Roberto Visentin

Feasibility of Outpatient Fully Integrated Closed-Loop Control First studies of wearable artificial pancreas

OBJECTIVE To evaluate the feasibility of a wearable artificial pancreas system, the Diabetes Assistant (DiAs), which uses a smart phone as a closed-loop control platform. RESEARCH DESIGN AND METHODS Twenty patients with type 1 diabetes were enrolled at the Universities of Padova, Montpellier, and Virginia and at Sansum Diabetes Research Institute. Each trial continued for 42 h. The United States studies were conducted entirely in outpatient setting (e.g., hotel or guest house); studies in Italy and France were hybrid hospital–hotel admissions. A continuous glucose monitoring/pump system (Dexcom Seven Plus/Omnipod) was placed on the subject and was connected to DiAs. The patient operated the system via the DiAs user interface in open-loop mode (first 14 h of study), switching to closed-loop for the remaining 28 h. Study personnel monitored remotely via 3G or WiFi connection to DiAs and were available on site for assistance. RESULTS The total duration of proper system communication functioning was 807.5 h (274 h in open-loop and 533.5 h in closed-loop), which represented 97.7% of the total possible time from admission to discharge. This exceeded the predetermined primary end point of 80% system functionality. CONCLUSIONS This study demonstrated that a contemporary smart phone is capable of running outpatient closed-loop control and introduced a prototype system (DiAs) for further investigation. Following this proof of concept, future steps should include equipping insulin pumps and sensors with wireless capabilities, as well as studies focusing on control efficacy and patient-oriented clinical outcomes.

2 month evening and night closed-loop glucose control in patients with type 1 diabetes under free-living conditions: a randomised crossover trial

BACKGROUND An artificial pancreas (AP) that can be worn at home from dinner to waking up in the morning might be safe and efficient for first routine use in patients with type 1 diabetes. We assessed the effect on glucose control with use of an AP during the evening and night plus patient-managed sensor-augmented pump therapy (SAP) during the day, versus 24 h use of patient-managed SAP only, in free-living conditions. METHODS In a crossover study done in medical centres in France, Italy, and the Netherlands, patients aged 18-69 years with type 1 diabetes who used insulin pumps for continuous subcutaneous insulin infusion were randomly assigned to 2 months of AP use from dinner to waking up plus SAP use during the day versus 2 months of SAP use only under free-living conditions. Randomisation was achieved with a computer-generated allocation sequence with random block sizes of two, four, or six, masked to the investigator. Patients and investigators were not masked to the type of intervention. The AP consisted of a continuous glucose monitor (CGM) and insulin pump connected to a modified smartphone with a model predictive control algorithm. The primary endpoint was the percentage of time spent in the target glucose concentration range (3·9-10·0 mmol/L) from 2000 to 0800 h. CGM data for weeks 3-8 of the interventions were analysed on a modified intention-to-treat basis including patients who completed at least 6 weeks of each intervention period. The 2 month study period also allowed us to asses HbA1c as one of the secondary outcomes. This trial is registered with ClinicalTrials.gov, number NCT02153190. FINDINGS During 2000-0800 h, the mean time spent in the target range was higher with AP than with SAP use: 66·7% versus 58·1% (paired difference 8·6% [95% CI 5·8 to 11·4], p<0·0001), through a reduction in both mean time spent in hyperglycaemia (glucose concentration >10·0 mmol/L; 31·6% vs 38·5%; -6·9% [-9·8% to -3·9], p<0·0001) and in hypoglycaemia (glucose concentration <3·9 mmol/L; 1·7% vs 3·0%; -1·6% [-2·3 to -1·0], p<0·0001). Decrease in mean HbA1c during the AP period was significantly greater than during the control period (-0·3% vs -0·2%; paired difference -0·2 [95% CI -0·4 to -0·0], p=0·047), taking a period effect into account (p=0·0034). No serious adverse events occurred during this study, and none of the mild-to-moderate adverse events was related to the study intervention. INTERPRETATION Our results support the use of AP at home as a safe and beneficial option for patients with type 1 diabetes. The HbA1c results are encouraging but preliminary. FUNDING European Commission.

