical information. The dataset includes 257 780 days of measurements spanning four years from 736 T1D patients from the province of Granada, Spain. This dataset advances beyond the state of the art as one the longest and largest open datasets of continuous glucose measurements, thus boosting the development of new artificial intelligence models for glucose level characterization and prediction.

A Nutritional Approach to Optimizing Pump Therapy in Type 1 Diabetes Mellitus

Achieving optimal glucose control in individuals with type 1 diabetes (T1DM) continues to pose a significant challenge. While continuous insulin infusion systems have shown promise as an alternative to conventional insulin therapy, there remains a crucial need for greater awareness regarding the necessary adaptations for various special circumstances. Nutritional choices play an essential role in the efficacy of diabetes management and overall health status for patients with T1DM. Factors such as effective carbohydrate counting, assessment of the macronutrient composition of meals, and comprehending the concept of the glycemic index of foods are paramount in making informed pre-meal adjustments when utilizing insulin pumps. Furthermore, the ability to handle such situations as physical exercise, illness, pregnancy, and lactation by making appropriate adjustments in nutrition and pump settings should be cultivated within the patient-practitioner relationship. This review aims to provide healthcare practitioners with practical guidance on optimizing care for individuals living with T1DM. It includes recommendations on carbohydrate counting, managing mixed meals and the glycemic index, addressing exercise-related challenges, coping with illness, and managing nutritional needs during pregnancy and lactation. Additionally, considerations relating to closed-loop systems with regard to nutrition are addressed. By implementing these strategies, healthcare providers can better equip themselves to support individuals with T1DM in achieving improved diabetes management and enhanced quality of life.

Participant Experiences of Low-Dose Empagliflozin Use as Adjunct Therapy to Hybrid Closed Loop: Findings From a Randomized Controlled Trial

BACKGROUND

Very few patient-reported outcomes have been published in regard to opinions of individuals with type 1 diabetes concerning adjunctive therapy. The aim of this subanalysis was to qualitatively and quantitatively assess the thoughts and experiences of participants with type 1 diabetes who have used low doses of empagliflozin as an adjunct to hybrid closed-loop therapy.

METHODS

Semi-structured interviews were performed with adult participants who completed a double-blinded, crossover, randomized controlled trial using low-dose empagliflozin as an adjunct to hybrid closed-loop therapy. Participant experiences were captured through qualitative and quantitative methods. A descriptive analysis was performed using a qualitative approach; attitudes toward relevant topics were extracted from interview transcripts.

RESULTS

Twenty-four participants were interviewed; 15 (63%) perceived differences between interventions despite blinding, due to glycemic control or side effects. Advantages that arose were better glycemic control, in particular postprandially, requiring less insulin, and ease of use. Disadvantages were thought to be adverse effects, increased incidence of hypoglycemia, and increased pill burden. Thirteen (54%) participants were interested in using low-dose empagliflozin beyond the study.

CONCLUSIONS

Many participants had positive experiences with low-dose empagliflozin as an adjunct to the hybrid closed-loop therapy. A dedicated study with unblinding would be beneficial to better characterize patient-reported outcomes.

Impact on glucometric variables and quality of life of the advanced hybrid closed-loop system in pediatric and adolescent type 1 diabetes

BACKGROUND

In recent years, technological advances in the field of diabetes have revolutionized the management, prognosis, and quality of life of diabetes patients and their environment. The aim of our study was to evaluate the impact of implementing the MiniMed 780G closed-loop system in a pediatric and adolescent population previously treated with a continuous subcutaneous insulin infusion pump and intermittent glucose monitoring.

METHODS

Data were collected from 28 patients with type 1 diabetes aged 6 to 17 years, with a follow-up of 6 months. We included both glucometric and quality of life variables, as well as quality of life in primary caregivers. Metabolic control variables were assessed at baseline (before system change) and at different cutoff points after initiation of the closed-loop system (48 hours, 7 days, 14 days, 21 days, 1 month, 3 months, 6 months).

RESULTS

Time in range 70-180 mg/dL increased from 59.44% at baseline to 74.29% in the first 48 hours after automation of the new system, and this improvement was maintained at the other cutoff points, as was time in hyperglycemia 180-250 mg/dL (24.44% at baseline to 18.96% at 48 hours) and >250 mg/dL (11.71% at baseline to 3.82% at 48 hours).

CONCLUSIONS

Our study showed an improvement in time in range and in all time spent in hyperglycemia from the first 48 hours after the automation of the system, which was maintained at 6 months.

A Randomized Crossover Trial to Compare Automated Insulin Delivery (the Artificial Pancreas) With Carbohydrate Counting or Simplified Qualitative Meal-Size Estimation in Type 1 Diabetes

OBJECTIVE

Qualitative meal-size estimation has been proposed instead of quantitative carbohydrate (CHO) counting with automated insulin delivery. We aimed to assess the noninferiority of qualitative meal-size estimation strategy.

RESEARCH DESIGN AND METHODS

We conducted a two-center, randomized, crossover, noninferiority trial to compare 3 weeks of automated insulin delivery with 1) CHO counting and 2) qualitative meal-size estimation in adults with type 1 diabetes. Qualitative meal-size estimation categories were low, medium, high, or very high CHO and were defined as <30 g, 30-60 g, 60-90 g, and >90 g CHO, respectively. Prandial insulin boluses were calculated as the individualized insulin to CHO ratios multiplied by 15, 35, 65, and 95, respectively. Closed-loop algorithms were otherwise identical in the two arms. The primary outcome was time in range 3.9-10.0 mmol/L, with a predefined noninferiority margin of 4%.

RESULTS

A total of 30 participants completed the study (n = 20 women; age 44 (SD 17) years; A1C 7.4% [0.7%]). The mean time in the 3.9-10.0 mmol/L range was 74.1% (10.0%) with CHO counting and 70.5% (11.2%) with qualitative meal-size estimation; mean difference was -3.6% (8.3%; noninferiority P = 0.78). Frequencies of times at <3.9 mmol/L and <3.0 mmol/L were low (<1.6% and <0.2%) in both arms. Automated basal insulin delivery was higher in the qualitative meal-size estimation arm (34.6 vs. 32.6 units/day; P = 0.003).

CONCLUSIONS

Though the qualitative meal-size estimation method achieved a high time in range and low time in hypoglycemia, noninferiority was not confirmed.

A High-Linearity Glucose Sensor Based on Silver-Doped Con A Hydrogel and Laser Direct Writing

A continuous glucose monitoring (CGM) system is an ideal monitoring system for the blood glucose control of diabetic patients. The development of flexible glucose sensors with good glucose-responsive ability and high linearity within a large detection range is still challenging in the field of continuous glucose detection. A silver-doped Concanavalin A (Con A)-based hydrogel sensor is proposed to address the above issues. The proposed flexible enzyme-free glucose sensor was prepared by combining Con-A-based glucose-responsive hydrogels with green-synthetic silver particles on laser direct-writing graphene electrodes. The experimental results showed that in a glucose concentration range of 0–30 mM, the proposed sensor is capable of measuring the glucose level in a repeatable and reversible manner, showing a sensitivity of 150.12 Ω/mM with high linearity of R2 = 0.97. Due to its high performance and simple manufacturing process, the proposed glucose sensor is excellent among existing enzyme-free glucose sensors. It has good potential in the development of CGM devices.

Automated Insulin Delivery Systems as a Treatment for Type 2 Diabetes Mellitus: A Review

OBJECTIVE

Approximately 6.3% of the worldwide population has type 2 diabetes mellitus (T2DM), and the number of people requiring insulin is increasing. Automated insulin delivery (AID) systems integrate continuous subcutaneous insulin infusion and continuous glucose monitoring with a predictive control algorithm to provide more physiologic glycemic control. Personalized glycemic targets are recommended in T2DM owing to the heterogeneity of the disease. Based on the success of hybrid closed-loop systems in improving glycemic control and safety in type 1 diabetes mellitus, there has been further interest in the use of these systems in people with T2DM.

METHODS

We performed a review of AID systems with a focus on the T2DM population.

