Improved Satisfaction While Maintaining Safety and High Time in Range (TIR) With a Medtronic Investigational Enhanced Advanced Hybrid Closed-Loop (e-AHCL) System.

OBJECTIVE: To determine feasibility and compare acceptance of an investigational Medtronic enhanced advanced hybrid closed-loop (e-AHCL) system in adults with type 1 diabetes with earlier iterations. RESEARCH DESIGN AND METHODS: This nonrandomized three-stage (12 weeks each) exploratory study compared e-AHCL (Bluetooth-enabled MiniMed 780G insulin pump with automatic data upload [780G] incorporating an updated algorithm; calibration-free all-in-one disposable sensor; 7-day infusion set) preceded by a run-in (non-Bluetooth 780G [670G V4.0 insulin pump] requiring manual data upload; Guardian Sensor 3 [GS3] requiring calibration; 3-day infusion set), stage 1 (780G; GS3; 3-day infusion set), and stage 2 (780G; calibration-free Guardian Sensor 4; 3-day infusion set). Treatment satisfaction was assessed by Diabetes Technology Questionnaire (DTQ)-current (primary outcome) and other validated treatment satisfaction tools with glucose outcomes by continuous glucose monitoring metrics. RESULTS: Twenty-one of 22 (11 women) participants (baseline HbA1c 6.7%/50 mmol/mol) completed the study. DTQ-current scores favored e-AHCL (123.1 [17.8]) versus run-in (101.6 [24.2]) and versus stage 1 (110.6 [20.8]) (both P < 0.001) but did not differ from stage 2 (119.4 [16.0]; P = 0.271). Diabetes Medication System Rating Questionnaire short-form scores for "Convenience and Efficacy" favored e-AHCL over run-in and all stages. Percent time in range 70-180 mg/dL was greater with e-AHCL versus run-in and stage 2 (+2.9% and +3.6%, respectively; both P < 0.001). Percent times of <70 mg/dL for e-AHCL were significantly lower than run-in, stage 1, and stage 2 (-0.9%, -0.6%, and -0.5%, respectively; all P < 0.01). CONCLUSIONS: e-AHCL was feasible. User satisfaction increased compared with earlier Medtronic HCL iterations without compromising glucose control.

Unannounced Meal Challenges Using an Advanced Hybrid Closed-Loop System.

Background: The advanced hybrid closed-loop (AHCL) algorithm combines automated basal rates and corrections yet requires meal announcement for optimal outcomes. We aimed to compare the performance of the MiniMed™ 780G AHCL algorithm with and without meal announcement. Methods: In a single-arm study involving 14 adults with type 1 diabetes, we evaluated the safety and efficacy of AHCL when meals were not announced. Participants stayed at a supervised environment for 5 days, during which the outcomes of not announcing meals (≤80 g of carbohydrate) were assessed. Next, participants entered a 90-day at-home "unannounced" phase, during which all meals (≤80 g of carbohydrate) were unannounced, followed by a 90-day at-home phase in which all meals were announced. Results: Time in range (TIR 70-180 mg/dL) was lower in the unannounced versus announced periods (67.5% ± 12.5% vs. 77.7% ± 9.5%; P < 0.01, respectively), with more time spent in hyperglycemia range 180-250 mg/dL (22.7% ± 7.7% vs. 15.7% ± 7.2%) and >250 mg/dL (7.9% ± 6.4% vs. 3.6% ± 2.7%), but less time in hypoglycemia range 54-70 mg/dL (1.6% ± 1% vs. 2.8% ± 1.8%) and <54 mg/dL (0.3% ± 0.4% vs. 0.7% ± 0.9%). Not announcing meals containing up to 60 g of carbohydrate did not lead to increase in postprandial extreme dysglycemia >250 mg/dL, and up to 20 g of unannounced carbohydrates did not significantly change the TIR 70-180 mg/dL compared with full announcement. Conclusion: The AHCL system is optimized for use with meal announcement. While not announcing meals of ≤80 g carbohydrates appears to be safe, it results in suboptimal postprandial glycemic control, especially with high-carbohydrate meals. Not announcing small meals (≤20 g carbohydrate) does not deteriorate glycemic control. Clinical Trial Registration number: NCT04479826.

