John Lum

A Randomized Trial of a Home System to Reduce Nocturnal Hypoglycemia in Type 1 Diabetes

OBJECTIVE Overnight hypoglycemia occurs frequently in individuals with type 1 diabetes and can result in loss of consciousness, seizure, or even death. We conducted an in-home randomized trial to determine whether nocturnal hypoglycemia could be safely reduced by temporarily suspending pump insulin delivery when hypoglycemia was predicted by an algorithm based on continuous glucose monitoring (CGM) glucose levels. RESEARCH DESIGN AND METHODS Following an initial run-in phase, a 42-night trial was conducted in 45 individuals aged 15–45 years with type 1 diabetes in which each night was assigned randomly to either having the predictive low-glucose suspend system active (intervention night) or inactive (control night). The primary outcome was the proportion of nights in which ≥1 CGM glucose values ≤60 mg/dL occurred. RESULTS Overnight hypoglycemia with at least one CGM value ≤60 mg/dL occurred on 196 of 942 (21%) intervention nights versus 322 of 970 (33%) control nights (odds ratio 0.52 [95% CI 0.43–0.64]; P < 0.001). Median hypoglycemia area under the curve was reduced by 81%, and hypoglycemia lasting >2 h was reduced by 74%. Overnight sensor glucose was >180 mg/dL during 57% of control nights and 59% of intervention nights (P = 0.17), while morning blood glucose was >180 mg/dL following 21% and 27% of nights, respectively (P < 0.001), and >250 mg/dL following 6% and 6%, respectively. Morning ketosis was present <1% of the time in each arm. CONCLUSIONS Use of a nocturnal low-glucose suspend system can substantially reduce overnight hypoglycemia without an increase in morning ketosis.

In silico preclinical trials: methodology and engineering guide to closed-loop control in type 1 diabetes mellitus.

This article sets forth guidelines for in silico (simulation-based) proof-of-concept testing of artificial pancreas control algorithms. The goal was to design a test procedure that can facilitate regulatory approval [e.g., Food and Drug Administration Investigational Device Exemption] for General Clinical Research Center experiments without preliminary testing on animals. The methodology is designed around a software package, based on a recent meal simulation model of the glucose-insulin system. Putting a premium on generality, this document starts by specifying a generic, rather abstract, meta-algorithm for control. The meta-algorithm has two main components: (1) patient assessment and tuning of control parameters, i.e., algorithmic processes for collection and processing patient data prior to closed-loop operation, and (2) controller warm-up and run-time operation, i.e., algorithmic processes for initializing controller states and managing blood glucose. The simulation-based testing methodology is designed to reveal the conceptual/mathematical operation of both main components, as applied to a large population of in silico patients with type 1 diabetes mellitus.

Outpatient Safety Assessment of an In-Home Predictive Low-Glucose Suspend System with Type 1 Diabetes Subjects at Elevated Risk of Nocturnal Hypoglycemia

OBJECTIVE Nocturnal hypoglycemia is a common problem with type 1 diabetes. In the home setting, we conducted a pilot study to evaluate the safety of a system consisting of an insulin pump and continuous glucose monitor communicating wirelessly with a bedside computer running an algorithm that temporarily suspends insulin delivery when hypoglycemia is predicted. RESEARCH DESIGN AND METHODS After the run-in phase, a 21-night randomized trial was conducted in which each night was randomly assigned 2:1 to have either the predictive low-glucose suspend (PLGS) system active (intervention night) or inactive (control night). Three predictive algorithm versions were studied sequentially during the study for a total of 252 intervention and 123 control nights. The trial included 19 participants 18-56 years old with type 1 diabetes (hemoglobin A1c level of 6.0-7.7%) who were current users of the MiniMed Paradigm® REAL-Time Revel™ System and Sof-sensor® glucose sensor (Medtronic Diabetes, Northridge, CA). RESULTS With the final algorithm, pump suspension occurred on 53% of 77 intervention nights. Mean morning glucose level was 144±48 mg/dL on the 77 intervention nights versus 133±57 mg/dL on the 37 control nights, with morning blood ketones >0.6 mmol/L following one intervention night. Overnight hypoglycemia was lower on intervention than control nights, with at least one value ≤70 mg/dL occurring on 16% versus 30% of nights, respectively, with the final algorithm. CONCLUSIONS This study demonstrated that the PLGS system in the home setting is safe and feasible. The preliminary efficacy data appear promising with the final algorithm reducing nocturnal hypoglycemia by almost 50%.

