Premeal Bolus Research Articles

Mitigating iftar-related glycemic excursions in adolescents and young adults with type 1 diabetes on MiniMed™ 780G advanced hybrid closed loop system: a randomized clinical trial for adjunctive oral vildagliptin therapy during Ramadan fasting

BackgroundRamadan Iftar meal typically causes glucose excursions. Dipeptidyl peptidase-4 inhibitors increase glucagon-like peptide-1 and thus, decrease blood glucose levels with low risk of hypoglycemia.AimTo investigate the efficacy and safety of vildagliptin as an add-on therapy on glucose excursions of Iftar Ramadan meals among adolescents and young adults with type 1 diabetes mellitus (T1DM) using advanced hybrid closed-loop (AHCL) treatment.MethodsFifty T1DM patients on MiniMed™ 780G AHCL were randomly assigned either to receive vildagliptin (50 mg tablet) with iftar meal during Ramadan month or not. All participants received pre-meal insulin bolus based on insulin-to-carbohydrate ratio (ICR) for each meal constitution.ResultsVildagliptin offered blunting of post-meal glucose surges (mean difference − 30.3 mg/dL [− 1.7 mmol/L] versus − 2.9 mg/dL [− 0.2 mmol/L] in control group; p < 0.001) together with concomitant exceptional euglycemia with time in range (TIR) significantly increased at end of Ramadan in intervention group from 77.8 ± 9.6% to 84.7 ± 8.3% (p = 0.016) and time above range (180–250 mg/dL) decreased from 13.6 ± 5.1% to 9.7 ± 3.6% (p = 0.003) without increasing hypoglycemia. A significant reduction was observed in automated daily correction boluses and total bolus dose by 23.9% and 16.3% (p = 0.015 and p < 0.023, respectively) with less aggressive ICR settings within intervention group at end of Ramadan. Coefficient of variation was improved from 37.0 ± 9.4% to 31.8 ± 7.1%; p = 0.035). No severe hypoglycemia or diabetic ketoacidosis were reported.ConclusionAdjunctive vildagliptin treatment mitigated postprandial hyperglycemia compared with pre-meal bolus alone. Vildagliptin significantly increased TIR while reducing glycemic variability without compromising safety.Trial registration This trial was registered under ClinicalTrials.gov Identifier no. NCT06021119.

926-P: Implementation of a Novel AutoBolus Feature in an Automated Insulin Delivery (AID) System

AID systems aim to reduce mental burden experienced by people with diabetes by automatically adjusting insulin delivery in response to real-time glucose levels; however, systems still require pre-meal boluses for optimal outcomes. A system providing an automatic bolus response (‘AutoBolus’) to rising glucose levels (e.g., after meals) lessens user burden and reduces hyperglycemic events by compensating for missed or under-estimated pre-meal boluses. We propose a novel method to deliver an AutoBolus based on rising glucose levels via a machine learning based meal detection algorithm. AutoBolus meal detection is paired with a two-part novel insulin delivery scheme with an immediate safe upfront delivery, followed by temporarily tuning AID algorithm parameters to progressively respond to the post-prandial glucose response by delivering additional insulin. If a decreasing glucose condition is detected, the AID algorithm parameters revert to baseline. In-silico simulation demonstrates AutoBolus increases time in euglycemia by as much as 11% in adolescents, 8% in adults, and 6% in children for missed boluses for three meals in a 24-hour period. Our results show that the proposed AutoBolus insulin delivery partially compensates for missed pre-meal boluses increasing time in euglycemia, reducing user burden. Figure. Illustrative diagram showing the two-part novel insulin delivery scheme upon meal detection. Disclosure R.Narayanaswami: None. Y.Zheng: Employee; Insulet Corporation. W.J.Whiteley: Employee; Insulet Corporation. M.Sevil: None. S.Salavati: Employee; Insulet Corporation.

