Twenty-Four Hour Fasting (Basal Rate) Tests to Achieve Custom-Tailored,Hour-by-Hour Basal Insulin Infusion Rates in Patients With Type 1 Diabetes Using Insulin Pumps (CSII)

Background:Twenty-four hour fasting periods are being used to scrutinize basal insulin infusion rates for pump-treated patients with type 1 diabetes.Methods:Data from 339 consecutive in-patients with adult type 1 diabetes on insulin pump therapy undergoing a 24-hour fast as a basal rate test were retrospectively analyzed. Hourly programmed basal insulin infusion rates and plasma glucose concentrations within, below, or above arbitrarily defined target ranges were assessed for periods of the day of special interest (eg, 01:00-07:00 am, “dawn” period, 04:00-07:00 pm, and “dusk” period). Statistics: χ²-tests, paired t-tests were used.Results:Basal rates (mean: 0.90 ± 0.02 IU/h) showed circadian variations with peaks corresponding to “dawn” (1.07 ± 0.02 IU/h from 01:00 to 07:00 am) and, less prominently, “dusk” (0.95 ± 0.02 IU/h from 03:00 to 07:00 pm). Individual mean plasma glucose concentrations averaged 6.6 ± 0.1 mmol/L, with 53.1% in the predefined “strict” (4.4-7.2 mmol/L) target range. Interestingly, during the “dawn” period, plasma glucose was significantly higher (by 0.5 ± 0.1 mmol/L [95% confidence interval: 0.3-0.8 mmol/L; P < .0001]) and the odds ratio for hypoglycemia was significantly lower compared to the reference period.Interpretation:Twenty-four hour fasting periods as basal rate tests frequently unravel periods with inappropriate basal insulin infusion rates potentially responsible for fasting hyper- or hypoglycemia. Notably, the higher basal insulin infusion rate found during the “dawn” period seems to be justified and may need to be accentuated.     

Closed-loop driven by control-to-range algorithm outperforms threshold-low-glucose-suspend insulin delivery on glucose control albeit not on nocturnal hypoglycaemia in prepubertal patients with type 1 diabetes in a supervised hotel setting

This randomized control trial investigated glucose control with closed-loop (CL) versus threshold-low-glucose-suspend (TLGS) insulin pump delivery in pre-pubertal children with type 1 diabetes in supervised hotel conditions. The patients [n = 24, age range: 7-12, HbA1c: 7.5 ± 0.5% (58 ± 5 mmol/mol)] and their parents were admitted twice at a 3-week interval. CL control to range or TLGS set at 3.9 mmoL/L were assessed for 48 hour in randomized order. Admissions included three meals and one snack, and physical exercise. Meal boluses followed individual insulin/carb ratios. While overnight (22:00-08:00) per cent continuous glucose monitoring (CGM) time below 3.9 mmol/L (primary outcome) was similar, time in ranges 3.9 to 10.0 and 3.9 to 7.8 mmoL/L and mean CGM were all significantly improved with CL (P < 0.001). These results were confirmed over the whole 48 hour. Disconnections between devices and limited accuracy of glucose sensors in the hypoglycaemic range appeared as limiting factors for optimal control. CL mode was well accepted while fear of hypoglycaemia was unchanged. CL did not minimize nocturnal hypoglycaemia exposure but improved time in target range compared to TLGS. Although safe and well-accepted, CL systems would benefit from more integrated devices.     

Metabolic Control With the Bio-inspired Artificial Pancreas in Adults With Type 1 Diabetes: A 24-Hour Randomized Controlled Crossover Study

Background:

The Bio-inspired Artificial Pancreas (BiAP) is a closed-loop insulin delivery system based on a mathematical model of beta-cell physiology and implemented in a microchip within a low-powered handheld device. We aimed to evaluate the safety and efficacy of the BiAP over 24 hours, followed by a substudy assessing the safety of the algorithm without and with partial meal announcement. Changes in lactate and 3-hydroxybutyrate concentrations were investigated for the first time during closed-loop.

Methods:

This is a prospective randomized controlled open-label crossover study. Participants were randomly assigned to attend either a 24-hour closed-loop visit connected to the BiAP system or a 24-hour open-loop visit (standard insulin pump therapy). The primary outcome was percentage time spent in target range (3.9-10 mmol/l) measured by sensor glucose. Secondary outcomes included percentage time in hypoglycemia (<3.9 mmol/l) and hyperglycemia (>10 mmol/l). Participants were invited to attend for an additional visit to assess the BiAP without and with partial meal announcements.