RESULTS

In 5 randomized controlled trials, AID systems improve time in range and reduce glycemic variability, without increasing insulin requirements or the risk of hypoglycemia.

CONCLUSION

AID systems in T2DM are safe and effective in hospitalized and closely monitored settings. Home studies of longer duration are required to assess for long-term benefit and identify target populations of benefit.

Low-Dose Empagliflozin as Adjunct to Hybrid Closed-Loop Insulin Therapy in Adults With Suboptimally Controlled Type 1 Diabetes: A Randomized Crossover Controlled Trial

OBJECTIVE

To assess whether low doses of empagliflozin as adjunct to hybrid closed-loop therapy improve glycemia compared with placebo in adults with type 1 diabetes (T1D) who are not able to achieve targets with the system alone.

RESEARCH DESIGN AND METHODS

A double-blind crossover randomized controlled trial was performed in adults with suboptimally controlled T1D (HbA1c 7.0-10.5%) who were not able to achieve a target time in range (3.9-10.0 mmol/L) ≥70% after 14 days of hybrid closed-loop therapy. Three 14-day interventions were performed with placebo, 2.5 mg empagliflozin, or 5 mg empagliflozin as adjunct to the McGill artificial pancreas. Participants were assigned at a 1:1:1:1:1:1 ratio with blocked randomization. The primary outcome was time in range (3.9-10.0 mmol/L). Analysis was by intention to treat, and a P value <0.05 was regarded as significant.

RESULTS

A total of 24 participants completed the study (50% male; age 33 ± 14 years; HbA1c 8.1 ± 0.5%). The time in range was 59.0 ± 9.0% for placebo, 71.6 ± 9.7% for 2.5 mg empagliflozin, and 70.2 ± 8.0% for 5 mg empagliflozin (P < 0.0001 between 2.5 mg empagliflozin and placebo and between 5 mg empagliflozin and placebo). Mean daily capillary ketone levels were not different between arms. There were no serious adverse events or cases of diabetic ketoacidosis or severe hypoglycemia in any intervention.

CONCLUSIONS

Empagliflozin at 2.5 and 5 mg increased time in range during hybrid closed-loop therapy by 11-13 percentage points compared with placebo in those who otherwise were unable to attain glycemic targets. Future studies are required to assess long-term efficacy and safety.

Study protocol: a randomised controlled proof-of-concept real-world study - does maximising time in range using hybrid closed loop insulin delivery and a low carbohydrate diet restore the glucagon response to hypoglycaemia in adults with type 1 diabetes?

INTRODUCTION

People with type 1 diabetes (T1D) develop an impaired glucagon response to hypoglycaemia within 5 years of diagnosis, increasing their risk of severe hypoglycaemia. It is not known whether eliminating hypoglycaemia and hyperglycaemia allows recovery of this glucagon response. Hybrid closed loop (HCL) technologies improve glycaemic time in range (TIR). However, post-prandial glycaemic excursions are still evident. Consuming a low carbohydrate diet (LCD) may minimise these excursions.

METHODS AND ANALYSIS

This feasibility study will assess if maximising TIR (glucose ≥3.9 mmol/L≤10 mmol/L) using HCL systems plus an LCD (defined here as <130 g carbohydrate/day) for >8 months, restores the glucagon response to insulin-induced hypoglycaemia. Adults (n=24) with T1D (C-peptide <200 pmol/L), naïve to continuous glucose monitoring (CGM) and HCL systems, will be recruited and randomised to: group 1 (non-HCL) to continue their standard diabetes care with intermittent blinded CGM; or group 2 (HCL-LCD) to use the HCL system and follow a LCD. Baseline data on diet and glycaemia will be collected from all participants. The HCL-LCD group will then enter a 2-week run-in to acclimatise to their devices. Throughout, the HCL-LCD group will have their glucose closely monitored and adjusted aiming for glycaemic TIR >70%. Participants will have their glucagon response to hypoglycaemia measured at the beginning and 8 months later at the study end using a stepped hyperinsulinaemic hypoglycaemic clamp, in combination with the stable isotopes 6,6-²H₂-glucose (D2-glucose) and 1,1,2,3,3-²H₅-glycerol (D5-glycerol) to assess glucose and glycerol kinetics. The impact of hypoglycaemia on symptoms and cognitive function will be assessed during each clamp study. The primary outcome is the difference in the glucagon response to hypoglycaemia between and within groups at baseline versus study end.

ETHICS AND DISSEMINATION

Ethical (20/SS/0117)/institutional review board (2021/0001) approval has been obtained. The study will be disseminated by peer-reviewed publications and conference presentations.

TRIAL REGISTRATION NUMBER

NCT04614168.

Internal model control based module for the elimination of meal and exercise announcements in hybrid artificial pancreas systems

BACKGROUND AND OBJECTIVES

Hybrid artificial pancreas systems outperform current insulin pump therapies in blood glucose regulation in type 1 diabetes. However, subjects still have to inform the system about meals intake and exercise to achieve reasonable control. These patient announcements may result in overburden and compromise controller performance if not provided timely and accurately. Here, a hybrid artificial pancreas is extended with an add-on module that releases subjects from meals and exercise announcements.

METHODS

The add-on module consists of an internal-model controller that generates a "virtual" control action to compensate for disturbances. This "virtual" action is converted into insulin delivery, rescue carbohydrates suggestions, or insulin-on-board limitations, depending on a switching logic based on glucose measurements and predictions. The controller parameters are tuned by optimization and then related to standard parameters from the open-loop therapy. This module is implemented in a hybrid artificial pancreas system proposed by our research group for validation. This hybrid system extended with the add-on module is compared with the hybrid controller with carbohydrate counting errors (hybrid) and the hybrid controller with an alternative unannounced meal compensation module based on a meal detection algorithm (meal detector). The validation used the educational version of the UVa/Padova simulator to simulate the three controllers under two scenarios: one with only meals and another with meals and exercise. The exercise was modeled as a temporal increase of the insulin sensitivity resulting in the glucose drop usually related to an aerobic exercise.

RESULTS

For the scenario with only meals, the three controllers achieved similar time in range (proposed: 85.1 [77.9,88.1]%, hybrid: 84.0 [75.9,86.4]%, meal detector: 81.9 [79.3,83.8]%, median [interquartile range]) with low time in moderate hypoglycemia. Under the scenario with meals and exercise, the proposed module reduces 4.61% the time in hypoglycemia achieved with the other controllers, suggesting an acceptable amount of rescues (27.2 [23.7, 31.0] g).

CONCLUSIONS

The proposed add-on module achieved promising results: it outperformed the meal-detector-based controller, even achieving a postprandial performance as good as the hybrid controller (with carbohydrate counting errors). Also, the rescue suggestion feature of the module mitigated exercise-induced hypoglycemia with admissible rescue amounts.

Comparison of Nocturnal Glucose After Exercise Among Dual-Hormone, Single-Hormone Algorithm-Assisted Insulin Delivery System and Usual Care in Adults and Adolescents Living with Type 1 Diabetes: A Pooled Analysis

Background: Available studies comparing the efficacy of dual-hormone (DH)-algorithm-assisted insulin delivery (AID), single-hormone (SH)-AID and usual care on postexercise overnight glucose in people with type 1 diabetes (T1D) have had different outcomes. By pooling data from all available studies, we aim to draw stronger conclusions. Methods: Data were pooled from two three-arm, open-label, randomized, controlled, crossover studies. Forty-one adults [median (Q1, Q3) age: 34.0 years (29.5, 51.0), mean HbA1c: 7.5% ± 1.0%] and 17 adolescents with T1D [age: 14.0 (13.0, 16.0), HbA1c: 7.8% ± 0.8%] underwent DH-AID, SH-AID, and usual care. Each intervention involved evening aerobic exercise (60-min). The primary outcome, time in range% (TIR%) overnight (00:00-06:00) postexercise based on continuous glucose monitoring, was compared among treatments using linear mixed effect model or generalized linear mixed model. Results: Among adults, mean TIR% was 94.0% ± 11.9%, 83.1% ± 20.5%, and 65.1% ± 37.0% during DH-AID, SH-AID, and usual care intervention, respectively (P < 0.05 for all between-group comparisons). DH-AID was superior to SH-AID and usual care, and SH-AID was superior to usual care regarding hypoglycemia and hyperglycemia prevention, but not glycemic variability. Among adolescents, DH-AID and SH-AID reduced dysglycemia, but not glycemic variability, better than usual care. Glycemic outcomes were similar between DH-AID and SH-AID. Conclusion: AID systems allow improved postexercise nocturnal glycemic management than usual care for both adults and adolescents. DH-AID was better than SH-AID among adults, but not adolescents.