925-P: Postprandial Glucose Control Using an Extended Bolus for High Fat High Protein (HFHP) Meals during Closed-Loop (CL) in Patients with Type 1 Diabetes (T1D)

We investigated the impact of an extended bolus (EB) for a HFHP breakfast on postprandial glycemia in adolescents with T1D using the Control IQ (CIQ) system. In a randomized cross-over trial, following optimization, the participants with CIQ were asked to have identical standardized HFHP breakfasts (carbohydrate:51 g, fat:40 g, protein:54 g). Meal insulin bolus infusion began within 0.25 hrs of meal consumption (time 0). Eight adolescents (mean age 15.2 ± 1.7 yrs) were randomly assigned in blocks of two to the order in which they received the extended and standard insulin bolus (SB). Postprandial sensor glucose (SG) was measured for 5 hrs. The 5-hr incremental area under the curves (AUC) for SG was comparable for EB and SB (8913 and 10305 mg/dl/min, respectively). Peak SG value, time to peak SG, time in range SG (69.75% for SB vs. 71.7% for EB) and percent time &amp;gt;180 mg/dl were similar in both groups; however, the AUC for SG 2 hrs post meal onset and the rise in SG was significantly higher with EB (p= 0.02 and 0.03 respectively). Insulin use was not significantly different between arms. CL cannot fully compensate for a HFHP meal. However, SB appears to achieve better glycemic control than EB during the two hour postprandial period. Further studies with a larger sample size and larger and longer extended meal boluses may be needed to optimize pre-meal bolus dosing for HFHP meals. Disclosure L.Ekhlaspour: Consultant; Ypsomed AG, Tandem Diabetes Care, Inc., Other Relationship; NIH - National Institutes of Health, Research Support; MannKind Corporation, Tandem Diabetes Care, Inc., JDRF, Speaker's Bureau; Insulet Corporation. Y.J.Hosseinipour: None. B.A.Buckingham: Advisory Panel; Medtronic, Novo Nordisk, Consultant; Lilly, Research Support; Medtronic, Insulet Corporation, Tandem Diabetes Care, Inc. E.Cengiz: Advisory Panel; Eli Lilly and Company, Adocia, Novo Nordisk, Arecor. Funding National Institutes of Health (1K23DK121942)

Missed meal boluses and poorer glycemic control impact on neurocognitive function may be associated with white matter integrity in adolescents with type 1 diabetes.

The notion that pediatric type 1 diabetes impacts brain function and structure early in life is of great concern. Neurological manifestations, including neurocognitive and behavioral symptoms, may be present from childhood, initially mild and undetectable in daily life. Despite intensive management and technological therapeutic interventions, most pediatric patients do not achieve glycemic control targets for HbA1c. One of the most common causes of such poor control and frequent transient hyperglycemic episodes may be lifestyle factors, including missed meal boluses. The aim of this study was to assess the association between specific neurocognitive accomplishments-learning and memory, inhibition ability learning, and verbal and semantic memory-during meals with and without bolusing, correlated to diffusion tensor imaging measurements of major related tracts, and glycemic control in adolescents with type 1 diabetes compared with their healthy siblings of similar age. This is a case-control study of 12- to 18-year-old patients with type 1 diabetes (N = 17, 8 male patients, diabetes duration of 6.53 ± 4.1 years) and their healthy siblings (N = 13). All were hospitalized for 30 h for continuous glucose monitoring and repeated neurocognitive tests as a function of a missed or appropriate pre-meal bolus. This situation was mimicked by controlled, patient blinded manipulation of lunch pre-meal bolus administration to enable capillary glucose level of <180 mg/dl and to >240 mg/d 2 hours after similar meals, at a similar time. The diabetes team randomly and blindly manipulated post-lunch glucose levels by subcutaneous injection of either rapid-acting insulin or 0.9% NaCl solution before lunch. A specific neurocognitive test battery was performed twice, after each manipulation, and its results were compared, along with additional neurocognitive tasks administered during hospitalization without insulin manipulation. Participants underwent brain imaging, including diffusion tensor imaging and tractography. A significant association was demonstrated between glycemic control and performance in the domains of executive functions, inhibition ability, learning and verbal memory, and semantic memory. Inhibition ability was specifically related to food management. Poorer glycemic control (>8.3%) was associated with a slower reaction time. These findings highlight the potential impairment of brain networks responsible for learning, memory, and controlled reactivity to food in adolescents with type 1 diabetes whose glycemic control is poor.

A new proposal for a second insulin bolus to optimize postprandial glucose profile in adolescents with type 1 diabetes.