Results:

A total of 12 adults with type 1 diabetes completed the study (58% female, mean [SD] age 45 [10] years, BMI 25 [4] kg/m², duration of diabetes 22 [12] years and HbA1c 7.4 [0.7]% [58 (8) mmol/mol]). The median (IQR) percentage time in target did not differ between closed-loop and open-loop (71% vs 66.9%, P = .9). Closed-loop reduced time spent in hypoglycemia from 17.9% to 3.0% (P < .01), but increased time was spent in hyperglycemia (10% vs 28.9%, P = .01). The percentage time in target was higher when all meals were announced during closed-loop compared to no or partial meal announcement (65.7% [53.6-80.5] vs 45.5% [38.2-68.3], P = .12).

Conclusions:

The BiAP is safe and achieved equivalent time in target as measured by sensor glucose, with improvement in hypoglycemia, when compared to standard pump therapy.     

Closed-Loop Control Performance of the Hypoglycemia-Hyperglycemia Minimizer (HHM) System in a Feasibility Study

Background:This feasibility study investigated the insulin-delivery characteristics of the Hypoglycemia-Hyperglycemia Minimizer (HHM) System—an automated insulin delivery device—in participants with type 1 diabetes.Methods:Thirteen adults with type 1 diabetes were enrolled in this nonrandomized, uncontrolled, clinical-research-center-based feasibility study. The HHM System comprised a continuous subcutaneous insulin infusion pump, a continuous glucose monitor (CGM), and a model predictive control algorithm with a safety module, run on a laptop platform. Closed-loop control lasted approximately 20 hours, including an overnight period and two meals.Results:When attempting to minimize glucose excursions outside of a prespecified target zone, the predictive HHM System decreased insulin infusion rates below the participants’ preset basal rates in advance of below-zone excursions (CGM < 90 mg/dl), and delivered 80.4% less insulin than basal during those excursions. Similarly, the HHM System increased infusion rates above basal during above-zone excursions (CGM > 140 mg/dl), delivering 39.9% more insulin than basal during those excursions. Based on YSI, participants spent a mean ± standard deviation (SD) of 0.2 ± 0.5% of the closed-loop control time at glucose levels < 70 mg/dl, including 0.3 ± 0.9% for the overnight period. The mean ± SD glucose based on YSI for all participants was 164.5 ± 23.5 mg/dl. There were nine instances of algorithm-recommended supplemental carbohydrate administrations, and there was no severe hypoglycemia or diabetic ketoacidosis.Conclusions:Results of this study indicate that the current HHM System is a feasible foundation for development of a closed-loop insulin delivery device.     

Model-Based Closed-Loop Glucose Control in Type 1 Diabetes: The DiaCon Experience

Background

To improve type 1 diabetes mellitus (T1DM) management, we developed a model predictive control (MPC) algorithm for closed-loop (CL) glucose control based on a linear second-order deterministic-stochastic model. The deterministic part of the model is specified by three patient-specific parameters: insulin sensitivity factor, insulin action time, and basal insulin infusion rate. The stochastic part is identical for all patients but identified from data from a single patient. Results of the first clinical feasibility test of the algorithm are presented.

Methods

We conducted two randomized crossover studies. Study 1 compared CL with open-loop (OL) control. Study 2 compared glucose control after CL initiation in the euglycemic (CL-Eu) and hyperglycemic (CL-Hyper) ranges, respectively. Patients were studied from 22:00–07:00 on two separate nights.

Results

Each study included six T1DM patients (hemoglobin A1c 7.2% ± 0.4%). In study 1, hypoglycemic events (plasma glucose < 54 mg/dl) occurred on two OL and one CL nights. Average glucose from 22:00–07:00 was 90 mg/dl [74–146 mg/dl; median (interquartile range)] during OL and 108 mg/dl (101–128 mg/dl) during CL (determined by continuous glucose monitoring). However, median time spent in the range 70–144 mg/dl was 67.9% (3.0–73.3%) during OL and 80.8% (70.5–89.7%) during CL. In study 2, there was one episode of hypoglycemia with plasma glucose <54 mg/dl in a CL-Eu night. Mean glucose from 22:00–07:00 and time spent in the range 70–144 mg/dl were 121 mg/dl (117–133 mg/dl) and 69.0% (30.7–77.9%) in CL-Eu and 149 mg/dl (140–193 mg/dl) and 48.2% (34.9–72.5%) in CL-Hyper, respectively.

Conclusions

This study suggests that our novel MPC algorithm can safely and effectively control glucose overnight, also when CL control is initiated during hyperglycemia.     