Improved technology satisfaction and sleep quality with Medtronic MiniMed® Advanced Hybrid Closed-Loop delivery compared to predictive low glucose suspend in people with Type 1 Diabetes in a randomized crossover trial.

BACKGROUND: Automated insulin delivery aims to lower treatment burden and improve quality of life as well as glycemic outcomes. METHODS: We present sub-study data from a dual-center, randomized, open-label, two-sequence crossover study in automated insulin delivery naïve users, comparing Medtronic MiniMed® Advanced Hybrid Closed-Loop (AHCL) to Sensor Augmented Pump therapy with Predictive Low Glucose Management (SAP + PLGM). At the end of each 4-week intervention, impacts on quality of life, sleep and treatment satisfaction were compared using seven age-appropriate validated questionnaires given to patients or caregivers. RESULTS: 59/60 people completed the study (mean age 23.3 ± 14.4yrs). Statistically significant differences favoring AHCL were demonstrated in several scales (data shown as mean ± SE). In adults (≥ 18yrs), technology satisfaction favored AHCL over PLGM as shown by a higher score in the DTSQs during AHCL (n = 28) vs SAP + PLGM (n = 29) (30.9 ± 0.7 vs 27.9 ± 0.7, p = 0.004) and DTSQc AHCL (n = 29) vs SAP + PLGM (n = 30) (11.7 ± 0.9 vs 9.2 ± 0.8, p = 0.032). Adolescents (aged 13-17yrs) also showed a higher DTSQc score during AHCL (n = 16) versus SAP + PLGM (n = 15) (14.8 ± 0.7 vs 12.1 ± 0.8, p = 0.024). The DTQ "change" score (n = 59) favored AHCL over SAP + PLGM (3.5 ± 0.0 vs 3.3 ± 0.0, p < 0.001). PSQI was completed in those > 16 years (n = 36) and demonstrated improved sleep quality during AHCL vs SAP + PLGM (4.8 ± 0.3 vs 5.7 ± 0.3, p = 0.048) with a total score > 5 indicating poor quality sleep. CONCLUSION: These data suggest that AHCL compared to SAP + PLGM mode has the potential to increase treatment satisfaction and improve subjective sleep quality in adolescents and adults with T1D.

Comparable Glucose Control with Fast-Acting Insulin Aspart Versus Insulin Aspart Using a Second-Generation Hybrid Closed-Loop System During Exercise.

Background: This study compared glucose control with fast-acting insulin aspart (FiAsp) versus insulin aspart following moderate-intensity exercise (MIE) and high-intensity exercise (HIE) using a second-generation closed-loop (CL) system in people with type 1 diabetes. Materials and Methods: This randomized crossover study compared FiAsp versus insulin aspart over four sessions during MIE and HIE with CL insulin delivery by the MiniMed™ Advanced hybrid CL system. Participants were randomly assigned FiAsp and insulin aspart each for 6 weeks and within each period performed, in random order, 40 min MIE (∼50% VO2max) and HIE (6 × 2 min ∼80% VO2max; 5 min recovery). The primary outcome was continuous glucose monitoring (CGM) time in range (TIR, 3.9-10.0 mM) for 24 h following exercise. Results: Sixteen adults (9 male; age 48 [37, 57] years; hemoglobin A1c (HbA1c) 7.0 [6.4, 7.2] %; duration diabetes 30 [17, 41] years) were recruited. In the 24 h postexercise, median TIR was >81%, time in hypoglycemia (<3.9 mM) was <4%, and time in hyperglycemia (>10 mM) was <17% for both exercise conditions and insulin formations, with no significant differences between insulins (P > 0.05). In the 2 h postexercise and overnight, the TIR approached 100% for all conditions. Conclusions: There were no differences in TIR during and 24 h after MIE or HIE when comparing insulin aspart with FiAsp delivered by a second-generation CL system. Insulin formulations with an offset in action greater than FiAsp are needed to provide a meaningful improvement in CL glucose control with exercise. Clinical Trial Registration number: ACTRN12619000469112.