To evaluate whether a second insulin bolus, calculated with a new approach, could improve postprandial glucose (PPG) after the intake of real-life high-fat (HF) and high-protein (HP) mixed meals. Fifteen adolescents with T1D treated with non-automated insulin pumps and CGM were enrolled. Patients received standard, HF and HP mixed meals treated with one pre-meal insulin bolus; based on differences in PPG between standard, HF and HP meals, correction boluses were calculated (30% and 60% of pre-meal bolus for HF and HP meals, respectively). Then patients received the same HF or HP meal treated with pre-meal bolus plus second insulin bolus after 3h. Differences between postprandial variables after HF and HP meals treated with one or two insulin boluses were assessed by paired Student's t-test. Treating HF and HP meals with two insulin boluses significantly reduced the postprandial BG-AUC (21% and 26% respectively, p < 0.05), increased %TIR (from 52.5 to 78.3% for HF meal; from 32.7 to 57.1% for HP meal; p < 0.01), and reduced mean BG and %TAR (p < 0.01), with no differences in %TBR. The new way to calculate and administer correction boluses 3h after HF and HP meals is effective and safe in reducing PPG and the hypoglycemia risk.

Optimal Prandial Timing of Insulin Bolus in Youths with Type 1 Diabetes: A Systematic Review.

The aim of this systematic review was to report the evidence on optimal prandial timing of insulin bolus in youths with type 1 diabetes. A systematic search was performed including studies published in the last 20 years (2002-2022). A PICOS framework was used in the selection process and evidence was assessed using the GRADE system. Up to one third of children and adolescents with type 1 diabetes injected rapid-acting insulin analogues after a meal. Moderate-high level quality studies showed that a pre-meal bolus compared with a bolus given at the start or after the meal was associated with a lower peak blood glucose after one to two hours, particularly after breakfast, as well as with reduced HbA1c, without any difference in the frequency of hypoglycemia. There were no differences related to the timing of bolus in total daily insulin and BMI, although these results were based on a single study. Data on individuals' treatment satisfaction were limited but did not show any effect of timing of bolus on quality of life. In addition, post-prandial administration of fast-acting analogues was superior to rapid-acting analogues on post-prandial glycemia. There was no evidence for any difference in outcomes related to the timing of insulin bolus across age groups in the two studies. In conclusion, prandial insulin injected before a meal, particularly at breakfast, provides better post-prandial glycemia and HbA1c without increasing the risk of hypoglycemia, and without affecting total daily insulin dose and BMI. For young children who often have variable eating behaviors, fast-acting analogues administered at mealtime or post-meal could provide an additional advantage.

Diabete hi-tech

Recently, technological innovations have radically changed diabetes care. Insulin pumps and continuous glucose monitoring systems have significantly improved diabetes outcomes in both children and adults with Type 1 diabetes. For this reason, the major international associations recommend the use of technology in the management of Type 1 diabetes. The limitations of glycemic self-monitoring have prompted research to develop alternative techniques, favouring the expansion of continuous blood glucose monitoring systems (CGMs). CGM measures interstitial glucose through tiny sensors inserted in the subcutaneous tissue. Sensors can provide information in real time on the current glucose level and its trend. These data can be uploaded to the cloud and checked any time by doctors, patients and their caregivers. CGM can be combined with multiple daily injections (MDI) therapy or continuous subcutaneous insulin infusion (CSII). With CSII, basal insulin is supplied in the form of a continuous infusion and pre-meal bolus doses are calculated based on the meals’ carbohydrate content. A variety of insulin pumps is available, some of which can communicate with specific CGM devices, helping the patient to make better decisions about insulin dosing. This approach is known as sensor-augmented insulin pump therapy and it is the gold standard for the treatment of Type 1 diabetes in children and young adults, as recommended by the Italian Association of Paediatric Endocrinology and Diabetology. In the most recent systems, basal insulin delivery can be automatically modified through algorithms, based on CGM results, target glucose and the amount of active insulin, even though the patients still have to set the pre-meal insulin bolus manually. This system is defined as a partially hybrid closed-loop system, also known as artificial pancreas. Compared to MDI, CSII is associated with better control of blood glucose - measured by haemoglobin A1c and glycemic variability -, reduction of daily insulin requirement and an improvement of the quality of life. Psychophysical disabilities, language barriers or socio-economic disadvantage should not be considered limitations of CSII treatment as long as the caregiver is able to manage the therapy. Nowadays, MDI is recommended as first line therapy exclusively for those patients who do not want to use insulin pumps due to physical discomfort. The aim of this article is to provide updated information on the management of paediatric diabetes with modern technological devices for glucose monitoring and insulin delivery.