Dessert Formulation Using Sucralose and Dextrin Affects Favorably Postprandial Response to Glucose,Insulin, and C-Peptide in Type 2 Diabetic Patients

BACKGROUND: Dessert compositions may conform to diabetic diet when it contains low sugar or artificial sweetener to replace sugar. However, it is still questionable whether glycemic control in type 2 diabetes patients is improved by the use of diet-conforming dessert compositions. OBJECTIVE: To compare, in type 2 diabetes patients, the glycemic, insulin, and C-peptide responses to seven modified dessert compositions for diabetics (D-dessert) with the response to seven similar desserts of non-modified composition, used as control desserts (C-dessert). METHODS: Seventy type 2 diabetes patients were allocated to seven groups of ten. On three occasions, each patient received either the meal which consisted of bread and cheese, or the meal and D-dessert, or the meal and the respective C-dessert. Differences in postprandial glucose, insulin, and C-peptide were evaluated using analysis of repeated measures at 0, 30, 60, 90, and 120 min after consumption. RESULTS: D-cake and D-pastry cream resulted in lower glucose levels (8.81 ± 0.32 mmol/l and 8.67 ± 0.36 mmol/l, respectively) and D-strawberry jelly in lower insulin levels (16.46 ± 2.66 μU/ml) than the respective C-desserts (9.99 ± 0.32 mmol/l for C-cake, 9.28 ± 0.36 mmol/l for C-pastry cream, and 27.42 ± 2.66 μU/ml for C-strawberry jelly) (p < 0.05). Compared with the meal, D-cake did not increase glucose or insulin levels (p > 0.05), while C-cake did (p < 0.05). D-pastry cream increased glucose to a lesser extent than C-pastry cream (p < 0.05). Similar effects were reported for D-milk dessert, D-millefeuille, and D-chocolate on glucose, insulin, and C-peptide at specific timepoints. D-crème caramel showed no effect. CONCLUSIONS: Some desserts formulated with sugar substitutes and soluble fiber may have a favorable effect on postprandial levels of glucose, insulin, and C-peptide in type 2 diabetic patients.     

Preliminary Evaluation of a New Semi-Closed-Loop Insulin Therapy System Over the Prandial Period in Adult Patients With Type 1 Diabetes: The WP6.0 Diabeloop Study

There is room for improvement in the algorithms used in closed-loop insulin therapy during the prandial period. This pilot study evaluated the efficacy and safety of the Diabeloop algorithm (model predictive control type) during the postprandial period. This 2-center clinical trial compared interstitial glucose levels over two 5-hour periods (with/without the algorithm) following a calibrated lunch. On the control day, the amount of insulin delivered by the pump was determined according to the patient’s usual parameters. On the test day, 50% or 75% of the theoretical bolus required was delivered, while the algorithm, informed of carbohydrate intake, proposed changes to insulin delivery every 15 minutes using modeling to forecast glucose levels. The primary endpoint was percentage of time spent at near normoglycemia (70-180 mg/dl). Twelve patients with type 1 diabetes (9 men, age 35.6 ± 12.7 years, HbA1c 7.3 ± 0.8%) were included. The percentage of time spent in the target range was 84.5 ± 20.8 (test day) versus 69.2 ± 33.9% (control day, P = .11). The percentage of time spent in hypoglycemia < 70 mg/dl was 0.2 ± 0.8 (test) versus 4.4 ± 8.2% (control, P = .18). Interstitial glucose at the end of the test (5 hours) was 127.5 ± 40.1 (test) versus 146 ± 53.5 mg/dl (control, P = .25). The insulin doses did not differ, and no differences were observed between the 50% and 75% boluses. In a semi-closed-loop configuration with manual priming boluses (25% or 50% reduction), the Diabeloop v1 algorithm was as successful as the manual method in determining the prandial bolus, without any exposure to excessive hypoglycemic risk.     

Omitting breakfast and lunch after injection of different long-acting insulin preparations at bedtime: a prospective study in patients with type 2 diabetes