Vasodilatory effects of glucagon: A possible new approach to enhanced subcutaneous insulin absorption in artificial pancreas devices

Patients with diabetes mellitus type 1 depend on exogenous insulin to keep their blood glucose concentrations within the desired range. Subcutaneous bihormonal artificial pancreas devices that can measure glucose concentrations continuously and autonomously calculate and deliver insulin and glucagon infusions is a promising new treatment option for these patients. The slow absorption rate of insulin from subcutaneous tissue is perhaps the most important factor preventing the development of a fully automated artificial pancreas using subcutaneous insulin delivery. Subcutaneous insulin absorption is influenced by several factors, among which local subcutaneous blood flow is one of the most prominent. We have discovered that micro-doses of glucagon may cause a substantial increase in local subcutaneous blood flow. This paper discusses how the local vasodilative effects of micro-doses of glucagon might be utilised to improve the performance of subcutaneous bihormonal artificial pancreas devices. We map out the early stages of our hypothesis as a disruptive novel approach, where we propose to use glucagon as a vasodilator to accelerate the absorption of meal boluses of insulin, besides using it conventionally to treat hypoglycaemia.

Formulation Excipients and Their Role in Insulin Stability and Association State in Formulation

While  excipients are often overlooked as the "inactive" ingredients in pharmaceutical formulations, they often play a critical role in protein stability and absorption kinetics. Recent work has identified an ultrafast absorbing insulin formulation that is the result of excipient modifications. Specifically, the insulin monomer can be isolated by replacing zinc and the phenolic preservative metacresol with phenoxyethanol as an antimicrobial agent and an amphiphilic acrylamide copolymer excipient for stability. A greater understanding is needed of the interplay between excipients, insulin association state, and stability in order to optimize this formulation. Here, we formulated insulin with different preservatives and stabilizing excipient concentrations using both insulin lispro and regular human insulin and assessed the insulin association states using analytical ultracentrifugation as well as formulation stability. We determined that phenoxyethanol is required to eliminate hexamers and promote a high monomer content even in a zinc-free lispro formulation. There is also a concentration dependent relationship between the concentration of polyacrylamide-based copolymer excipient and insulin stability, where a concentration greater than 0.1 g/mL copolymer is required for a mostly monomeric zinc-free lispro formulation to achieve stability exceeding that of Humalog in a stressed aging assay. Further, we determined that under the formulation conditions tested zinc-free regular human insulin remains primarily hexameric and is not at this time a promising candidate for rapid-acting formulations.

Carbohydrate Tolerance Threshold for Unannounced Snacks in Children and Adolescents With Type 1 Diabetes Using an Advanced Hybrid Closed-Loop System

OBJECTIVE

To find a carbohydrate (CHO) tolerance threshold for unannounced snacks to avoid the 2 h increase in glycemia (difference between pre- and postmeal blood glucose [ΔBG]) ≥50 mg/dL in advanced hybrid closed-loop (a-HCL) users.

RESEARCH DESIGN AND METHODS

Fourteen children and adolescents with type 1 diabetes (7 females; mean age [± SD] 14.5 ± 3.6 years), users of the Medtronic MiniMed 780G, participated in the study. For 12 days, they did not perform insulin bolus before breakfasts, with defined different quantities and types of CHO, with or without fats, performing blood glucose (BG) before and 2 h after the meal.

RESULTS

A cutoff of 19.8 g of total CHO was found to determine a ΔBG of 50 mg/dL. BG never exceeded 250 mg/dL. Mean time in range was ≥70% in the 2 h following each snack.

CONCLUSIONS

Unannounced snacks of up to 20 g of CHO can avoid ΔBG ≥50 mg/dL in MiniMed 780G users, although unannounced meals of up to 30 g of CHO are safe.

Super-twisting-based meal detector for type 1 diabetes management: Improvement and assessment in a real-life scenario

BACKGROUND AND OBJECTIVE

Hybrid automated insulin delivery systems rely on carbohydrate counting to improve postprandial control in type 1 diabetes. However, this is an extra burden on subjects, and it introduces a source of potential errors that could impact control performances. In fact, carbohydrates estimation is challenging, prone to errors, and it is known that subjects sometimes struggle to adhere to this requirement, forgetting to perform this task. A possible solution is the use of automated meal detection algorithms. In this work, we extended a super-twisting-based meal detector suggested in the literature and assessed it on real-life data.

METHODS

To reduce the false detections in the original meal detector, we implemented an implicit discretization of the super-twisting and replaced the Euler approximation of the glucose derivative with a Kalman filter. The modified meal detector is retrospectively evaluated in a challenging real-life dataset corresponding to a 2-week trial with 30 subjects using sensor-augmented pump control. The assessment includes an analysis of the nature and riskiness of false detections.

RESULTS

The proposed algorithm achieved a recall of 70 [13] % (median [interquartile range]), a precision of 73 [26] %, and had 1.4 [1.4] false positives-per-day. False positives were related to rising glucose conditions, whereas false negatives occurred after calibrations, missing samples, or hypoglycemia treatments.

CONCLUSIONS

The proposed algorithm achieves encouraging performance. Although false positives and false negatives were not avoided, they are related to situations with a low risk of hypoglycemia and hyperglycemia, respectively.

The relative contribution of diurnal and nocturnal glucose exposures to HbA1c in type 1 diabetes males: a pooled analysis

Purpose

The exact contribution of daily glucose exposure to HbA1c in people with type 1 diabetes (T1D) remains controversial. We examined the contribution of pre- and postprandial glycaemia, nocturnal and early-morning glycaemia, and glycaemic variability to HbA1c levels in T1D. In this analysis, we used clinical data, namely age, BMI and HbA1c, as well as glycaemic metrics (24-h glycaemia, postprandial, nocturnal, early-morning glycaemia, wake-up glucose, and glycaemic variability) obtained over a four-week period of continuous glucose monitoring (CGM) wear in thirty-two males with T1D.

Methods

The trapezoid method was used estimate the incremental area under the glucose curve (iAUC) for 24-h, postprandial (3-h period following breakfast, lunch, and dinner, respectively), nocturnal (between 24:00–04:00 AM), and early-morning (2-h period 2-h prior to wake-up) glycaemia. Linear regression analysis was employed whereby CGM-derived glycaemic metrics were explanatory variables and HbA1c was the outcome.

Results

Thirty-two T1D males (mean ± SD: age 29 ± 4 years; HbA1c 7.3 ± 0.9% [56 ± 13 mmol/mol]; BMI 25.80 ± 5.01 kg/m²) were included in this analysis. In linear models adjusted for age and BMI, HbA1c was associated with 24-h mean glucose (r² = 0.735, p < 0.001), SD (r² = 0.643, p = 0.039), and dinner iAUC (r² = 0.711, p = 0.001). CGM-derived metrics and non-glycaemic factors explained 77% of the variance in HbA1c, in which postprandial glucose accounted for 32% of the variance explained. The single greatest contributor to HbA1c was dinner iAUC resulting in 0.6%-point (~7 mmol/mol) increase in HbA1c per SD increase in dinner iAUC.

Conclusions

Using comprehensive CGM profiling, we show that postprandial glucose, specifically evening-time postprandial glucose, is the single largest contributing factor to HbA1c in T1D.

Trial registration number

NCT02204839 (July 30th 2014); NCT02595658 (November 3rd 2015).

Prediction of Personal Glycemic Responses to Food for Individuals With Type 1 Diabetes Through Integration of Clinical and Microbial Data

OBJECTIVE

Despite technological advances, results from various clinical trials have repeatedly shown that many individuals with type 1 diabetes (T1D) do not achieve their glycemic goals. One of the major challenges in disease management is the administration of an accurate amount of insulin for each meal that will match the expected postprandial glycemic response (PPGR). The objective of this study was to develop a prediction model for PPGR in individuals with T1D.