First Use of Model Predictive Control in Outpatient Wearable Artificial Pancreas

OBJECTIVE Inpatient studies suggest that model predictive control (MPC) is one of the most promising algorithms for artificial pancreas (AP). So far, outpatient trials have used hypo/hyperglycemia-mitigation or medical-expert systems. In this study, we report the first wearable AP outpatient study based on MPC and investigate specifically its ability to control postprandial glucose, one of the major challenges in glucose control. RESEARCH DESIGN AND METHODS A new modular MPC algorithm has been designed focusing on meal control. Six type 1 diabetes mellitus patients underwent 42-h experiments: sensor-augmented pump therapy in the first 14 h (open-loop) and closed-loop in the remaining 28 h. RESULTS MPC showed satisfactory dinner control versus open-loop: time-in-target (70–180 mg/dL) 94.83 vs. 68.2% and time-in-hypo 1.25 vs. 11.9%. Overnight control was also satisfactory: time-in-target 89.4 vs. 85.0% and time-in-hypo: 0.00 vs. 8.19%. CONCLUSIONS This outpatient study confirms inpatient evidence of suitability of MPC-based strategies for AP. These encouraging results pave the way to randomized crossover outpatient studies.

Multicenter outpatient dinner/overnight reduction of hypoglycemia and increased time of glucose in target with a wearable artificial pancreas using modular model predictive control in adults with type 1 diabetes.

To test in an outpatient setting the safety and efficacy of continuous subcutaneous insulin infusion (CSII) driven by a modular model predictive control (MMPC) algorithm informed by continuous glucose monitoring (CGM) measurement.

Day and Night Closed-Loop Glucose Control in Patients With Type 1 Diabetes Under Free-Living Conditions: Results of a Single-Arm 1-Month Experience Compared With a Previously Reported Feasibility Study of Evening and Night at Home

OBJECTIVE After testing of a wearable artificial pancreas (AP) during evening and night (E/N-AP) under free-living conditions in patients with type 1 diabetes (T1D), we investigated AP during day and night (D/N-AP) for 1 month. RESEARCH DESIGN AND METHODS Twenty adult patients with T1D who completed a previous randomized crossover study comparing 2-month E/N-AP versus 2-month sensor augmented pump (SAP) volunteered for 1-month D/N-AP nonrandomized extension. AP was executed by a model predictive control algorithm run by a modified smartphone wirelessly connected to a continuous glucose monitor (CGM) and insulin pump. CGM data were analyzed by intention-to-treat with percentage time-in-target (3.9–10 mmol/L) over 24 h as the primary end point. RESULTS Time-in-target (mean ± SD, %) was similar over 24 h with D/N-AP versus E/N-AP: 64.7 ± 7.6 vs. 63.6 ± 9.9 (P = 0.79), and both were higher than with SAP: 59.7 ± 9.6 (P = 0.01 and P = 0.06, respectively). Time below 3.9 mmol/L was similarly and significantly reduced by D/N-AP and E/N-AP versus SAP (both P < 0.001). SD of blood glucose concentration (mmol/L) was lower with D/N-AP versus E/N-AP during whole daytime: 3.2 ± 0.6 vs. 3.4 ± 0.7 (P = 0.003), morning: 2.7 ± 0.5 vs. 3.1 ± 0.5 (P = 0.02), and afternoon: 3.3 ± 0.6 vs. 3.5 ± 0.8 (P = 0.07), and was lower with D/N-AP versus SAP over 24 h: 3.1 ± 0.5 vs. 3.3 ± 0.6 (P = 0.049). Insulin delivery (IU) over 24 h was higher with D/N-AP and SAP than with E/N-AP: 40.6 ± 15.5 and 42.3 ± 15.5 vs. 36.6 ± 11.6 (P = 0.03 and P = 0.0004, respectively). CONCLUSIONS D/N-AP and E/N-AP both achieved better glucose control than SAP under free-living conditions. Although time in the different glycemic ranges was similar between D/N-AP and E/N-AP, D/N-AP further reduces glucose variability.