Aims/hypothesis  The aim of this prospective trial was to compare the effect of different long-acting insulin preparations injected at bedtime on glucose concentrations in patients with type 2 diabetes omitting breakfast and lunch the next day. Methods  Twenty patients (ten women) with type 2 diabetes who were on an intensified insulin therapy participated. Mean (±SD) age was 63 ± 10 years, diabetes duration 18 ± 9 years, BMI 32.5 ± 5 kg/m², and HbA_1c 7.3 ± 0.7%. Patients received neutral protamine Hagedorn (NPH) insulin, insulin detemir or insulin glargine for at least 2 months; doses were adjusted to achieve morning blood glucose levels of <7 mmol/l. At the end of the respective treatment period, the long-acting insulin was injected at bedtime (at 22:45 hours) as usual but patients refrained from breakfast and lunch the next day; glucose was measured by a continuous glucose monitoring system (CGMS). Results   Comparable glucose target ranges were reached at midnight (5.8 to 6.1 mmol/l) and at 07:00 hours (6.7 to 6.9 mmol/l) with all three insulin preparations, using mean doses of 29 ± 10 U (NPH insulin), 33 ± 13 U (insulin detemir), and 32 ± 12 U (insulin glargine). Glucose levels between midnight and 07:00 hours were not significantly different for the three insulin preparations. Symptomatic hypoglycaemia did not occur from 08:00 to 16:00 hours; glucose concentrations during this time were slightly lower with NPH insulin than with insulin detemir (p = 0.012) and insulin glargine (p = 0.049). Conclusions/interpretation  Following bedtime injection of NPH insulin or of the analogues insulin detemir or insulin glargine, fasting glucose <7 mmol/l was achieved in the morning, without subsequent hypoglycaemia when participants continued to fast during the day.     

Biochemical evidence for the requirement of continuous glucose therapy in young adults with type 1 glycogen storage disease

Summary To determine whether patients with GSD-1 need nocturnal glucose therapy after completing physical growth and development, studies were performed on two consecutive nights. On the first night uncooked cornstarch (UCS) was given at the calculated glucose production rate at 21:00 h and 02:00 h. On the second night UCS was given at 21:00 h but omitted at 02:00 h. Six GSD-1 patients, aged 17.2–20.9 years, previously treated with continuous glucose therapy were studied. Measurements were made of plasma glucose (PG), serum insulin, growth hormone, cortisol, plasma glucagon (n=4), and blood lactate at 30–60-min intervals. Serum uric acid, cholesterol, and triglycerides were measured at 21:00 h and 07:00 h, and serum FFA at 21:00 h, 02:00 h and 07:00 h on the first night and immediately before treatment for hypoglycaemia on the second night.For five hours after UCS at 21:00 h, mean PG, serum insulin and blood lactate concentrations were similar on the two nights. With UCS at 02:00 h, mean PG concentrations were 4.1 mmol/L from 02:00 to 07:00 h. Without UCS at 02:00 h, in all subjects PG concentrations fell to <2.5 mmol/L after 6.5–8.5 h and mean blood lactate concentration increased to 7.4±3.0 mmol/L.Young adults with GSD-1 developed hypoglycaemia and hyperlactataemia after a relatively brief period without exogenous glucose and, therefore, need to continue nocturnal glucose therapy to prevent fasting hypoglycaemia.     

Artificial Pancreas Systems: Overnight Closed-Loop Insulin Delivery with Model Predictive Control: Assessment of Hypoglycemia and Hyperglycemia Risk Using Simulation Studies

Background

Hypoglycemia and hyperglycemia during closed-loop insulin delivery based on subcutaneous (SC) glucose sensing may arise due to (1) overdosing and underdosing of insulin by control algorithm and (2) difference between plasma glucose (PG) and sensor glucose, which may be transient (kinetics origin and sensor artifacts) or persistent (calibration error [CE]). Using in silico testing, we assessed hypoglycemia and hyperglycemia incidence during over-night closed loop. Additionally, a comparison was made against incidence observed experimentally during open-loop single-night in-clinic studies in young people with type 1 diabetes mellitus (T1DM) treated by continuous SC insulin infusion.

Methods

Simulation environment comprising 18 virtual subjects with T1DM was used to simulate overnight closed-loop study with a model predictive control (MPC) algorithm. A 15 h experiment started at 17:00 and ended at 08:00 the next day. Closed loop commenced at 21:00 and continued for 11 h. At 18:00, protocol included meal (50 g carbo-hydrates) accompanied by prandial insulin. The MPC algorithm advised on insulin infusion every 15 min. Sensor glucose was obtained by combining model-calculated noise-free interstitial glucose with experimentally derived tran-sient and persistent sensor artifacts associated with FreeStyle Navigator® (FSN). Transient artifacts were obtained from FSN sensor pairs worn by 58 subjects with T1DM over 194 nighttime periods. Persistent difference due to FSN CE was quantified from 585 FSN sensor insertions, yielding 1421 calibration sessions from 248 subjects with diabetes.