RESEARCH DESIGN AND METHODS

We recruited individuals with T1D who were using continuous glucose monitoring and continuous subcutaneous insulin infusion devices simultaneously to a prospective cohort and profiled them for 2 weeks. Participants were asked to report real-time dietary intake using a designated mobile app. We measured their PPGRs and devised machine learning algorithms for PPGR prediction, which integrate glucose measurements, insulin dosages, dietary habits, blood parameters, anthropometrics, exercise, and gut microbiota. Data of the PPGR of 900 healthy individuals to 41,371 meals were also integrated into the model. The performance of the models was evaluated with 10-fold cross validation.

RESULTS

A total of 121 individuals with T1D, 75 adults and 46 children, were included in the study. PPGR to 6,377 meals was measured. Our PPGR prediction model substantially outperforms a baseline model with emulation of standard of care (correlation of R = 0.59 compared with R = 0.40 for predicted and observed PPGR respectively; P < 10-10). The model was robust across different subpopulations. Feature attribution analysis revealed that glucose levels at meal initiation, glucose trend 30 min prior to meal, meal carbohydrate content, and meal's carbohydrate-to-fat ratio were the most influential features for the model.

CONCLUSIONS

Our model enables a more accurate prediction of PPGR and therefore may allow a better adjustment of the required insulin dosage for meals. It can be further implemented in closed loop systems and may lead to rationally designed nutritional interventions personally tailored for individuals with T1D on the basis of meals with expected low glycemic response.

Examining Type 1 Diabetes Mathematical Models Using Experimental Data

Type 1 diabetes requires treatment with insulin injections and monitoring glucose levels in affected individuals. We explored the utility of two mathematical models in predicting glucose concentration levels in type 1 diabetic mice and determined disease pathways. We adapted two mathematical models, one with β-cells and the other with no β-cell component to determine their capability in predicting glucose concentration and determine type 1 diabetes pathways using published glucose concentration data for four groups of experimental mice. The groups of mice were numbered Mice Group 1–4, depending on the diabetes severity of each group, with severity increasing from group 1–4. A Markov Chain Monte Carlo method based on a Bayesian framework was used to fit the model to determine the best model structure. Akaike information criteria (AIC) and Bayesian information criteria (BIC) approaches were used to assess the best model structure for type 1 diabetes. In fitting the model with no β-cells to glucose level data, we varied insulin absorption rate and insulin clearance rate. However, the model with β-cells required more parameters to match the data and we fitted the β-cell glucose tolerance factor, whole body insulin clearance rate, glucose production rate, and glucose clearance rate. Fitting the models to the blood glucose concentration level gave the least difference in AIC of 1.2, and a difference in BIC of 0.12 for Mice Group 4. The estimated AIC and BIC values were highest for Mice Group 1 than all other mice groups. The models gave substantial differences in AIC and BIC values for Mice Groups 1–3 ranging from 2.10 to 4.05. Our results suggest that the model without β-cells provides a more suitable structure for modelling type 1 diabetes and predicting blood glucose concentration for hypoglycaemic episodes.

Can Faster Aspart Be Used to Optimize Glycemic Control With Insulin Pump Therapy? From Expectations to Lessons Learned After a Year of Use in the United States

Fast-acting insulin aspart (faster aspart) is an ultra-rapid-acting formulation of insulin aspart developed to more closely match the prandial endogenous insulin profile, and its accelerated absorption kinetics are expected to provide clinical benefits for patients using insulin pump therapy. A head-to-head trial versus the original insulin aspart formulation in pump therapy did not demonstrate superiority of faster aspart in terms of A1C reduction, but pump settings were not optimized for the pharmacokinetic/pharmacodynamic profile of faster aspart. Nevertheless, meal test and continuous glucose monitoring data suggest that faster aspart is beneficial for postprandial glucose control, and a case study is presented illustrating excellent results using this insulin in pump therapy. Frequent blood glucose monitoring and appropriate patient education are vital for success.

Using an Online Disturbance Rejection and Anticipation System to Reduce Hyperglycemia in a Fully Closed-Loop Artificial Pancreas System

INTRODUCTION

Hyperglycemia following meals is a recurring challenge for people with type 1 diabetes, and even the most advanced available automated systems currently require manual input of carbohydrate amounts. To progress toward fully automated systems, we present a novel control system that can automatically deliver priming boluses and/or anticipate eating behaviors to improve postprandial full closed-loop control.

METHODS

A model predictive control (MPC) system was enhanced by an automated bolus system reacting to early glucose rise and/or a multistage MPC (MS-MPC) framework to anticipate historical patterns. Priming was achieved by detecting large glycemic disturbances, such as meals, and delivering a fraction of the patient's total daily insulin (TDI) modulated by the disturbance's likelihood (bolus priming system [BPS]). In the anticipatory module, glycemic disturbance profiles were generated from historical data using clustering to group days with similar behaviors; the probability of each cluster is then evaluated at every controller step and informs the MS-MPC framework to anticipate each profile. We tested four configurations: MPC, MPC + BPS, MS-MPC, and MS-MPC + BPS in simulation to contrast the effect of each controller module.

RESULTS

Postprandial time in range was highest for MS-MPC + BPS: 60.73 ± 25.39%, but improved with each module: MPC + BPS: 56.95±25.83 and MS-MPC: 54.83 ± 26.00%, compared with MPC: 51.79 ± 26.12%. Exposure to hypoglycemia was maintained for all controllers (time below 70 mg/dL <0.5%), and improvement came primarily from a reduction in postprandial time above range (MS-MPC + BPS: 39.10 ± 25.32%, MPC + BPS: 42.99 ± 25.81%, MS-MPC: 45.09 ± 25.96%, MPC: 48.18 ± 26.09%).

CONCLUSIONS

The BPS and anticipatory disturbance profiles improved blood glucose control and were most efficient when combined.

One-hundred year evolution of prandial insulin preparations: From animal pancreas extracts to rapid-acting analogs

The first insulin preparation injected in humans in 1922 was short-acting, extracted from animal pancreas, contaminated by impurities. Ever since the insulin extracted from animal pancreas has been continuously purified, until an unlimited synthesis of regular human insulin (RHI) became possible in the '80s using the recombinant-DNA (rDNA) technique. The rDNA technique then led to the designer insulins (analogs) in the early '90s. Rapid-acting insulin analogs were developed to accelerate the slow subcutaneous (sc) absorption of RHI, thus lowering the 2-h post-prandial plasma glucose (PP-PG) and risk for late hypoglycemia as comparing with RHI. The first rapid-acting analog was lispro (in 1996), soon followed by aspart and glulisine. Rapid-acting analogs are more convenient than RHI: they improve early PP-PG, and 24-h PG and A1C as long as basal insulin is also optimized; they lower the risk of late PP hypoglycemia and they allow a shorter time-interval between injection and meal. Today rapid-acting analogs are the gold standard prandial insulins. Recently, even faster analogs have become available (faster aspart, ultra-rapid lispro) or are being studied (Biochaperone lispro), making additional gains in lowering PP-PG. Rapid-acting analogs are recommended in all those with type 1 and type 2 diabetes who need prandial insulin replacement.

Dietary determinants of postprandial blood glucose control in adults with type 1 diabetes on a hybrid closed-loop system

AIMS/HYPOTHESIS

The aim of this work was to assess the relationship between meal nutrients and postprandial blood glucose response (PGR) in individuals with type 1 diabetes on a hybrid closed-loop system (HCLS).

METHODS

The dietary composition of 1264 meals (398 breakfasts, 441 lunches and 425 dinners) was assessed by 7-day food records completed by 25 individuals with type 1 diabetes on HCLSs (12 men/13 women, mean ± SD age 40 ± 12 years, mean ± SD HbA_1c 51 ± 10 mmol/mol [6.9 ± 0.2%]). For each meal, PGR (continuous glucose monitoring metrics, glucose incremental AUCs) and insulin doses (pre-meal boluses, post-meal microboluses automatically delivered by the pump and adjustment boluses) over 6 h were evaluated.