Personalized hybrid artificial pancreas using unidirectional sliding-modes control algorithm

This paper presents an artificial pancreas algorithm implemented with a discrete-time sliding-mode method combined with a nonlinear block controllable form using a unidirectional control law and a discrete adaptive observer. The algorithm is both unidirectional, using insulin as unique input, and hybrid with a percentage of the pre-meal bolus administered in advance to complement the control action. Personalisation combines patient clustering and individual gain calculation after analysing glucose time-in-range. The stability of the complete closed-loop system involving the observer bounds is tested using the Lyapunov methodology. The performance of the algorithm is evaluated with 256 patients, simulated using Hovorka’s model. The evaluation defines two scenarios (closed-loop and open loop with continuous subcutaneous insulin infusion, CSII), divided into three 1-week intervals, to respectively compare the impact of glucose control under the expected meal plan as a result of changes in carbohydrates quantities and meal schedule, and in response to more extreme events.The performance of time-in-range in each period obtained with CSII is improved by hybrid closed-loop in all cases, i.e., with the expected meals (weekdays 74.9 vs 78.4; weekends 71.5 vs 73.4), with meal variability (weekdays 74.3 vs 77.6; weekend 71.6 vs 72.7), and in the presence of transgressions (forgetting meal announcement: 50.1 vs 63.4; meal omission: 78.2 vs 82.03; copious meal: 60.1 vs 63.4). Compared to CSII, the personalised nonlinear block controller was able to increase the time-in-range without glucose presence in time below range level 2 for 98 % of the cohort for expected meals, meal variability, and transgressions.

Automated insulin delivery systems: from early research to routine care of type 1 diabetes.

Automated insulin delivery (AID) systems, so-called closed-loop systems or artificial pancreas, are based upon the concept of insulin supply driven by blood glucose levels and their variations according to body glucose needs, glucose intakes and insulin action. They include a continuous glucose monitoring device which provides a signal to a control algorithm tuning insulin delivery from an infusion pump. The control algorithm is the key of the system since it commands insulin administration in order to maintain blood glucose in a predefined target range and close to a near-normal glucose level. The last two decades have shown dramatic advances toward the use in free life of AID systems for routine care of type 1 diabetes through step-by-step demonstrations of feasibility, safety and efficacy in successive hospital, transitional and outpatient trials. Because of the constraints of pharmacokinetics and dynamics of subcutaneous insulin delivery, the currently available AID systems are all 'hybrid' or 'semi-automated' insulin delivery systems with a need of meal and exercise announcements in order to anticipate rapid glucose variations through pre-meal bolus or pre-exercise reduction of infusion rate. Nevertheless, these AID systems significantly improve time spent in a near-normal range with a reduction of the risk of hypoglycemia and the mental load of managing diabetes in everyday life, representing a milestone in insulin therapy. Expected progression toward fully automated, further miniaturized and integrated, possibly implantable on long-term and more physiological closed-loop systems paves the way for a functional cure of type 1 diabetes.

An effective and cost-saving structured education program teaching dynamic glucose management strategies to a socio-economically deprived cohort with type 1 diabetes in a VIRTUAL setting.

Compare the clinical and cost-effectiveness of an established face to face (F2F) structured education program to a new remote (VIRTUAL) program teaching dynamic glucose management (DynamicGM) to children and young people with type 1 diabetes (CYPD) using continuous glucose monitoring (CGM). To ascertain the most effective DynamicGM strategies predicting time in range (TIR) (3.9-10.0 mmol/L) and incorporating these into a user-friendly teaching aid. Effectiveness of the F2F and VIRTUAL programs were ascertained by comparing the mean change (Δ) from baseline to 6 months in HbA1c, TIR and severe hypoglycemia. Delivery cost for the two programs were evaluated. Factors predicting TIR in the combined cohort were determined and incorporated into a user-friendly infographic. First 50 graduates per group were evaluated. The mean difference in Δ HbA1c, Δ TIR and Δ episodes of severe hypoglycemia between VIRTUAL and F2F groups were 1.16 (p= 0.47), 0.76 (p= 0.78) and -0.06 (p= 0.61) respectively. Delivery cost per 50 CYPD for VIRTUAL and F2F were $5752 and $7020, respectively. The strongest predictors of TIR (n= 100) were short bursts of exercise (10-40min) to lower hyperglycemia (p< 0.001), using trend arrow adjustment tools (p< 0.001) and adjusting pre-meal bolus timing based on trend arrows (p< 0.01). These strategies were translated into a GAME (Stop highs), SET (Stay in target), MATCH (Prevent lows) mnemonic. Teaching DynamicGM VIRTUALLY is just as effective as F2F delivery and cost saving. Short bursts of exercise and using CGM trend arrows to adjust insulin dose and timing improves TIR.