Results

Episodes of severe (PG ≤ 36 mg/dl) and significant (PG ≤ 45 mg/dl) hypoglycemia and significant hy-perglycemia (PG ≥ 300 mg/dl) were extracted from 18,000 simulated closed-loop nights. Severe hypoglycemia was not observed when FSN CE was less than 45%. Hypoglycemia and hyperglycemia incidence during open loop was assessed from 21 overnight studies in 17 young subjects with T1DM (8 males; 13.5 ± 3.6 years of age; body mass index 21.0 ± 4.0 kg/m2; duration diabetes 6.4 ± 4.1 years; hemoglobin A1c 8.5% ± 1.8%; mean ± standard deviation) participating in the Artificial Pancreas Project at Cambridge. Severe and significant hypoglycemia during simulated closed loop occurred 0.75 and 17.11 times per 100 person years compared to 1739 and 3479 times per 100 person years during experimental open loop, respectively. Signifi-cant hyperglycemia during closed loop and open loop occurred 75 and 15,654 times per 100 person years, respec-tively.

Conclusions

The incidence of severe and significant hypoglycemia reduced 2300- and 200-fold, respectively, during simu-lated overnight closed loop with MPC compared to that observed during open-loop overnight clinical studies in young subjects with T1DM. Hyperglycemia was 200 times less likely. Overnight closed loop with the FSN and the MPC algorithm is expected to reduce substantially the risk of hypoglycemia and hyperglycemia.     

Use of automated insulin delivery systems in people with type 1 diabetes fasting during Ramadan: An observational study

Fasting among people with type 1 diabetes imposes the risk of metabolic decompensation. Automated insulin dosing systems can allow better glycemic control without safety concerns. The utility in prolonged and repetitive fasting has not been studied. In this observational study, validated glycemic data were reviewed and analyzed from people with type 1 diabetes who observed fasting during Ramadan in 2019 and 2020 using automated insulin dosing systems. Six profiles met the inclusion criteria. The average age was 33.7 ± 4.8 years, diabetes duration was 23.5 ± 7.9 years, body mass index 23.6 ± 1.9 kg/m² and glycated hemoglobin was 6.3 ± 0.2% (45 ± 5 mmol/mol). The average glucose during Ramadan was 7.0 ± 0.5 mmol/L (126 ± 9 mg/dL), coefficient of variation 28.5%, percentage of time in range 3.9–10 mmol/L (70–180 mg/dL) 88.8 ± 7.3% and percentage time <3.9 mmol/L (<70.0 mg/dL) 2.5 ± 1.3%. The number of fasting days was 27.3 ± 3.3, and the number of days where fasting was broken due diabetes was 1 ± 1.5/participant. No significant differences in glycemic outcomes were noted between Ramadan and non‐Ramadan periods. In this first clinically validated study, automated insulin dosing systems showed a safe and effective management strategy to support prolonged and consecutive fasting in people with type 1 diabetes.     

Differences in Glycemic Variability Between Normoglycemic and Prediabetic Subjects

So far the criteria for NGT and abnormal glucose tolerance (AGT) are based on HbA1c and 75 g oGTT. We present data on GV and diurnal profiles in stratified cohorts with AGT versus controls. 28 NGT, 42 AGT (15 IGT, 11 IFG, 16 CGI) matched for age and BMI classified by 75 g oGTT underwent a CGM with test meal (TM). Diurnal profiles, glucose excursion after TM, and GV (SD, MAGE) were calculated for day 2 and 3. HbA1c, with its values of 5.5 ± 0.37% versus 5.65 ± 0.36%, was within normal range. Average interstitial glucose (AiG) was 5.84 ± 0.52 mmol/l) in NGT and 6.35 ± 0.65 mmol/l in AGT (P = .002). The 2 h incremental area under curve (iAUC) from TM until 2 h after TM was 1.94 ± 1.31 mmol/l*h versus 2.89 ( ± 1.75) mmol/l*h (P = .012), AiG 2 hours after TM was 5.99 ± 1.14 mmol/l*d versus 6.64 ± 1.30 mmol/l (P = .035). Peaks of AiG after TM were 7.69 ± 1.48 mmol/l*d versus 9.18 ± 1.67 mmol/l*d (P = .001). SD was significantly higher for AGT (1.12 ± 0.37 vs. 0.85 ± 0.32 mmol/l, P = .01) and MAGE 2.26 ± 0.84 vs. 1.60 ± 0.69 mmol/l, P = .005). In this comparative analysis NGT and AGT well matched for age, BMI, and comorbidities, CGM revealed significant differences in daytime AiG, pp glucose excursion and postprandial peaks. SD and MAGE was significantly higher for subjects with AGT. I Impaired glucose homeostasis a better characterizes degree of AGTe than HbA1c and 75 g OGTT.     