Fast-Acting Insulin Aspart Versus Insulin Aspart Using a Second-Generation Hybrid Closed-Loop System in Adults With Type 1 Diabetes: A Randomized, Open-Label, Crossover Trial.

OBJECTIVE: To evaluate glucose control using fast-acting insulin aspart (faster aspart) compared with insulin aspart (IAsp) delivered by the MiniMed Advanced Hybrid Closed-Loop (AHCL) system in adults with type 1 diabetes. RESEARCH DESIGN AND METHODS: In this randomized, open-label, crossover study, participants were assigned to receive faster aspart or IAsp in random order. Stages 1 and 2 comprised of 6 weeks in closed loop, preceded by 2 weeks in open loop. This was followed by stage 3, whereby participants changed directly back to the insulin formulation used in stage 1 for 1 week in closed loop. Participants chose their own meals except for two standardized meal tests, a missed meal bolus and late meal bolus. The primary outcome was the percentage of time sensor glucose values were from 70 to 180 mg/dL (time in range; [TIR]). RESULTS: Twenty-five adults (52% male) were recruited; the median (interquartile range) age was 48 (37, 57) years, and the median HbA1c was 7.0% (6.6, 7.2) (53 [49, 55] mmol/mol). Faster aspart demonstrated greater overall TIR compared with IAsp (82.3% [78.5, 83.7] vs. 79.6% [77.0, 83.4], respectively; mean difference 1.9% [0.5, 3.3]; P = 0.007). Four-hour postprandial glucose TIR was higher using faster aspart compared with IAsp for all meals combined (73.6% [69.4, 80.2] vs. 72.1% [64.5, 78.5], respectively; median difference 3.5% [1.0, 7.3]; P = 0.003). There was no ketoacidosis or severe hypoglycemia. CONCLUSIONS: Faster aspart safely improved glucose control compared with IAsp in a group of adults with well-controlled type 1 diabetes using AHCL. The modest improvement was mainly related to mealtime glycemia. While the primary outcome demonstrated statistical significance, the clinical impact may be small, given an overall difference in TIR of 1.9%.

Fast-acting insulin aspart (Fiasp®) improves glycemic outcomes when used with MiniMedTM 670G hybrid closed-loop system in simulated trials compared to NovoLog®.

INTRODUCTION: Medtronic has developed a virtual patient simulator for modeling and predicting insulin therapy outcomes for people with type 1 diabetes (T1D). An enhanced simulator was created to estimate outcomes when using the MiniMedTM 670G system with standard NovoLog® (EU: NovoRapid, US: NovoLog) versus Fiasp ® by using clinical data. METHODS: Sixty-seven participants' PK profiles were generated per type of insulin (Total of 134 PK profiles). 7,485 virtual patients' PK measurements was matched with one of the 67 NovoLog® PK Tmax values. These 7,485 virtual patients were then simulated using the Medtronic MiniMed™ 670G algorithm following an in-silico protocol of 90 days: 14 days in open loop (Manual Mode) followed by 76 days in closed loop (Auto Mode). Simulation study was repeated with each NovoLog® PK profile being replaced by its corresponding Fiasp® PK profile in the same virtual patient. To validate our in-silico analysis, we compared the results of "actual" 19 "real life" patients from a clinical study RESULTS: Simulated overall and postprandial glycemic outcomes improved in all age groups with Fiasp®. The percentage of time in the euglycemic range increased by about ~2.2% with Fiasp®, in all age groups (p < 0.01). The percentage of time spent at <70 mg/dL was reduced by about ~0.6% with insulin Fiasp® (p < 0.01) and the mean glucose was reduced by about 1.3 mg/dL (p < 0.01), excluding those age <7 years. The simulated mean postprandial SG was reduced by ~5 mg/dL, a significant difference for all age groups. A clinical study results showed similar improvements with MiniMedTM 670G system when switching from NovoLog® to Fiasp®. CONCLUSIONS: The simulation studies indicate that using Fiasp® in place of NovoLog® with the MiniMedTM 670G system will significantly improve the time spent in the healthy, euglycemic range and reduce exposure to hyperglycemia and hypoglycemia in most patients.