772-P: Combining Meal-Bolus Reduction and Exercise Announcement Eliminates the Risk of Hypoglycemia during Postprandial Exercise in People Living with Type 1 Diabetes Treated with Automated Insulin Delivery Systems

For people living with type 1 diabetes (PWT1D) post-prandial exercise remains a challenge for the maintenance of glycemic control even with automated insulin delivery systems (AID) . During the postprandial phase, elevated insulin levels, rapid changes in glucose levels with increased CGM lag time make it difficult for AID algorithms to mitigate the risk of hypoglycemia by solely relying on basal rate modulation. The main objective of this study was to assess the safety and efficacy of AID using a combination strategy of pre-meal exercise announcement and meal bolus reduction during exercise bouts performed 1- and 2-hours post-meal. Thirteen adults PWT1D chronically treated with AID (6 females; A1c = 7.9 ± 0.6%; Age= 53,5 ± 15,5 years; T1D duration= 29.0 ± 16.0 years) were included. Participants performed in a randomized crossover fashion 2 60-min exercise sessions (60% of VO2peak) , 1 (60Ex) and 2-h (120Ex) post-meal. A standardized meal was given at 8AM with a 33% insulin bolus reduction and exercise was announced to the AID algorithm (target glucose increased from 6 to 9 mmol/L) up to the end of each exercise session. Plasma glucose was collected regularly. Plasma glucose times in range (3.9-10.0 mmol/L) and above range (&amp;gt;10.0 mmol/L) from exercise onset to 90-min-post-exercise, were similar between Ex60 and Ex120 (63.7 ± 41.4% Ex60 vs. 65.9 ±24.9% Ex120, p=0.3; 36.1 ± 41.6% Ex60 vs. 34.1 ± 24.9% Ex120, p=0.4, respectively) . No hypoglycemic events (&amp;lt;3.9 mmol/L) occurred during the study. The mean reduction in plasma glucose levels were similar during exercise in both conditions (-2.6 ± 1.4 mmol/L Ex60 vs. -3.5 ± 2.2 mmol/L Ex120, p=0.2) Conclusion: combining pre-meal exercise announcement with a meal bolus reduction of 33% was effective and safe at preventing postprandial exercise hypoglycemia in PWT1D treated with AID whether exercise was performed 1 or 2-h after a meal. Disclosure M.Raffray: None. R.Rabasa-lhoret: Consultant; HLS Therapeutics Inc., Pfizer Inc., Other Relationship; Abbott Diabetes, AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Janssen Pharmaceuticals, Inc., Medtronic, Merck &amp; Co., Inc., Novo Nordisk Canada Inc., Sanofi, Vertex Pharmaceuticals Incorporated, Research Support; Canadian Institutes of Health Research, Cystic Fibrosis Canada, Diabetes Canada, Fondation Francophone pour la Recherche en Diabète (FFRD) , JDRF, National Institutes of Health, Société Francophone du Diabète (SFD) , Speaker's Bureau; Canadian Medical &amp; Surgical Knowledge Translation Research Group (CMS) , CPD Network, Tandem Diabetes Care, Inc. É.Myette-côté: None. J.Molveau: None. M.Devaux: None. Z.Wu: Other Relationship; Eli Lilly and Company. Funding National Institutes of Health (A12BC345678)

Abstract 21: The burden of mealtime insulin dosing in adults and children with type 1 diabetes