RESULTS

Breakfast, lunch and dinner significantly differed with respect to energy and nutrient intake and insulin doses. The blood glucose postprandial profile showed an earlier peak after breakfast and a slow increase until 4 h after lunch and dinner (p < 0.001). Mean ± SD postprandial time in range (TIR) was better at breakfast (79.3 ± 22.2%) than at lunch (71.3 ± 23.9%) or dinner (70.0 ± 25.9%) (p < 0.001). Significant negative predictors of TIR at breakfast were total energy intake, per cent intake of total protein and monounsaturated fatty acids, glycaemic load and absolute amounts of cholesterol, carbohydrates and simple sugars consumed (p < 0.05 for all). No significant predictors were detected for TIR at lunch. For TIR at dinner, a significant positive predictor was the per cent intake of plant proteins, while negative predictors were glycaemic load and intake amounts of simple sugars and carbohydrate (p < 0.05 for all).

CONCLUSIONS/INTERPRETATION

This study shows that nutritional factors other than the amount of carbohydrate significantly influence postprandial blood glucose control. These nutritional determinants vary between breakfast, lunch and dinner, with differing effects on postprandial blood glucose profile and insulin requirements, thus remaining a challenge to HCLSs.

Strategically Playing with Fire: SGLT Inhibitors as Possible Adjunct to Closed-Loop Insulin Therapy

As closed-loop insulin therapies emerge into clinical practice and evolve in medical research for type 1 diabetes (T1D) treatment, the limitations in these therapies become more evident. These gaps include unachieved target levels of glycated hemoglobin in some patients, postprandial hyperglycemia, the ongoing need for carbohydrate counting, and the lack of non-glycemic benefits (such as prevention of metabolic syndrome and complications). Multiple adjunct therapies have been examined to improve closed-loop systems, yet none have become a staple. Sodium-glucose-linked cotransporter inhibitors (SGLTi's) have been extensively researched in T1D, with average reductions in placebo-adjusted HbA1c by 0.39%, and total daily dose by approximately 10%. Unfortunately, many trials revealed an increased risk of diabetic ketoacidosis, as high as 5 times the relative risk compared to placebo. This narrative review discusses the proven benefits and risks of SGLTi in patients with T1D with routine therapy, what has been studied thus far in closed-loop therapy in combination with SGLTi, the potential benefits of SGLTi use to closed-loop systems, and what is required going forward to improve the benefit to risk ratio in these insulin systems.

The impact of "faster aspart" on blood glucose control in children and adolescents with type 1 diabetes treated using a sensor-augmented insulin pump

BACKGROUND AND AIMS

Post-prandial glucose control is essential to achieve metabolic goals in patients with type 1 diabetes mellitus (T1DM). The new "faster aspart" insulin has a pharmacological profile noted for its faster absorption and onset of action, and increased early availability, resulting in improved blood glucose control after meals. The main objective of the study was to analyse the efficacy of "faster aspart" vs. "insulin aspart" in children and adolescents with DM1 on sensor-augmented pump treatment.

PATIENTS AND METHODS

Multicentre, longitudinal and prospective analytical trial evaluating the use of faster aspart insulin for three months in children with T1DM with MiniMed640G® sensor-augmented pumps previously treated with aspart insulin. At the beginning and end of the study the following variables were analysed for subsequent comparison: mean sensor glucose, percentage of time in range, hypoglycaemia and hyperglycaemia, area under the curve (AUC) <70 and >180 mg/dL, mean sensor glucose pre- and postprandial in main meals, daily insulin requirements, basal/bolus percentage, and HbA1c. Acute complications, adverse events and satisfaction survey were assessed.

RESULTS

The study included 32 patients with a mean of 13.49 ± 2.42 years of age and with T1DM of 7.0 ± 3.67 years of onset. The use of faster aspart was associated with lower time in hyperglycaemia >180 mg/dL (25.8 ± 11.3 vs. 22.4 ± 9.5; p = .011) and >250 mg/dL (5.2±4.9 vs. 4.0 ± 3.6; p = .04), lower AUC >180 mg/dL (10.8 ± 6.5 vs. 9.3 ± 6.1; p = .03), and increased time in range (71.4 ± 10.0 vs. 74.3 ± 9.2; p = .03). No significant changes in hypoglycaemia, HbA1c, insulin requirements, and basal/bolus percentages were detected. Faster aspart was safe and well-evaluated by patients and caregivers.

CONCLUSIONS

Faster aspart achieves better glycaemic control by increasing glucose time in range in children and adolescents with T1DM on treatment with sensor-augmented pumps.

Effect of meal composition and alcohol consumption on postprandial glucose concentration in subjects with type 1 diabetes: a randomized crossover trial

INTRODUCTION

Meal composition is known to affect glycemic variability and glucose control in type 1 diabetes. The objective of this work was to evaluate the effect of high carbohydrate meals of different nutritional composition and alcohol on the postprandial glucose response in patients with type 1 diabetes.

RESEARCH DESIGN AND METHODS

Twelve participants were recruited to this randomized crossover trial. Following a 4-week run-in period, participants received a mixed meal on three occasions with the same carbohydrate content but different macronutrient composition: high protein-high fat with alcohol (0.7g/kg body weight, beer), high protein-high fat without alcohol, and low protein-low fat without alcohol at 2-week intervals. Plasma and interstitial glucose, insulin, glucagon, growth hormone, cortisol, alcohol, free fatty acids, lactate, and pH concentrations were measured during 6 hours. A statistical analysis was then carried out to determine significant differences between studies.

RESULTS

Significantly higher late postprandial glucose was observed in studies with higher content of fats and proteins (p=0.0088). This was associated with lower time in hypoglycemia as compared with the low protein and fat study (p=0.0179), at least partially due to greater glucagon concentration in the same period (p=0.04). Alcohol significantly increased lactate, decreased pH and growth hormone, and maintained free fatty acids suppressed during the late postprandial phase (p<0.001), without significant changes in plasma glucose.

CONCLUSIONS

Our data suggest that the addition of proteins and fats to carbohydrates increases late postprandial blood glucose. Moreover, alcohol consumption together with a mixed meal has relevant metabolic effects without any increase in the risk of hypoglycemia, at least 6 hours postprandially.

TRIAL REGISTRATION NUMBER

NCT03320993.

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. Basal-bolus FiASP-and-pramlintide were delivered at a fixed ratio (1 U:10 μg). Glycaemic outcomes were measured, surveys evaluated gastrointestinal symptoms and diabetes distress, and participant interviews helped establish a preliminary coding framework to assess user experience.

RESULTS

Seven participants were included in the feasibility analysis. Time spent in 3.9-10 mmol/L was similar between both interventions (81%-84%). Four participants were included in the pilot analysis. Time spent in 3.9-10 mmol/L was similar between the FiASP-and-placebo with FCC and FiASP-and-pramlintide with SMA interventions (70%), but was lower in the FiASP-and-placebo with SMA intervention (60%). Time less than 3.9 mmol/L and gastrointestinal symptoms were similar across all interventions. Emotional distress was moderate at baseline, after the FiASP-and-placebo with FCC and SMA interventions, and fell after the FiASP-and-pramlintide with SMA intervention. SMA reportedly afforded participants flexibility and reduced mealtime concerns.

CONCLUSIONS

The FiASP-and-pramlintide system has the potential to substitute carbohydrate counting with SMA without degrading glucose control.