Outcome measures for artificial pancreas clinical trials: A consensus report

Research on and commercial development of the artificial pancreas (AP) continue to progress rapidly, and the AP promises to become a part of clinical care. In this report, members of the JDRF Artificial Pancreas Project Consortium in collaboration with the wider AP community 1) advocate for the use of continuous glucose monitoring glucose metrics as outcome measures in AP trials, in addition to HbA1c, and 2) identify a short set of basic, easily interpreted outcome measures to be reported in AP studies whenever feasible. Consensus on a broader range of measures remains challenging; therefore, reporting of additional metrics is encouraged as appropriate for individual AP studies or study groups. Greater consistency in reporting of basic outcome measures may facilitate the interpretation of study results by investigators, regulatory bodies, health care providers, payers, and patients themselves, thereby accelerating the widespread adoption of AP technology to improve the lives of people with type 1 diabetes.

Predictive Low-Glucose Insulin Suspension Reduces Duration of Nocturnal Hypoglycemia in Children Without Increasing Ketosis

OBJECTIVE Nocturnal hypoglycemia can cause seizures and is a major impediment to tight glycemic control, especially in young children with type 1 diabetes. We conducted an in-home randomized trial to assess the efficacy and safety of a continuous glucose monitor–based overnight predictive low-glucose suspend (PLGS) system. RESEARCH DESIGN AND METHODS In two age-groups of children with type 1 diabetes (11–14 and 4–10 years of age), a 42-night trial for each child was conducted wherein each night was assigned randomly to either having the PLGS system active (intervention night) or inactive (control night). The primary outcome was percent time <70 mg/dL overnight. RESULTS Median time at <70 mg/dL was reduced by 54% from 10.1% on control nights to 4.6% on intervention nights (P < 0.001) in 11–14-year-olds (n = 45) and by 50% from 6.2% to 3.1% (P < 0.001) in 4–10-year-olds (n = 36). Mean overnight glucose was lower on control versus intervention nights in both age-groups (144 ± 18 vs. 152 ± 19 mg/dL [P < 0.001] and 153 ± 14 vs. 160 ± 16 mg/dL [P = 0.004], respectively). Mean morning blood glucose was 159 ± 29 vs. 176 ± 28 mg/dL (P < 0.001) in the 11–14-year-olds and 154 ± 25 vs. 158 ± 22 mg/dL (P = 0.11) in the 4–10-year-olds, respectively. No differences were found between intervention and control in either age-group in morning blood ketosis. CONCLUSIONS In 4–14-year-olds, use of a nocturnal PLGS system can substantially reduce overnight hypoglycemia without an increase in morning ketosis, although overnight mean glucose is slightly higher.

Multinational Home Use of Closed-Loop Control Is Safe and Effective

OBJECTIVE To evaluate the efficacy of a portable, wearable, wireless artificial pancreas system (the Diabetes Assistant [DiAs] running the Unified Safety System) on glucose control at home in overnight-only and 24/7 closed-loop control (CLC) modes in patients with type 1 diabetes. RESEARCH DESIGN AND METHODS At six clinical centers in four countries, 30 participants 18–66 years old with type 1 diabetes (43% female, 96% non-Hispanic white, median type 1 diabetes duration 19 years, median A1C 7.3%) completed the study. The protocol included a 2-week baseline sensor-augmented pump (SAP) period followed by 2 weeks of overnight-only CLC and 2 weeks of 24/7 CLC at home. Glucose control during CLC was compared with the baseline SAP. RESULTS Glycemic control parameters for overnight-only CLC were improved during the nighttime period compared with baseline for hypoglycemia (time <70 mg/dL, primary end point median 1.1% vs. 3.0%; P < 0.001), time in target (70–180 mg/dL: 75% vs. 61%; P < 0.001), and glucose variability (coefficient of variation: 30% vs. 36%; P < 0.001). Similar improvements for day/night combined were observed with 24/7 CLC compared with baseline: 1.7% vs. 4.1%, P < 0.001; 73% vs. 65%, P < 0.001; and 34% vs. 38%, P < 0.001, respectively. CONCLUSIONS CLC running on a smartphone (DiAs) in the home environment was safe and effective. Overnight-only CLC reduced hypoglycemia and increased time in range overnight and increased time in range during the day; 24/7 CLC reduced hypoglycemia and increased time in range both overnight and during the day. Compared with overnight-only CLC, 24/7 CLC provided additional hypoglycemia protection during the day.

Inpatient studies of a Kalman-filter-based predictive pump shutoff algorithm.