Randomized summer camp crossover trial in 5-to 9-year-old children: Outpatient wearable artificial pancreas is feasible and safe

OBJECTIVE The Pediatric Artificial Pancreas (PedArPan) project tested a children-specific version of the modular model predictive control (MMPC) algorithm in 5- to 9-year-old children during a camp. RESEARCH DESIGN AND METHODS A total of 30 children, 5- to 9-years old, with type 1 diabetes completed an outpatient, open-label, randomized, crossover trial. Three days with an artificial pancreas (AP) were compared with three days of parent-managed sensor-augmented pump (SAP). RESULTS Overnight time-in-hypoglycemia was reduced with the AP versus SAP, median (25th–75th percentiles): 0.0% (0.0–2.2) vs. 2.2% (0.0–12.3) (P = 0.002), without a significant change of time-in-target, mean: 56.0% (SD 22.5) vs. 59.7% (21.2) (P = 0.430), but with increased mean glucose 173 mg/dL (36) vs. 150 mg/dL (39) (P = 0.002). Overall, the AP granted a threefold reduction of time-in-hypoglycemia (P < 0.001) at the cost of decreased time-in-target, 56.8% (13.5) vs. 63.1% (11.0) (P = 0.022) and increased mean glucose 169 mg/dL (23) vs. 147 mg/dL (23) (P < 0.001). CONCLUSIONS This trial, the first outpatient single-hormone AP trial in a population of this age, shows feasibility and safety of MMPC in young children. Algorithm retuning will be performed to improve efficacy.

One-Day Bayesian Cloning of Type 1 Diabetes Subjects: Toward a Single-Day UVA/Padova Type 1 Diabetes Simulator

Objective: The UVA/Padova Type 1 Diabetes (T1DM) Simulator has been shown to be representative of a T1DM population observed in a clinical trial, but has not yet been identified on T1DM data. Moreover, the current version of the simulator is “single meal” while making it “single-day centric,” i.e., by describing intraday variability, would be a step forward to create more realistic in silico scenarios. Here, we propose a Bayesian method for the identification of the model from plasma glucose and insulin concentrations only, by exploiting the prior model parameter distribution. Methods: The database consists of 47 T1DM subjects, who received dinner, breakfast, and lunch (respectively, 80, 50, and 60 CHO grams) in three 23-h occasions (one openand one closed-loop). The model is identified using the Bayesian Maximum a Posteriori technique, where the prior parameter distribution is that of the simulator. Diurnal variability of glucose absorption and insulin sensitivity is allowed. Results: The model well describes glucose traces (coefficient of determination R2 = 0.962 ± 0.027) and the posterior parameter distribution is similar to that included in the simulator. Absorption parameters at breakfast are significantly different from those at lunch and dinner, reflecting more rapid dynamics of glucose absorption. Insulin sensitivity varies in each individual but without a specific pattern. Conclusion: The incorporation of glucose absorption and insulin sensitivity diurnal variability into the simulator makes it more realistic. Significance: The proposed method, applied to the increasing number of longterm artificial pancreas studies, will allow to describe week/month variability, thus further refining the simulator.

Evaluating the Experience of Children With Type 1 Diabetes and Their Parents Taking Part in an Artificial Pancreas Clinical Trial Over Multiple Days in a Diabetes Camp Setting

OBJECTIVE To explore the experiences of children with type 1 diabetes and their parents taking part in an artificial pancreas (AP) clinical trial during a 7-day summer camp. RESEARCH DESIGN AND METHODS A semistructured interview, composed of 14 questions based on the Technology Acceptance Model, was conducted at the end of the clinical trial. Participants also completed the Diabetes Treatment Satisfaction Questionnaire (DTSQ, parent version) and the AP Acceptance Questionnaire. RESULTS Thirty children, aged 5–9 years, and their parents completed the study. A content analysis of the interviews showed that parents were focused on understanding the mechanisms, risks, and benefits of the new device, whereas the children were focused on the novelty of the new system. The parents’ main concerns about adopting the new system seemed related to the quality of glucose control. The mean scores of DTSQ subscales indicated general parents’ satisfaction (44.24 ± 5.99, range 32–53) and trustful views of diabetes control provided by the new system (7.8 ± 2.2, range 3–12). The AP Acceptance Questionnaire revealed that most parents considered the AP easy to use (70.5%), intended to use it long term (94.0%), and felt that it was apt to improve glucose control (67.0%). CONCLUSIONS Participants manifested a positive attitude toward the AP. Further studies are required to explore participants’ perceptions early in the AP development to individualize the new treatment as much as possible, and to tailor it to respond to their needs and values.