Role of Glucagon-Like Peptide-1 Analogue Versus Amylin as an Adjuvant Therapy in Type 1 Diabetes in a Closed Loop Setting With ePID Algorithm

Postprandial hyperglycemia due to paradoxical hyperglucagonemia is a major challenge of diabetes treatment despite the use of the artificial pancreas. We postulated that adjunctive therapy with pramlintide or exenatide would attenuate hyperglycemia in the postprandial phase through glucagon suppression, thereby optimizing the functioning of the closed-loop (CL) system. Subjects with type 1 diabetes (T1DM) on insulin pump therapy were recruited to participate in a 27-hour hospitalized admission on 3 occasions (2-4 weeks apart) and placed on the insulin delivery via CL system in random order to receive (1) insulin alone (control), (2) exenatide 2.5 µg + insulin, (3) pramlintide 30 µg + insulin. Medications were given prior to lunch and dinner, which was a standardized meal of 60 grams of carbohydrates. Insulin delivery was as per the ePID algorithm via the Medtronic CL system and continuous subcutaneous glucose monitoring via Medtronic Sof-sensors. Ten subjects age 23 ± 1 years with a HbA1c of 7.29 ± 0.3% (56 ± 1 mmol/mol) and duration of T1DM 10.6 ± 2.0 years participated in the 3-part study. Exenatide was found to be significantly better in attenuating postprandial hyperglycemia as compared to insulin monotherapy (P < .03) and pramlintide (P > .05). Glucagon suppression was statistically significant with exenatide (P < .03) as compared to pramlintide. Insulin requirements were lower with adjunctive therapy, but statistically insignificant. Insulin monotherapy results in postprandial hyperglycemia in T1DM in the CL setting and adjunctive therapy with exenatide reduces postprandial hyperglycemia effectively and should be considered as adjunctive therapy in T1DM.     

Artificial Pancreas Systems: Closed-Loop Artificial Pancreas Using Subcutaneous Glucose Sensing and Insulin Delivery and a Model Predictive Control Algorithm: Preliminary Studies in Padova and Montpellier

New effort has been made to develop closed-loop glucose control, using subcutaneous (SC) glucose sensing and continuous subcutaneous insulin infusion (CSII) from a pump, and a control algorithm. An approach based on a model predictive control (MPC) algorithm has been utilized during closed-loop control in type 1 diabetes patients. Here we describe the preliminary clinical experience with this approach.Six type 1 diabetes patients (three in each of two clinical investigation centers in Padova and Montpellier), using CSII, aged 36 ± 8 and 48 ± 6 years, duration of diabetes 12 ± 8 and 29 ± 4 years, hemoglobin A1c 7.4% ± 0.1% and 7.3% ± 0.3%, body mass index 23.2 ± 0.3 and 28.4 ± 2.2 kg/m², respectively, were studied on two occasions during 22 h overnight hospital admissions 2–4 weeks apart. A Freestyle Navigator® continuous glucose monitor and an OmniPod® insulin pump were applied in each trial. Admission 1 used open-loop control, while admission 2 employed closed-loop control using our MPC algorithm.In Padova, two out of three subjects showed better performance with the closed-loop system compared to open loop. Altogether, mean overnight plasma glucose (PG) levels were 134 versus 111 mg/dl during open loop versus closed loop, respectively. The percentage of time spent at PG > 140 mg/dl was 45% versus 12%, while postbreakfast mean PG was 165 versus 156 mg/dl during open loop versus closed loop, respectively. Also, in Montpellier, two patients out of three showed a better glucose control during closed-loop trials. Avoidance of nocturnal hypoglycemic excursions was a clear benefit during algorithm-guided insulin delivery in all cases.This preliminary set of studies demonstrates that closed-loop control based entirely on SC glucose sensing and insulin delivery is feasible and can be applied to improve glucose control in patients with type 1 diabetes, although the algorithm needs to be further improved to achieve better glycemic control.     