Improved Glycemic Outcomes With Medtronic MiniMed Advanced Hybrid Closed-Loop Delivery: Results From a Randomized Crossover Trial Comparing Automated Insulin Delivery With Predictive Low Glucose Suspend in People With Type 1 Diabetes.

OBJECTIVE: To study the MiniMed Advanced Hybrid Closed-Loop (AHCL) system, which includes an algorithm with individualized basal target set points, automated correction bolus function, and improved Auto Mode stability. RESEARCH DESIGN AND METHODS: This dual-center, randomized, open-label, two-sequence crossover study in automated-insulin-delivery-naive participants with type 1 diabetes (aged 7-80 years) compared AHCL to sensor-augmented pump therapy with predictive low glucose management (SAP + PLGM). Each study phase was 4 weeks, preceded by a 2- to 4-week run-in and separated by a 2-week washout. RESULTS: The study was completed by 59 of 60 people (mean age 23.3 ± 14.4 years). Time in target range (TIR) 3.9-10 mmol/L (70-180 mg/dL) favored AHCL over SAP + PLGM (70.4 ± 8.1% vs. 57.9 ± 11.7%) by 12.5 ± 8.5% (P < 0.001), with greater improvement overnight (18.8 ± 12.9%, P < 0.001). All age-groups (children [7-13 years], adolescents [14-21 years], and adults [>22 years]) demonstrated improvement, with adolescents showing the largest improvement (14.4 ± 8.4%). Mean sensor glucose (SG) at run-in was 9.3 ± 0.9 mmol/L (167 ± 16.2 mg/dL) and improved with AHCL (8.5 ± 0.7 mmol/L [153 ± 12.6 mg/dL], P < 0.001), but deteriorated during PLGM (9.5 ± 1.1 mmol/L [17 ± 19.8 mg/dL], P < 0.001). TIR was optimal when the algorithm set point was 5.6 mmol/L (100 mg/dL) compared with 6.7 mmol/L (120 mg/dL), 72.0 ± 7.9% vs. 64.6 ± 6.9%, respectively, with no additional hypoglycemia. Auto Mode was active 96.4 ± 4.0% of the time. The percentage of hypoglycemia at baseline (<3.9 mmol/L [70 mg/dL] and ≤3.0 mmol/L [54 mg/dL]) was 3.1 ± 2.1% and 0.5 ± 0.6%, respectively. During AHCL, the percentage time at <3.9 mmol/L (70 mg/dL) improved to 2.1 ± 1.4% (P = 0.034) and was statistically but not clinically reduced for ≤3.0 mmol/L (54 mg/dL) (0.5 ± 0.5%; P = 0.025). There was one episode of mild diabetic ketoacidosis attributed to an infusion set failure in combination with an intercurrent illness, which occurred during the SAP + PLGM arm. CONCLUSIONS: AHCL with automated correction bolus demonstrated significant improvement in glucose control compared with SAP + PLGM. A lower algorithm SG set point during AHCL resulted in greater TIR, with no increase in hypoglycemia.

Closed-Loop Insulin Delivery for Adults with Type 1 Diabetes Undertaking High-Intensity Interval Exercise Versus Moderate-Intensity Exercise: A Randomized, Crossover Study.