Background: An insulin pump shutoff system can prevent nocturnal hypoglycemia and is a first step on the pathway toward a closed-loop artificial pancreas. In previous pump shutoff studies using a voting algorithm and a 1 min continuous glucose monitor (CGM), 80% of induced hypoglycemic events were prevented. Methods: The pump shutoff algorithm used in previous studies was revised to a single Kalman filter to reduce complexity, incorporate CGMs with different sample times, handle sensor signal dropouts, and enforce safety constraints on the allowable pump shutoff time. Results: Retrospective testing of the new algorithm on previous clinical data sets indicated that, for the four cases where the previous algorithm failed (minimum reference glucose less than 60 mg/dl), the mean suspension start time was 30 min earlier than the previous algorithm. Inpatient studies of the new algorithm have been conducted on 16 subjects. The algorithm prevented hypoglycemia in 73% of subjects. Suspension-induced hyperglycemia is not assessed, because this study forced excessive basal insulin infusion rates. Conclusions: The new algorithm functioned well and is flexible enough to handle variable sensor sample times and sensor dropouts. It also provides a framework for handling sensor signal attenuations, which can be challenging, particularly when they occur overnight.

Multicenter closed-loop/hybrid meal bolus insulin delivery with type 1 diabetes.

BACKGROUND This study evaluated meal bolus insulin delivery strategies and associated postprandial glucose control while using an artificial pancreas (AP) system. SUBJECTS AND METHODS This study was a multicenter trial in 53 patients, 12-65 years of age, with type 1 diabetes for at least 1 year and use of continuous subcutaneous insulin infusion for at least 6 months. Four different insulin bolus strategies were assessed: standard bolus delivered with meal (n=51), standard bolus delivered 15 min prior to meal (n=40), over-bolus of 30% delivered with meal (n=40), and bolus purposely omitted (n=46). Meal carbohydrate (CHO) intake was 1 g of CHO/kg of body weight up to a maximum of 100 g for the first three strategies or up to a maximum of 50 g for strategy 4. RESULTS Only three of 177 meals (two with over-bolus and one with standard bolus 15 min prior to meal) had postprandial blood glucose values of <60 mg/dL. Postprandial hyperglycemia (blood glucose level >180 mg/dL) was prolonged for all four bolus strategies but was shorter for the over-bolus (41% of the 4-h period) than the two standard bolus strategies (73% for each). Mean postprandial blood glucose level was 15.9 mg/dL higher for the standard bolus with meal compared with the prebolus (baseline-adjusted, P=0.07 for treatment effect over the 4-h period). CONCLUSIONS The AP handled the four bolus situations safely, but at the expense of having elevated postprandial glucose levels in most subjects. This was most likely secondary to suboptimal performance of the algorithm.

Performance Comparison of the Medtronic Sof-Sensor and Enlite Glucose Sensors in Inpatient Studies of Individuals with Type 1 Diabetes

OBJECTIVE Knowledge of the accuracy of continuous glucose monitoring (CGM) devices is important for its use as a management tool for individuals with diabetes and for its use to assess outcomes in clinical studies. Using data from several inpatient studies, we compared the accuracy of two sensors, the Medtronic Enlite™ using MiniMed Paradigm(®) Veo™ calibration and the Sof-Sensor(®) glucose sensor using Guardian(®) REAL-Time CGM calibration (all from Medtronic Diabetes, Northridge, CA). SUBJECTS AND METHODS Nocturnal data were analyzed from eight inpatient studies in which both CGM and reference glucose measurements were available. The analyses included 1,666 CGM-reference paired glucose values for the Enlite in 54 participants over 69 nights and 3,627 paired values for the Sof-Sensor in 66 participants over 91 nights. RESULTS The Enlite sensor tended to report glucose levels lower than the reference over the entire range of glucose values, whereas the Sof-Sensor values tended to be higher than reference values in the hypoglycemic range and lower than reference values in the hyperglycemic range. The overall median sensor-reference difference was -15 mg/dL for the Enlite and -1 mg/dL for the Sof-Sensor (P<0.001). The median relative absolute difference was 15% for the Enlite versus 12% for the Sof-Sensor (P=0.06); 66% of Enlite values and 73% of Sof-Sensor values met International Organization for Standardization criteria. CONCLUSIONS We found that the Enlite tended to be biased low over the entire glucose range, whereas the Sof-Sensor showed the more typical sensor pattern of being biased high in the hypoglycemic range and biased low in the hyperglycemic range.

Juvenile Diabetes Research Foundation Artificial Pancreas Consortium Update

A mechanical means to restore euglycemica in diabetes has long been considered achievable, yet a portable and widely adopted artificial pancreas system has not been realized.1,2 The Artificial Pancreas Consortium was established in 2006 as part of the Juvenile Diabetes Research Foundation International (JDRF) Artificial Pancreas Project, a multimillion dollar, multiyear initiative with a mission to accelerate the development of systems for automated control of blood glucose in patients with diabetes. Consortium investigators seek to research and develop strategies, which can be commercialized, that will confer the long-term benefits of improved glycemic control by combining novel automated control algorithms and hormone therapies with continuous glucose monitors and pump devices.