Background and Aims: Timely and accurate mealtime insulin dosing is an ongoing challenge for people with type 1 diabetes (T1D). This multinational study aimed to assess attitudes, behaviours and the overall impact of pre-meal (15-20 minutes) bolus insulin dosing from the perspective of adults with T1D, parents of children with T1D and physicians.Materials and Methods: Online surveys were conducted in 2711 participants (recruited from an online panel) who chose to take part across USA, Canada, UK, Japan, Spain and France between 25 Nov 2019 and 06 Feb 2020. Participants were 1401 adults aged ≥18 with T1D, 350 parents who live with children with T1D aged ≤15 years and 960 physicians who have practised for 4-40 years. Adults/children had T1D for ≥6 months and were taking a bolus insulin (excluding fast-acting insulinaspart). Physicians were responsible for starting or managing treatment for T1D and the prescription of mealtime insulin. This analysis provides a country average assuming equal sizes for each country, to give an overall indication of results across the six countries in the study.Results: Of the surveyed adults with T1D (46% male; mean age was 43 years; mean of 19 years with T1D), 72% administered their bolus insulin by injection and 28% used an insulin pump. Continuous glucose monitoring (CGM) was used by 43% of adults. Of the parents surveyed (64% male; mean age was 10 years; mean of 4 years with T1D), 74% administered their bolus insulin by injection and 26% used an insulin pump, with 58% using CGM. The findings indicate that a majority (96%) of both adults with T1D and parents of children with T1D understood the importance of administering bolus insulin accurately. However, few adults (35%) and parents (47%) felt very confident in estimating the amount of insulin required accurately and 91% of adults and 96% of parents experienced challenge(s) with pre-meal insulin dosing. Almost all physicians (99.6%) reported that they believed their patients with T1D faced challenge(s) with pre-meal bolus insulin dosing. Of those surveyed, 25% of adults and 38% of parents forgot to administer pre-meal insulin ≥1 a week, and 70%of adults and 81%of parents reported that they/their child ate more or less than anticipated following their mealtime insulin ≥1 aweek. Accordingly, 68% of adults and 79% of parents indicated that they/their child needed to take corrective action ≥1 a week by either eating more or taking more insulin. A majority of participants (82% of adults, 93% of parents) felt that administering insulin 15-20 minutes before a meal had a negative impact on their/their child's day-to-day life; 91% of physicians concurred that this creates an extra burden in the day-to-day lives of people with T1D. When asked their preference, 73%of adults and 67% of parents preferred bolus insulin administration either immediately before (42% adults, 44% parents) or after (31% adults, 23% parents) a meal. A high proportion of adults with T1D (67%) and parents (72%) claimed that taking bolus insulin immediately before or after a meal would have a positive impact on their overall quality of life.Conclusion: Based on the study findings, although the importance of accurate mealtime dosing was well recognized, bolus insulin dosing still poses clear challenges to most people with T1D. Given the choice, the majority of participants would prefer to administer insulin immediately prior to or following a meal, as this was perceived to improve quality of life.

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

Aims/hypothesisThe 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).MethodsThe 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 HbA1c 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.ResultsBreakfast, 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/interpretationThis 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.Graphical abstract

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

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

Impact of glucagon response on early postprandial glucose excursions irrespective of residual β-cell function in type 1 diabetes: A cross-sectional study using a mixed meal tolerance test.

Aims/IntroductionControlling postprandial glucose levels in patients with type 1 diabetes is challenging even under the adequate treatment of insulin injection. Recent studies showed that dysregulated glucagon secretion exacerbates hyperglycemia in type 2 diabetes patients, but little is known in type 1 diabetes patients. We investigated whether the glucagon response to a meal ingestion could influence the postprandial glucose excursion in patients with type 1 diabetes.Materials and MethodsWe enrolled 34 patients with type 1 diabetes and 23 patients with type 2 diabetes as controls. All patients underwent a liquid mixed meal tolerance test. We measured levels of plasma glucose, C‐peptide and glucagon at fasting (0 min), and 30, 60 and 120 min after meal ingestion. All type 1 diabetes patients received their usual basal insulin and two‐thirds of the necessary dose of the premeal bolus insulin.ResultsThe levels of plasma glucagon were elevated and peaked 30 min after the mixed meal ingestion in both type 1 diabetes and type 2 diabetes patients. The glucagon increments from fasting to each time point (30, 60 and 120 min) in type 1 diabetes patients were comparable to those in type 2 diabetes patients. Among the type 1 diabetes patients, the glucagon response showed no differences between the subgroups based on diabetes duration (<5 vs ≥5 years) and fasting C‐peptide levels (<0.10 vs ≥0.10 nmol/L). The changes in plasma glucose from fasting to 30 min were positively correlated with those in glucagon, but not C‐peptide, irrespective of diabetes duration and fasting C‐peptide levels in patients with type 1 diabetes.ConclusionsThe dysregulated glucagon likely contributes to postprandial hyperglycemia independent of the residual β‐cell functions during the progression of type 1 diabetes.