BACKGROUND: We aimed to compare closed-loop glucose control for people with type 1 diabetes undertaking high-intensity interval exercise (HIIE) versus moderate-intensity exercise (MIE). METHODS: Adults with type 1 diabetes established on insulin pumps undertook HIIE and MIE stages in random order during automated insulin delivery via a closed-loop system (Medtronic). Frequent venous sampling for glucose, lactate, ketones, insulin, catecholamines, cortisol, growth hormone, and glucagon levels was performed. The primary outcome was plasma glucose <4.0 mmol/L for ≥15 min, from exercise commencement to 120 min postexercise. Secondary outcomes included continuous glucose monitoring and biochemical parameters. RESULTS: Twelve adults (age mean ± standard deviation 40 ± 13 years) were recruited; all completed the study. Plasma glucose of one participant fell to 3.4 mmol/L following MIE completion; no glucose levels were <4.0 mmol/L for HIIE (primary outcome). There were no glucose excursions >15.0 mmol/L for either stage. Mean (±standard error) plasma glucose did not differ between stages pre-exercise; was higher during exercise in HIIE than MIE (11.3 ± 0.5 mmol/L vs. 9.7 ± 0.6 mmol/L, respectively; P < 0.001); and remained higher until 60 min postexercise. There were no differences in circulating free insulin before, during, or postexercise. During HIIE compared with MIE, there were greater increases in lactate (P < 0.001), catecholamines (all P < 0.05), and cortisol (P < 0.001). Ketones increased more with HIIE than MIE postexercise (P = 0.031). CONCLUSIONS: Preliminary findings suggest that closed-loop glucose control is safe for people undertaking HIIE and MIE. However, the management of the postexercise rise in ketones secondary to counter-regulatory hormone-induced insulin resistance observed with HIIE may represent a challenge for closed-loop systems.

Exploration of the Performance of a Hybrid Closed Loop Insulin Delivery Algorithm That Includes Insulin Delivery Limits Designed to Protect Against Hypoglycemia.

BACKGROUND: Hypoglycemia remains a risk for closed loop insulin delivery particularly following exercise or if the glucose sensor is inaccurate. The aim of this study was to test whether an algorithm that includes a limit to insulin delivery is effective at protecting against hypoglycemia under those circumstances. METHODS: An observational study on 8 participants with type 1 diabetes was conducted, where a hybrid closed loop system (HCL) (Medtronic™ 670G) was challenged with hypoglycemic stimuli: exercise and an overreading glucose sensor. RESULTS: There was no overnight or exercise-induced hypoglycemia during HCL insulin delivery. All daytime hypoglycemia was attributable to postmeal bolused insulin in those participants with a more aggressive carbohydrate factor. CONCLUSION: HCL systems rely on accurate carbohydrate ratios and carbohydrate counting to avoid hypoglycemia. The algorithm that was tested against moderate exercise and an overreading glucose sensor performed well in terms of hypoglycemia avoidance. Algorithm refinement continues in preparation for long-term outpatient trials.

Automated hybrid closed-loop control with a proportional-integral-derivative based system in adolescents and adults with type 1 diabetes: individualizing settings for optimal performance.

BACKGROUND: Automated insulin delivery systems, utilizing a control algorithm to dose insulin based upon subcutaneous continuous glucose sensor values and insulin pump therapy, will soon be available for commercial use. The objective of this study was to determine the preliminary safety and efficacy of initialization parameters with the Medtronic hybrid closed-loop controller by comparing percentage of time in range, 70-180 mg/dL (3.9-10 mmol/L), mean glucose values, as well as percentage of time above and below target range between sensor-augmented pump therapy and hybrid closed-loop, in adults and adolescents with type 1 diabetes. METHODS: We studied an initial cohort of 9 adults followed by a second cohort of 15 adolescents, using the Medtronic hybrid closed-loop system with the proportional-integral-derivative with insulin feed-back (PID-IFB) algorithm. Hybrid closed-loop was tested in supervised hotel-based studies over 4-5 days. RESULTS: The overall mean percentage of time in range (70-180 mg/dL, 3.9-10 mmol/L) during hybrid closed-loop was 71.8% in the adult cohort and 69.8% in the adolescent cohort. The overall percentage of time spent under 70 mg/dL (3.9 mmol/L) was 2.0% in the adult cohort and 2.5% in the adolescent cohort. Mean glucose values were 152 mg/dL (8.4 mmol/L) in the adult cohort and 153 mg/dL (8.5 mmol/L) in the adolescent cohort. CONCLUSIONS: Closed-loop control using the Medtronic hybrid closed-loop system enables adaptive, real-time basal rate modulation. Initializing hybrid closed-loop in clinical practice will involve individualizing initiation parameters to optimize overall glucose control.