Patients with Type 1 Diabetes Treated with Insulin Pumps Need Widely Heterogeneous Basal Rate Profiles Ranging from Negligible to Pronounced Diurnal Variability

Background:Pump-treated patients with type 1 diabetes have widely differing basal insulin infusion profiles. We analyzed consequences of such heterogeneity for glycemic control under fasting conditions.Methods:Data from 339 adult patients with type 1 diabetes on insulin pump therapy undergoing a 24-hour fast (basal rate test) were retrospectively analyzed. Hourly programmed basal insulin infusion rates and plasma glucose concentrations as well as their proportions within, below, or above arbitrarily defined target ranges were assessed for specific periods of the day (eg, 1-7 hours, “dawn” period, 16-19 hours, “dusk” period, reference period 20-1 hours/10-14 hours), by tertiles of a predefined “dawn” index (mean basal insulin infusion rate during the “dawn” divided by the reference periods).Results:The “dawn” index varied interindividually from 0.7 to 4.4. Basal insulin infusion profiles exhibited substantial differences (P = .011), especially overnight. Despite higher insulin infusion rates at 4 and 6.45 hours, patients with the most pronounced “dawn” phenomenon exhibited higher plasma glucose concentrations at those time points (P < .012). Patients with a marked “dawn” phenomenon exhibited a lower probability for low (<4.4 mmol/L) and a higher probability of high values (>7.2 mmol/L) during the dawn period (all P values <.01).Conclusions:We observe substantial interindividual heterogeneity in the “dawn” phenomenon. However, widely different empirically derived basal insulin infusion profiles appear appropriate for individual patients, as indicated by similar plasma glucose concentrations, mainly in the target range, during a 24-hour fasting period.     

Effect of Insulin Feedback on Closed-Loop Glucose Control: A Crossover Study

Background

Closed-loop (CL) insulin delivery systems utilizing proportional-integral-derivative (PID) controllers have demonstrated susceptibility to late postprandial hypoglycemia because of delays between insulin delivery and blood glucose (BG) response. An insulin feedback (IFB) modification to the PID algorithm has been introduced to mitigate this risk. We examined the effect of IFB on CL BG control.

Methods

Using the Medtronic ePID CL system, four subjects were studied for 24 h on PID control and 24 h during a separate admission with the IFB modification (PID + IFB). Target glucose was 120 mg/dl; meals were served at 8:00 AM, 1:00 PM, and 6:00 PM and were identical for both admissions. No premeal manual boluses were given. Reference BG excursions, defined as incremental glucose rise from premeal to peak, and postprandial BG area under the curve (AUC; 0–5 h) were compared. Results are reported as mean ± standard deviation.

Results

The PID + IFB control resulted in higher mean BG levels compared with PID alone (153 ± 54 versus 133 ± 56 mg/dl; p < .0001). Postmeal BG excursions (114 ± 28 versus 114 ± 47 mg/dl) and AUCs (285 ± 102 versus 255 ± 129 mg/dl/h) were similar under both conditions. Total insulin delivery averaged 57 ± 20 U with PID versus 45 ± 13 U with PID + IFB (p = .18). Notably, eight hypoglycemic events (BG < 60 mg/dl) occurred during PID control versus none during PID + IFB.

Conclusions

Addition of IFB to the PID controller markedly reduced the occurrence of hypoglycemia without increasing meal-related glucose excursions. Higher average BG levels may be attributable to differences in the determination of system gain (Kp) in this study. The prevention of postprandial hypoglycemia suggests that the PID + IFB algorithm may allow for lower target glucose selection and improved overall glycemic control.     

Meta-analysis of overnight closed-loop randomized studies in children and adults with type 1 diabetes: the Cambridge cohort

Aim

We reviewed the safety and efficacy of overnight closed-loop insulin delivery compared with conventional continuous subcutaneous insulin infusion (CSII) in two distinct age groups with type 1 diabetes mellitus (T1DM), young people aged 5 to 18 years and adults, combining data of previously published randomized studies.

Methods

We evaluated four randomized crossover studies in 17 children and adolescents [13.4 ± 3.6 years; mean ± standard deviation (SD)] and 24 adults (37.5 ± 9.1 years) on 45 closed-loop (intervention) and 45 CSII (control) visits. Each subject attended for two overnight study visits, using either closed-loop or conventional pump therapy, in random order. In each age group, studies were designed to mimic realistic likely scenarios. In the children and adolescent studies, closed loop was used following a standard evening meal and following 40 min of moderate-intensity exercise. In the adult studies, closed loop was commenced following a 60 g carbohydrate meal or a 100 g carbohydrate meal accompanied by alcohol. The primary outcome measure was time for which plasma glucose was within target range (3.91–8.0 mmol/liter).

Results

Overnight closed loop increased the time in target plasma glucose in both young (from 40% to 60%, p = .002) and adults (from 50% to 76%, p < .001) compared with conventional CSII. Combined analysis showed an increase from 43% to 71% with closed loop (p < .001). Additionally, closed loop reduced the time spent below 3.91 mmol/liter and above 8.0 mmol/liter, from 4.1% to 2.1% (p = .01) and 33% to 20% (p = .03), respectively. Glycemic variability, as measured by the SD of plasma glucose, was lower during closed loop compared with CSII (1.5 versus 2.1 mmol/liter, p = .007).