Measuring Postprandial Metabolic Flexibility to Assess Metabolic Health and Disease

Metabolic abnormalities substantially increase the risk of noncommunicable diseases, which are among the leading causes of mortality globally. Mitigating and preventing these adverse consequences remains challenging due to a limited understanding of metabolic health. Metabolic flexibility, a key tenet of metabolic health, encompasses the responsiveness of interrelated pathways to maintain energy homeostasis throughout daily physiologic challenges, such as the response to meal challenges. One critical underlying research gap concerns the measurement of postprandial metabolic flexibility, which remains incompletely understood. We concisely review the methodology for assessment of postprandial metabolic flexibility in recent human studies. We identify 3 commonalities of study design, specifically the nature of the challenge, nature of the response measured, and approach to data analysis. Primary interventions were acute short-term nutrition challenges, including single- and multiple-macronutrient tolerance tests. Postmeal challenge responses were measured via laboratory assays and instrumentation, based on a diverse set of metabolic flexibility indicators [e.g., energy expenditure (whole-body indirect calorimetry), glucose and insulin kinetics, metabolomics, transcriptomics]. Common standard approaches have been diabetes-centric with single-macronutrient challenges (oral-glucose-tolerance test) to characterize the postprandial response based on glucose and insulin metabolism; or broad measurements of energy expenditure with calculated macronutrient oxidation via indirect calorimetry. Recent methodological advances have included the use of multiple-macronutrient meal challenges that are more representative of physiologic meals consumed by free-living humans, combinatorial approaches for assays and instruments, evaluation of other metabolic flexibility indicators via precision health, systems biology, and temporal perspectives. Omics studies have identified potential novel indicators of metabolic flexibility, which provide greater granularity to prior evidence from canonical approaches. In summary, recent findings indicate the potential for an expanded understanding of postprandial metabolic flexibility, based on nonclassical measurements and methodology, which could represent novel dynamic indicators of metabolic diseases.

An ultrafast insulin formulation enabled by high-throughput screening of engineered polymeric excipients

Insulin has been used to treat diabetes for almost 100 years; yet, current rapid-acting insulin formulations do not have sufficiently fast pharmacokinetics to maintain tight glycemic control at mealtimes. Dissociation of the insulin hexamer, the primary association state of insulin in rapid-acting formulations, is the rate-limiting step that leads to delayed onset and extended duration of action. A formulation of insulin monomers would more closely mimic endogenous postprandial insulin secretion, but monomeric insulin is unstable in solution using present formulation strategies and rapidly aggregates into amyloid fibrils. Here, we implement high-throughput-controlled radical polymerization techniques to generate a large library of acrylamide carrier/dopant copolymer (AC/DC) excipients designed to reduce insulin aggregation. Our top-performing AC/DC excipient candidate enabled the development of an ultrafast-absorbing insulin lispro (UFAL) formulation, which remains stable under stressed aging conditions for 25 ± 1 hours compared to 5 ± 2 hours for commercial fast-acting insulin lispro formulations (Humalog). In a porcine model of insulin-deficient diabetes, UFAL exhibited peak action at 9 ± 4 min, whereas commercial Humalog exhibited peak action at 25 ± 10 min. These ultrafast kinetics make UFAL a promising candidate for improving glucose control and reducing burden for patients with diabetes.

Review of Automated Insulin Delivery Systems for Individuals with Type 1 Diabetes: Tailored Solutions for Subpopulations

Automated insulin delivery (AID) systems have proven safe and effective in improving glycemic outcomes in individuals with type 1 diabetes (T1D). Clinical evaluation of this technology has progressed to large randomized, controlled outpatient studies and recent commercial approval of AID systems for children and adults. However, several challenges remain in improving these systems for different subpopulations (e.g., young children, athletes, pregnant women, seniors and those with hypoglycemia unawareness). In this review, we highlight the requirements and challenges in AID design for selected subpopulations, and discuss current advances from recent clinical studies.

Full closed loop open-source algorithm performance comparison in pigs with diabetes

Understanding how automated insulin delivery (AID) algorithm features impact glucose control under full closed loop delivery represents a critical step toward reducing patient burden by eliminating the need for carbohydrate entries at mealtimes. Here, we use a pig model of diabetes to compare AndroidAPS and Loop open‐source AID systems without meal announcements. Overall time‐in‐range (70–180 mg/dl) for AndroidAPS was 58% ± 5%, while time‐in‐range for Loop was 35% ± 5%. The effect of the algorithms on time‐in‐range differed between meals and overnight. During the overnight monitoring period, pigs had an average time‐in‐range of 90% ± 7% when on AndroidAPS compared to 22% ± 8% on Loop. Time‐in‐hypoglycemia also differed significantly during the lunch meal, whereby pigs running AndroidAPS spent an average of 1.4% (+0.4/−0.8)% in hypoglycemia compared to 10% (+3/−6)% for those using Loop. As algorithm design for closed loop systems continues to develop, the strategies employed in the OpenAPS algorithm (known as oref1) as implemented in AndroidAPS for unannounced meals may result in a better overall control for full closed loop systems.

Perceptions and expectations of adults with type 1 diabetes for the use of artificial pancreas systems with and without glucagon addition: Results of an online survey

BACKGROUND AND AIMS

The first hybrid artificial pancreas (AP) systems with insulin only (mono-hormonal) have recently reached the market while next generations systems are under development including those with glucagon addition (bi-hormonal). Understanding the expectations and impressions of future potential users about AP systems is important for optimal use of this clinically effective emerging technology.

METHODS AND RESULTS

An online survey about AP systems which consisted of 50 questions was addressed to people with type 1 diabetes in the province of Quebec, Canada. Surveys were completed by 123 respondents with type 1 diabetes (54% women, mean (SD) age 40.2 (14.4) y.o., diabetes duration 23.7 (14.1) years, 58% insulin pump users and 43% glucose sensor users). Of the respondents, 91% understood how AP systems work, 79% trusted them with correct insulin dosing, 73% were willing to replace their current treatment with AP and 80% expected improvement in quality of life. Anxiety about letting an algorithm control their glucose levels was expressed by 18% while the option of ignoring or modifying AP instructions was favoured by 88%. As for bi-hormonal AP systems, 83% of respondents thought they would be useful to further reduce hypoglycemic risks.

CONCLUSIONS

Overall, respondents expressed positive views about AP systems use and high expectations for a better quality of life, glycemic control and hypoglycemia reduction. Data from this survey could be useful to health care professionals and developers of AP systems.

Adjunctive therapies in type 1 diabetes mellitus

PURPOSE OF REVIEW

Insulin is the mainstay of treatment in people living with type 1 diabetes mellitus due to an immune-mediated loss of beta cells. Yet despite advances in insulin therapy and other technological advances, glycemic control remains difficult to achieve. Therefore, we aim to highlight risks and benefits of adjunctive therapies that may improve type 1 diabetes care.

RECENT FINDINGS

We identified studies assessing clinical outcomes of adjunctive therapies that are both Food and Drug Administration (FDA)-approved and off-label in type 1 diabetes. Adjunctive therapies reviewed included metformin, pramlintide, glucagon-like peptide-1 (GLP-1) receptor agonists and sodium-glucose cotransporter-2 inhibitors.

SUMMARY

Although insulin is required in people living with type 1 diabetes mellitus, adjunctive therapies may positively impact glycemic control, reduce insulin requirements and lead to weight loss. In addition, the risk of hypoglycemia, gastrointestinal side effects and diabetes ketoacidosis may be increased with the use of these adjunctive therapies. Pramlintide is currently the only FDA-approved adjunctive therapy, whereas others require continued research to better understand risk-to-benefit ratio.

Engineering biopharmaceutical formulations to improve diabetes management

Insulin was first isolated almost a century ago, yet commercial formulations of insulin and its analogs for hormone replacement therapy still fall short of appropriately mimicking endogenous glycemic control. Moreover, the controlled delivery of complementary hormones (such as amylin or glucagon) is complicated by instability of the pharmacologic agents and complexity of maintaining multiple infusions. In this review, we highlight the advantages and limitations of recent advances in drug formulation that improve protein stability and pharmacokinetics, prolong drug delivery, or enable alternative dosage forms for the management of diabetes. With controlled delivery, these formulations could improve closed-loop glycemic control.