Glycemia, Treatment Satisfaction, Cognition, and Sleep Quality in Adults and Adolescents with Type 1 Diabetes When Using a Closed-Loop System Overnight Versus Sensor-Augmented Pump with Low-Glucose Suspend Function: A Randomized Crossover Study.

BACKGROUND: We compared glycemia, treatment satisfaction, sleep quality, and cognition using a nighttime Android-based hybrid closed-loop system (Android-HCLS) with sensor-augmented pump with low-glucose suspend function (SAP-LGS) in people with type 1 diabetes. MATERIALS AND METHODS: An open-label, prospective, randomized crossover study of 16 adults (mean [SD] age 42.1 [9.6] years) and 12 adolescents (15.2 [1.6] years) was conducted. All participants completed four consecutive nights at home with Android-HCLS (proportional integral derivative with insulin feedback algorithm; Medtronic) and SAP-LGS. PRIMARY OUTCOME: percent continuous glucose monitoring (CGM) time (00:00-08:00 h) within target range (72-144 mg/dL). Secondary endpoints: percent CGM time above target (>144 mg/dL); below target (<72 mg/dL); glycemic variability (SD); symptomatic hypoglycemia; adult treatment satisfaction; sleep quality; and cognitive function. RESULTS: The primary outcome for all participants was not statistically different between Android-HCLS and SAP-LGS (mean [SD] 59.4 [17.9]% vs. 53.1 [18]%; p = 0.14). Adults had greater percent time within target range (57.7 [18.6]% vs. 44.5 [14.5]%; p < 0.006); less time above target (42.0 [18.7]% vs. 52.6 [16.5]%; p = 0.034); lower glycemic variability (35 [10.7] mg/dL vs. 46 [10.7] mg/dL; p = 0.003); and less (median [IQR]) time below target (0.0 [0.0-0.4]% vs. 0.80 [0.0-3.9]%; p = 0.025). In adolescents, time below target was lower with Android-HCLS vs. SAP-LGS (0.0 [0.0-0.0]% vs. 1.8 [0.1-7.9]%; p = 0.011). Nocturnal symptomatic hypoglycemia was less (1 vs. 10; p = 0.007) in adolescents, but not adults (5 vs. 13; p = 0.059). In adults, treatment satisfaction increased by 10 points (p < 0.02). Sleep quality and cognition did not differ. CONCLUSIONS: Android-HCLS in both adults and adolescents reduced nocturnal hypoglycemia and, in adults, improved overnight time in target range and treatment satisfaction compared with SAP-LGS.

Effectiveness of a Predictive Algorithm in the Prevention of Exercise-Induced Hypoglycemia in Type 1 Diabetes.

BACKGROUND: Sensor-augmented pump therapy (SAPT) with a predictive algorithm to suspend insulin delivery has the potential to reduce hypoglycemia, a known obstacle in improving physical activity in patients with type 1 diabetes. The predictive low glucose management (PLGM) system employs a predictive algorithm that suspends basal insulin when hypoglycemia is predicted. The aim of this study was to determine the efficacy of this algorithm in the prevention of exercise-induced hypoglycemia under in-clinic conditions. METHODS: This was a randomized, controlled cross-over study in which 25 participants performed 2 consecutive sessions of 30 min of moderate-intensity exercise while on basal continuous subcutaneous insulin infusion on 2 study days: a control day with SAPT alone and an intervention day with SAPT and PLGM. The predictive algorithm suspended basal insulin when sensor glucose was predicted to be below the preset hypoglycemic threshold in 30 min. We tested preset hypoglycemic thresholds of 70 and 80 mg/dL. The primary outcome was the requirement for hypoglycemia treatment (symptomatic hypoglycemia with plasma glucose <63 mg/dL or plasma glucose <50 mg/dL) and was compared in both control and intervention arms. RESULTS: Results were analyzed in 19 participants. In the intervention arm with both thresholds, only 6 participants (32%) required treatment for hypoglycemia compared with 17 participants (89%) in the control arm (P = 0.003). In participants with a 2-h pump suspension on intervention days, the plasma glucose was 84 ± 12 and 99 ± 24 mg/dL at thresholds of 70 and 80 mg/dL, respectively. CONCLUSIONS: SAPT with PLGM reduced the need for hypoglycemia treatment after moderate-intensity exercise in an in-clinic setting.