Evidence Generation for Postprandial Insulin Administration for Better Management of Diabetes in Noncritically iII Patients

Introduction: Previously, premeal sliding scale insulin regimen was used to control sugar levels in hospitalized type-2 diabetes patients. However, the now recommended basal-bolus regimen also failed to show any substantial advantage over the traditional sliding scale regimen in the latest Cochrane review. Methodology: In this retrospective cohort study, data were collected from two groups of patients who received basal with premeal bolus regimen and those who received modified sliding scale regimen (basal with both pre- and lower dose postprandial insulin by sliding scale). The data collected were analyzed to compare the mean reduction in blood glucose level, number of hypoglycemic episodes, and mean hospital stay among the two groups. Results: A total of forty patients were included in the study. Twenty received basal with both pre- and postprandial insulin correction by sliding scale and other twenty received basal insulin with postmeal bolus correction regimen. The mean hospital stay in sliding scale with postprandial insulin correction was 3.9 ± 2.2 days, and in other group, it was 6.1 ± 4.47 days. Two out of twenty patients in the sliding scale with postprandial insulin group, whereas six out of twenty patients in the other group had hypoglycemic events. Conclusion: Basal with both pre- and postmeal (low dose) insulin by sliding scale might be an answer to the concerns of faster attainment of euglycemia in hospitalized type-2 diabetes patients with minimal risk of hypoglycemia. We plan a prospective study with a larger sample size to substantiate the evidence.

Effect of Afrezza on Glucose Dynamics During HCL Treatment.

A major obstacle in optimizing the performance of closed-loop automated insulin delivery systems has been the delay in insulin absorption and action that results from the subcutaneous (SC) route of insulin delivery leading to exaggerated postmeal hyperglycemic excursions. We aimed to investigate the effect of Afrezza inhaled insulin with ultrafast-in and -out action profile on improving postprandial blood glucose control during hybrid closed-loop (HCL) treatment in young adults with type 1 diabetes. We conducted an inpatient, three-way, randomized crossover standardized meal study to assess the efficacy and safety of Afrezza at a low (AL) and a high (AH) dose as compared with a standard SC rapid-acting insulin (aspart) premeal bolus during Diabetes Assistant (DiAs) HCL treatment. Participants received two sequential meals on three study days, and premeal insulin bolus was determined based on home insulin-to-carbohydrate ratio for each meal (rounded up to the closest available Afrezza cartridge dose for AH and down for AL). The primary efficacy outcome was the peak postprandial plasma glucose (PPG) level calculated by pooling data for up to 4 h after the start of each meal. Secondary outcomes included hyperglycemic, hypoglycemic, and euglycemic venous glucose metrics. The mean ± SD PPG for the rapid-acting insulin control arm and AH was similar (185 ± 50 mg/dL vs. 195 ± 46 mg/dL, respectively; P = 0.45), while it was higher for meals using AL (208 ± 54 mg/dL, P = 0.04). The AH achieved significantly lower early PPG level than the control arm (30 min; P < 0.001), and improvement in PPG waned at later time points (120 and 180 min; P = 0.02) coinciding with the end of Afrezza glucodynamic action. Afrezza (AH) premeal bolus reduced the early glycemic excursion and improved PPG during HCL compared with aspart premeal bolus. The improvement in PPG was not sustained after the end of Afrezza glucodynamic action at 120 min.

201-OR: Automated Insulin Delivery (AID) System Performance with and without Meal Announcement: Effect of Meal Macronutrient Content