An enzyme-free capacitive glucose sensor based on dual-network glucose-responsive hydrogel and coplanar electrode

Glucose sensors are vital devices for blood glucose detection in the diabetes care. Different from traditional electrochemical devices based on glucose oxidase, the glucose sensor based on the glucose-responsive hydrogel is more robust owing to its enzyme-free principle. However, integrating the high sensitivity, fast response, wide measuring range and low-cost fabrication into a hydrogel sensor is still challenging. In this study, we present a physical capacitive sensor, which consists of interdigital carbon electrodes (ICEs) fabricated by a direct laser writing technology and glucose-responsive hydrogel (DexG-Con A hydrogel) built by UV curing in situ. The dielectric property of DexG-Con A hydrogel changes accordingly with the change in environmental glucose concentration. Experimental results demonstrate that in a glucose concentration range of 0-30 mM, the proposed hydrogel sensor is capable of measuring the glucose level in a repeatable and reversible manner, showing a short responsive time of less than 2 min and a high sensitivity of 8.81 pF mM-1 at a glucose range of 0-6 mM. Owing to its simple fabrication process, low-cost and high performance, the proposed glucose sensor shows great potential on batch production for continuous glucose monitoring application.

[The impact of «faster aspart» on blood glucose control in children and adolescents with type 1 diabetes treated using a sensor-augmented insulin pump]

BACKGROUND AND AIMS

Post-prandial glucose control is essential to achieve metabolic goals in patients with type 1 diabetes mellitus (T1DM). The new «faster aspart» insulin has a pharmacological profile noted for its faster absorption and onset of action, and increased early availability, resulting in improved blood glucose control after meals. The main objective of the study was to analyse the efficacy of «faster aspart» vs. «insulin aspart» in children and adolescents with DM1 on sensor-augmented pump treatment.

PATIENTS AND METHODS

Multicentre, longitudinal and prospective analytical trial evaluating the use of faster aspart insulin for three months in children with T1DM with MiniMed640G® sensor-augmented pumps previously treated with aspart insulin. At the beginning and end of the study the following variables were analysed for subsequent comparison: mean sensor glucose, percentage of time in range, hypoglycaemia and hyperglycaemia, area under the curve (AUC) < 70 and > 180 mg/dL, mean sensor glucose pre and postprandial in main meals, daily insulin requirements, basal/bolus percentage, and HbA1c. Acute complications, adverse events and satisfaction survey were assessed.

RESULTS

The study included 31 patients with a mean of 13.49 ± 2.42 years of age and with T1DM of 7.0 ± 3.67 years of onset. The use of faster aspart was associated with lower time in hyperglycaemia > 180 mg/dL (25.8 ± 11.3 vs. 22.4 ± 9.5; p = 0.011) and > 250 mg/dL (5.2 ± 4.9 vs. 4.0 ± 3.6; p = 0.04), lower AUC > 180 mg/dL (10.8 ± 6.5 vs. 9.3 ± 6.1; p = 0.03), and increased time in range (71.4 ± 10.0 vs. 74.3 ± 9.2; p = 0.03). No significant changes in hypoglycaemia, HbA1c, insulin requirements, and basal/bolus percentages were detected. Faster aspart was safe and well-evaluated by patients and caregivers.

CONCLUSIONS

Faster aspart achieves better glycaemic control by increasing glucose time in range in children and adolescents with T1DM on treatment with sensor-augmented pumps.

A single-blind, randomised, crossover study to reduce hypoglycaemia risk during postprandial exercise with closed-loop insulin delivery in adults with type 1 diabetes: announced (with or without bolus reduction) vs unannounced exercise strategies

AIMS/HYPOTHESIS

For individuals living with type 1 diabetes, closed-loop insulin delivery improves glycaemic control. Nonetheless, maintenance of glycaemic control during exercise while a prandial insulin bolus remains active is a challenge even to closed-loop systems. We investigated the effect of exercise announcement on the efficacy of a closed-loop system, to reduce hypoglycaemia during postprandial exercise.

METHODS

A single-blind randomised, crossover open-label trial was carried out to compare three strategies applied to a closed-loop system at mealtime in preparation for exercise taken 90 min after eating at a research testing centre: (1) announced exercise to the closed-loop system (increases target glucose levels) in addition to a 33% reduction in meal bolus (A-RB); (2) announced exercise to the closed-loop system and a full meal bolus (A-FB); (3) unannounced exercise and a full meal bolus (U-FB). Participants performed 60 min of exercise at 60% [Formula: see text] 90 min after eating breakfast. The investigators were not blinded to the interventions. However, the participants were blinded to the sensor glucose readings and to the insulin infusion rates throughout the intervention visits.

RESULTS

The trial was completed by 37 adults with type 1 diabetes, all using insulin pumps: mean±SD, 40.0 ± 15.0 years of age, HbA_1c 57.1 ± 10.8 mmol/mol (7.3 ± 1.0%). Reported results were based on plasma glucose values. During exercise and the following 1 h recovery period, time spent in hypoglycaemia (<3.9 mmol/l; primary outcome) was reduced with A-RB (mean ± SD; 2.0 ± 6.2%) and A-FB (7.0 ± 12.6%) vs U-FB (13.0 ± 19.0%; p < 0.0001 and p = 0.005, respectively). During exercise, A-RB had the least drop in plasma glucose levels: A-RB -0.3 ± 2.8 mmol/l, A-FB -2.6 ± 2.9 mmol/l vs U-FB -2.4 ± 2.7 mmol/l (p < 0.0001 and p = 0.5, respectively). Comparison of A-RB vs U-FB revealed a decrease in the time spent in target (3.9-10 mmol/l) by 12.7% (p = 0.05) and an increase in the time spent in hyperglycaemia (>10 mmol/l) by 21% (p = 0.001). No side effects were reported during the applied strategies.

CONCLUSIONS/INTERPRETATION

Combining postprandial exercise announcement, which increases closed-loop system glucose target levels, with a 33% meal bolus reduction significantly reduced time spent in hypoglycaemia compared with the other two strategies, yet at the expense of more time spent in hyperglycaemia.

TRIAL REGISTRATION

ClinicalTrials.gov NCT0285530 FUNDING: JDRF (2-SRA-2016-210-A-N), the Canadian Institutes of Health Research (354024) and the Fondation J.-A. DeSève chair held by RR-L.

Effects of advanced carbohydrate counting on glucose control and quality of life in children with type 1 diabetes

OBJECTIVE

The effect of advanced carbohydrate counting (ACC) on metabolic and quality of life (QOL) outcomes is uncertain in children with type 1 diabetes. Our aim was to determine whether ACC would improve HbA1c and QOL scores as compared with standard nutrition in this population.

METHODS

We randomized 87 patients using pump and rapid-acting analogs in a 1 year randomized multicenter study (age 9.6 ± 3.5 years, diabetes duration 4.6 ± 2.7 years, HbA1c 7.8 ± 0.5% [62 ± 5 mmol/mol]). The ACC group received CC education and the control group received traditional dietary education. HbA1c was measured every 3 months. At 0 and 1 year, general, diabetes-specific, and diet-related QOL were respectively assessed by the KIDSCREEN and WHO-5 questionnaires, the diabetes-specific module of the DISABKIDS, and the diet restriction items of the DSQOLS.

RESULTS

Mean HbA1c was lower in the ACC than the control group at 3 months (P < .05) and tended to be lower at 6 months (P = .10), 9 months (P = .10), but not at 12 months. The mean of individual average HbA1c during the one-year study period (from M3 to M12) was 7.63 ± 0.43 in the ACC vs 7.85 ± 0.47% in the control group (60 ± 5 vs 62 ± 5 mmol/mol)(P < .05). ACC was associated with significantly higher scores at 1 year on the KIDSCREEN children's psychological scale and the KIDSCREEN parents' physical scale, the DISABKIDS children's treatment scale, and the children's and parents' dietary restriction scales of the DSQOLS (indicating better QOL or lower perceived diet restriction).

CONCLUSIONS

ACC may be associated with small improvements in metabolic control and QOL scores in children.

Unannounced Meal Detection for Artificial Pancreas Systems Using Extended Isolation Forest

This study aims at developing an unannounced meal detection method for artificial pancreas, based on a recent extension of Isolation Forest. The proposed method makes use of features accounting for individual Continuous Glucose Monitoring (CGM) profiles and benefits from a two-threshold decision rule detection. The advantage of using Extended Isolation Forest (EIF) instead of the standard one is supported by experiments on data from virtual diabetic patients, showing good detection accuracy with acceptable detection delays.