Accuracy of a CGM Sensor in Pediatric Subjects With Type 1 Diabetes. Comparison of Three Insertion Sites: Arm, Abdomen, and Gluteus:

Background: Patients with diabetes, especially pediatric ones, sometimes use continuous glucose monitoring (CGM) sensor in different positions from the approved ones. Here we compare the accuracy of Dexcom® G5 CGM sensor in three different sites: abdomen, gluteus (both approved) and arm (off-label). Method: Thirty youths, 5-9 years old, with type 1 diabetes (T1D) wore the sensor during a clinical trial where frequent self-monitoring of blood glucose (SMBG) measurements were obtained. Sensor was inserted in different sites according to the patient habit. Accuracy metrics include absolute relative difference (ARD) and absolute difference (AD) of CGM with respect to SMBG. The three sites were compared with ANOVA. If the test detected a difference, an additional pair-wise comparison was performed. Results: Overall, no accuracy difference was detected: the mean ARD was 13.3% (SD = 13.5%) for abdomen, 13.4% (12.9%) for arm and 12.9% (20.2%) for gluteus (P value = .83); the mean AD was 17.0 mg/dl (17.2 mg/dl) for abdomen, 17.2 mg/dl (17.1 mg/dl) for arm and 18.3 mg/dl (18.5 mg/dl) for gluteus (P value = .30). In hypo- and euglycemia ARD (P value = .87 and .15, respectively), and AD (P value = .68 and .37, respectively) were not statistically different. At variance, in hyperglycemia, a significant difference was detected between the two approved sites, abdomen and gluteus (ΔARD = −2.2% [CI = −4.2%, −0.1%], P value = .04), whereas the comparisons with the off-label location, arm-abdomen, and arm-gluteus were not significant. Conclusions: These results suggest that the accuracy of the sensor placed on the arm was not significantly different with respect to the two approved insertion sites (abdomen and gluteus). Larger, randomized trials are needed to draw final conclusions.

Randomized Controlled Trial of a MUFA or Fiber-Rich Diet on Hepatic Fat in Prediabetes

Context Increased prevalence of type 2 diabetes mellitus and prediabetes worldwide is attributed in part to an unhealthy diet. Objective To evaluate whether 12 weeks of high monounsaturated fatty acid (MUFA) or fiber-rich weight-maintenance diet lowers hepatic fat and improves glucose tolerance in people with prediabetes. Design Subjects underwent a [6, 6-2H2]-labeled 75-g oral glucose tolerance test to estimate hepatic insulin sensitivity and liver fat fraction (LFF) using magnetic resonance spectroscopy before and after intervention. Setting Mayo Clinic Clinical Research Trials Unit. Participants 43 subjects with prediabetes. Intervention Subjects were randomized into three isocaloric weight-maintaining diets containing MUFA (olive oil), extra fiber, and standard US food (control-habitual diet). Outcome Measures LFF, glucose tolerance, and indices of insulin action and secretion. Results Body weight was maintained constant in all groups during the intervention. Glucose and hormonal concentrations were similar in all groups before, and unchanged after, 12 weeks of intervention. LFF was significantly lower after intervention in the MUFA group (P < 0.0003) but remained unchanged in the fiber (P = 0.25) and control groups (P = 0.45). After 12 weeks, LFF was significantly lower in the MUFA than in the control group (P = 0.01), but fiber and control groups did not differ (P = 0.41). Indices of insulin action and secretion were not significantly different between the MUFA and control groups after intervention (P ≥ 0.11), but within-group comparison showed higher hepatic (P = 0.01) and total insulin sensitivity (P < 0.04) with MUFA. Conclusions Twelve weeks of a MUFA diet decreases hepatic fat and improves both hepatic and total insulin sensitivity.