Missed meal boluses contribute to suboptimal glucose control. There has been limited evaluation of missed boluses for complex or high glycemic index meals while on hybrid closed loop AID systems. Ten subjects with type 1 diabetes (50% male), age 52±10 y, A1C 7.1±0.9%, insulin requirement 0.5±0.2 U/kg/day, used the Lilly investigational AID system (model predictive control algorithm) during a 48 h inpatient observation with 6 meals. For each subject, the 2 breakfast (pancake; [60 g carbohydrate (CHO), 15±4 g fat]) and 2 dinner (pizza; [53±3 g CHO, 20±1 g fat]) meals were identical, and were consumed with or without a pre-meal insulin bolus. Lunch meals were subject-selected (44±16 g CHO, 7±5 g fat), and appropriate pre-meal boluses were administered. Time-in-range (TIR, 70-180 mg/dL) overnight was 99.2±9.5% and following the lunches was 82.1±26.4%. In contrast, TIR following pancake and pizza challenges with bolus were 56.0±34.4% and 65.8±29.6%, and without bolus were 17.8±5.1% and 36.5±25.2%, respectively. Incremental area under the curve (0-2 h) following the pancake meal was larger than the pizza meal within both the bolused and non-bolused scenarios (Table). This study highlights the importance of structured, but varied meal challenge tests in the evaluation of AID system performance. Meal macronutrient content affects AID performance in bolused and non-bolused scenarios. Disclosure A. Bartee: None. R.L. Brazg: None. M. Katz: Employee; Self; Eli Lilly and Company. Stock/Shareholder; Self; Eli Lilly and Company. A. LaLonde: Employee; Self; Eli Lilly and Company. Stock/Shareholder; Self; Eli Lilly and Company. H. Wolpert: Employee; Self; Eli Lilly and Company. R. Jones: Employee; Self; Eli Lilly and Company. Stock/Shareholder; Self; Eli Lilly and Company.

Decision Support Systems for Insulin Treatment Adjustment in People with Type 1 Diabetes.

For people with type 1 diabetes, achieving optimal glycemic control requires use of intensive insulin therapy. To achieve this goal individuals are required to become proficient in accurately determining the appropriate amount of insulin needed to address a variety of situations throughout the day while considering numerous influencing factors. They also need to perform multiple tasks a day such as counting carbohydrates to accurately determine the required premeal bolus. There is also a need to periodically adjust insulin dosing as insulin sensitivity varies considerably over time. Sophisticated advanced technologies are being used by growing numbers of individuals to manage diabetes. However, despite innovations in glucose monitoring technologies and new insulin formulations, many of these individuals are not achieving their glycemic goals. The new technologies provide ample amount of valuable diabetes related data that may complicate even further the insulin dosing decision making for people with diabetes as well as for the health care providers. Mobile health, digital tools and decision support systems can help to increase accurate, timely insulin dosing and insulin titration and holds the potential to improve glycemic control to a wide range of individuals with diabetes. The emerging mobile toolbox for insulin dosing adjustments that will be reviewed in this paper includes insulin management Apps; diverse range of Apps to guide insulin adjustments such as in times of physical activity and eating; data management systems which enable visualization and analysis of insulin and glucose data of various devices; real-time alarms and glucose prediction Apps that help to prevent hypoglycemia and hyperglycemia events; various bolus calculators for meal time dosing; sophisticated decision support algorithms for people using insulin pump, multiple insulin injections and closed loop systems for real-time and retrospective insulin dosing adjustments.

In Silico Analysis of an Exercise-Safe Artificial Pancreas With Multistage Model Predictive Control and Insulin Safety System.

Maintaining glycemic equilibrium can be challenging for people living with type 1 diabetes (T1D) as many factors (eg, length, type, duration, insulin on board, stress, and training) will impact the metabolic changes triggered by physical activity potentially leading to both hypoglycemia and hyperglycemia. Therefore, and despite the noted health benefits, many individuals with T1D do not exercise as much as their healthy peers. While technology advances have improved glucose control during and immediately after exercise, it remains one of the key limitations of artificial pancreas (AP) systems, largely because stopping insulin at the onset of exercise may not be enough to prevent impending, exercise-induced hypoglycemia. A hybrid AP algorithm with subject-specific exercise behavior recognition and anticipatory action is designed to prevent hypoglycemic events during and after moderate-intensity exercise. Our approach relies on a number of key innovations, namely, an activity informed premeal bolus calculator, personalized exercise pattern recognition, and a multistage model predictive control (MS-MPC) strategy that can transition between reactive and anticipatory modes. This AP design was evaluated on 100 in silico subjects from the most up-to-date FDA-accepted UVA/Padova metabolic simulator, emulating an outpatient clinical trial setting. Results with a baseline controller, a regular MPC (rMPC), are also included for comparison purposes. In silico experiments reveal that the proposed MS-MPC strategy markedly reduces the number of exercise-related hypoglycemic events (8 vs 68). An anticipatory mode for insulin administration of a monohormonal AP controller reduces the occurrence of hypoglycemia during moderate-intensity exercise.