In-Silico Evaluation of Glucose Regulation Using Policy Gradient Reinforcement Learning for Patients with Type 1 Diabetes Mellitus

In this paper, we test and evaluate policy gradient reinforcement learning for automated blood glucose control in patients with Type 1 Diabetes Mellitus. Recent research has shown that reinforcement learning is a promising approach to accommodate the need for individualized blood glucose level control algorithms. The motivation for using policy gradient algorithms comes from the fact that adaptively administering insulin is an inherently continuous task. Policy gradient algorithms are known to be superior in continuous high-dimensional control tasks. Previously, most of the approaches for automated blood glucose control using reinforcement learning has used a finite set of actions. We use the Trust-Region Policy Optimization algorithm in this work. It represents the state of the art for deep policy gradient algorithms. The experiments are carried out in-silico using the Hovorka model, and stochastic behavior is modeled through simulated carbohydrate counting errors to illustrate the full potential of the framework. Furthermore, we use a model-free approach where no prior information about the patient is given to the algorithm. Our experiments show that the reinforcement learning agent is able to compete with and sometimes outperform state-of-the-art model predictive control in blood glucose regulation.

Assessment of Risks and Benefits of Beta Cell Replacement Versus Automated Insulin Delivery Systems for Type 1 Diabetes

PURPOSE OF REVIEW

Current approaches to insulin replacement in type 1 diabetes are unable to achieve optimal levels of glycemic control without substantial risk of hypoglycemia and substantial burden of self-management. Advances in biology and technology present beta cell replacement and automated insulin delivery as two alternative approaches. Here we discuss current and future prospects for the relative risks and benefits for biological and psychosocial outcomes from the perspective of researchers, clinicians, and persons living with diabetes.

RECENT FINDINGS

Beta cell replacement using pancreas or islet transplant can achieve insulin independence but requires immunosuppression. Although insulin independence may not be sustained, time in range of 80-90%, minimal glycemic variability and abolition of hypoglycemia is routine after islet transplantation. Clinical trials of potentially unlimited supply of stem cell-derived beta cells are showing promise. Automated insulin delivery (AID) systems can achieve 70-75% time in range, with reduced glycemic variability. Impatient with the pace of commercially available AID, users have developed their own algorithms which appear to be at least equivalent to systems developed within conventional regulatory frameworks. The importance of psychosocial factors and the preferences and values of persons living with diabetes are emerging as key elements on which therapies should be evaluated beyond their impact of biological outcomes. Biology or technology to deliver glucose dependent insulin secretion is associated with substantial improvements in glycemia and prevention of hypoglycemia while relieving much of the substantial burden of diabetes. Automated insulin delivery, currently, represents a more accessible bridge to a biologic cure that we expect future cellular therapies to deliver.

Closed-loop control in insulin pumps for type-1 diabetes mellitus: safety and efficacy

INTRODUCTION

Type 1 diabetes is a lifelong disease with high management burden. The majority of people with type 1 diabetes fail to achieve glycemic targets. Algorithm-driven automated insulin delivery (closed-loop) systems aim to address these challenges. This review provides an overview of commercial and emerging closed-loop systems.

AREAS COVERED

We review safety and efficacy of commercial and emerging hybrid closed-loop systems. A literature search was conducted and clinical trials using day-and-night closed-loop systems during free-living conditions were used to report on safety data. We comment on efficacy where robust randomized controlled trial data for a particular system are available. We highlight similarities and differences between commercial systems.

EXPERT OPINION

Study data shows that hybrid closed-loop systems are safe and effective, consistently improving glycemic control when compared to standard therapy. While a fully closed-loop system with minimal burden remains the end-goal, these hybrid closed-loop systems have transformative potential in diabetes care.

Closed-loop bioelectronic medicine for diabetes management

Modulation of the nervous system by delivering electrical or pharmaceutical agents has contributed to the development of novel treatments to serious health disorders. Recent advances in multidisciplinary research has enabled the emergence of a new powerful therapeutic approach called bioelectronic medicine. Bioelectronic medicine exploits the fact that every organ in our bodies is neurally innervated and thus electrical interfacing with peripheral nerves can be a potential pathway for diagnosing or treating diseases such as diabetes. In this context, a plethora of studies have confirmed the important role of the nervous system in maintaining a tight regulation of glucose homeostasis. This has initiated new research exploring the opportunities of bioelectronic medicine for improving glucose control in people with diabetes, including regulation of gastric emptying, insulin sensitivity, and secretion of pancreatic hormones. Moreover, the development of novel closed-loop strategies aims to provide effective, specific and safe interfacing with the nervous system, and thereby targeting the organ of interest. This is especially valuable in the context of chronic diseases such as diabetes, where closed-loop bioelectronic medicine promises to provide real-time, autonomous and patient-specific therapies. In this article, we present an overview of the state-of-the-art for closed-loop neuromodulation systems in relation to diabetes and discuss future related opportunities for management of this chronic disease.

The continuing quest for better subcutaneously administered prandial insulins: a review of recent developments and potential clinical implications

The class of rapid-acting insulin analogues were introduced more than 20 years ago to control postprandial plasma glucose (PPG) excursions better than unmodified regular human insulin. Insulins, lispro, aspart and glulisine all achieved an earlier onset of action, greater peak effect and shorter duration of action resulting in lower PPG levels and a reduced risk of late postprandial hypoglycaemia. However, the subcutaneous absorption rate of these analogues still fails to match the physiological profile of insulin in the systemic circulation following a meal. Recent reformulations of aspart and lispro have generated a second generation of more rapid-acting insulin analogue candidates, including fast-acting aspart (faster aspart), ultra-rapid lispro and BioChaperone Lispro. These modifications have the potential to mimic physiological prandial insulin secretion better with an even earlier onset of action with improved PPG control, shorter duration of effect and reduced risk of hypoglycaemia. Recent phase 3 trials in type 1 and type 2 diabetes show that faster aspart and ultra-rapid lispro compared with conventional aspart and lispro, achieved fewer PPG excursions with a small increase in post-meal hypoglycaemia but similar or marginally superior glycated haemoglobin levels, and suggest the need for parallel optimization of basal insulin replacement. Phase 1 trials for BioChaperone Lispro are equally encouraging with phase 3 trials yet to be initiated. Comparative analysis of the clinical and pharmacological evidence for these new prandial insulin candidates in the treatment of type 1 and type 2 diabetes is the main focus of this review.

Role of Glucagon in Automated Insulin Delivery

Treatment of type 1 diabetes with exogenous insulin often results in unpredictable daily glucose variability and hypoglycemia, which can be dangerous. Automated insulin delivery systems can improve glucose control while reducing burden for people with diabetes. One approach to improve treatment outcomes is to incorporate the counter-regulatory hormone glucagon into the automated delivery system to help prevent the hypoglycemia that can be induced by the slow pharmacodynamics of insulin action. This article explores the advantages and disadvantages of incorporating glucagon into dual-hormone automated hormone delivery systems.

Dynamic Rule-Based Algorithm to Tune Insulin-on-Board Constraints for a Hybrid Artificial Pancreas System

The artificial pancreas (AP) is a system intended to control blood glucose levels through automated insulin infusion, reducing the burden of subjects with type 1 diabetes to manage their condition. To increase patients' safety, some systems limit the allowed amount of insulin active in the body, known as insulin-on-board (IOB). The safety auxiliary feedback element (SAFE) layer has been designed previously to avoid overreaction of the controller and thus avoiding hypoglycemia. In this work, a new method, so-called “dynamic rule-based algorithm,” is presented in order to adjust the limits of IOB in real time. The algorithm is an extension of a previously designed method which aimed to adjust the limits of IOB for a meal with 60 grams of carbohydrates (CHO). The proposed method is intended to be applied on hybrid AP systems during 24 h operation. It has been designed by combining two different strategies to set IOB limits for different situations: (1) fasting periods and (2) postprandial periods, regardless of the size of the meal. The UVa/Padova simulator is considered to assess the performance of the method, considering challenging scenarios. In silico results showed that the method is able to reduce the time spent in hypoglycemic range, improving patients' safety, which reveals the feasibility of the approach to be included in different control algorithms.