Conclusions

Overnight closed loop may improve glycemic control and reduce nocturnal hypoglycemia in both young people and adults with T1DM.     

Time Lag of Glucose From Intravascular to Interstitial Compartment in Type 1 Diabetes

Method:Four microdialysis catheters were inserted into the abdominal subcutaneous space in 6 T1D subjects under overnight fasted conditions. Plasma glucose was maintained at 113.7 ± 6.3 mg/dl using a continuous intravenous insulin infusion. After sequential intravenous bolus administrations of glucose isotopes, timed plasma and interstitial fluid samples were collected chronologically and analyzed for tracer enrichments.Results:We observed a median (range) time lag of tracer appearance (time to detection) into the interstitial space after intravenous bolus of 6.8 (4.8-9.8) minutes, with all participants having detectable values by 9.8 minutes.Conclusions:We conclude that in the overnight fasted state in T1D adults, the delay of glucose appearance from the vascular to the interstitial space is less than 10 minutes, thereby implying that this minimal physiological time lag should not be a major impediment to the development of an effective closed-loop control system for T1D.     

Development of a Smartphone Application to Capture Carbohydrate,Lipid, and Protein Contents of Daily Food: Need for Integration in Artificial Pancreas for Patients With Type 1 Diabetes?

Background:Meal lipids (LIP) and proteins (PRO) may influence the effect of insulin doses based on carbohydrate (CHO) counting in patients with type 1 diabetes (T1D). We developed a smartphone application for CHO, LIP, and PRO counting in daily food and assessed its usability in real-life conditions and potential usefulness.Methods:Ten T1D patients used the android application for 1 week to collect their food intakes. Data included meal composition, premeal and 2-hour postmeal blood glucose, corrections for hypo- or hyperglycemia after meals, and time for entering meals in the application. Meal insulin doses were based on patients’ CHO counting (application in blinded mode). Linear mixed models were used to assess the statistical differences.Results:In all, 187 meals were analyzed. Average computed CHO amount was 74.37 ± 31.78 grams; LIP amount: 20.26 ± 14.28 grams and PRO amount: 25.68 ± 16.68 grams. Average CHO, LIP, and PRO contents were significantly different between breakfast and lunch/dinner. The average time for meal entry in the application moved from 3-4 minutes to 2.5 minutes during the week. No significant impact of LIP and PRO was found on available blood glucose values.Conclusion:Our study shows CHO, LIP, and PRO intakes can be easily captured by an application on smartphone for meal entry used by T1D patients. Although LIP and PRO meal contents did not influence glucose levels when insulin doses were based on CHO in this pilot study, this application could be used for further investigation of this topic, including in closed-loop conditions.     

Feasibility Study of Automated Overnight Closed-Loop Glucose Control Under MD-Logic Artificial Pancreas in Patients with Type 1 Diabetes: The DREAM Project

Abstract Background: Artificial pancreas systems may offer a potential major impact on the normalization of metabolic control and preventing hypoglycemic events. This study aims to establish near-normal overnight glucose control and reduce the risk of nocturnal hypoglycemia using the MD-Logic Artificial Pancreas (MDLAP), an algorithm that was developed by our research group. This inpatient feasibility study is the first step towards implementing an overnight closed-loop MDLAP system at the patient's home. Subjects and Methods: Seven patients with type 1 diabetes (three adolescents and four adults; mean±SD age, 20.6±4.7 years; duration of diabetes, 9.6±2.6 years; body mass index, 24.3±3.9 kg/m(2); and glycated hemoglobin, 7.8±0.8%) participated in a total of 14 closed-loop overnight sessions. Each participant underwent two closed-loop inpatient sessions starting at dinner alone and at dinner following exercise. The closed-loop inpatient sessions were compared with data derived from nights spent at home with an open-loop system in a similar scenario to the study protocol. Results: The mean percentage of time spent in the near normal glucose range of 63-140?mg/dL was 83±16%, and the median (interquartile range) was 85% (78-92%) for the overnight closed-loop sessions compared with 34±31% and 27% (6-57%) in the homecare open-loop setting, respectively. During the overnight closed-loop sessions at dinner alone 92±9% of the sensor values ranged within target range, compared with 73±19% for the sessions following exercise (P=0.03). No hypoglycemic (<63?mg/dL) events occurred during the closed-loop sessions. Conclusion: Closed-loop insulin delivery under MDLAP is a feasible and safe solution to control overnight glycemia.