Automated Overnight Closed-Loop Control Using a Proportional-Integral-Derivative Algorithm with Insulin Feedback in Children and Adolescents with Type 1 Diabetes at Diabetes Camp.

OBJECTIVE: This study determined the feasibility and efficacy of an automated proportional-integral-derivative with insulin feedback (PID-IFB) controller in overnight closed-loop (OCL) control of children and adolescents with type 1 diabetes over multiple days in a diabetes camp setting. RESEARCH DESIGN AND METHODS: The Medtronic (Northridge, CA) Android™ (Google, Mountain View, CA)-based PID-IFB system consists of the Medtronic Minimed Revel™ 2.0 pump and Enlite™ sensor, a control algorithm residing on an Android phone, a translator, and remote monitoring capabilities. An inpatient study was completed for 16 participants to determine feasibility. For the camp study, subjects with type 1 diabetes were randomized to either OCL or sensor-augmented pump therapy (control conditions) per night for up to 6 nights at diabetes camp. RESULTS: During the camp study, 21 subjects completed 50 OCL nights and 52 control nights. Based on intention to treat, the median time spent in range, from 70 to 150 mg/dL, was greater during OCL at 66.4% (n = 55) versus 50.6% (n = 52) during the control period (P = 0.004). A per-protocol analysis allowed for assessment of algorithm performance with the median percentage time in range, 70-150 mg/dL, being 75.5% (n = 37) for OCL versus 47.6% (n = 32) for the control period (P < 0.001). There was less time spent in the hypoglycemic ranges <60 mg/dL and <70 mg/dL during OCL compared with the control period (P = 0.003 and P < 0.001, respectively). CONCLUSIONS: The PID-IFB controller is effective in improving time spent in range as well as reducing nocturnal hypoglycemia during the overnight period in children and adolescents with type 1 diabetes in a diabetes camp setting.

Hybrid Closed-Loop Insulin Delivery in Type 1 Diabetes During Supervised Outpatient Conditions.

BACKGROUND: Efficacy and safety of the Medtronic Hybrid Closed-Loop (HCL) system were tested in subjects with type 1 diabetes in a supervised outpatient setting. METHODS: The HCL system is a prototype research platform that includes a sensor-augmented insulin pump in communication with a control algorithm housed on an Android-based cellular device. Nine subjects with type 1 diabetes (5 female, mean age 53.3 years, mean A1C 7.2%) underwent 9 studies totaling 571 hours of closed-loop control using either default or personalized parameters. The system required meal announcements with estimates of carbohydrate (CHO) intake that were based on metabolic kitchen quantification (MK), dietician estimates (D), or subject estimates (Control). Postprandial glycemia was compared for MK, D, and Control meals. RESULTS: The overall sensor glucose mean was 145 ± 43, the overall percentage time in the range 70-180 mg/dL was 80%, the overall percentage time <70 mg/dL was 0.79%. Compared to intervals of default parameter use (225 hours), intervals of personalized parameter use (346 hours), sensor glucose mean was 158 ± 49 and 137 ± 37 mg/dL (P < .001), respectively, and included more time in range (87% vs 68%) and less time below range (0.54% vs 1.18%). Most subjects underestimated the CHO content of meals, but postprandial glycemia was not significantly different between MK and matched Control meals (P = .16) or between D and matched Control meals (P = .76). There were no episodes of severe hypoglycemia. CONCLUSIONS: The HCL system was efficacious and safe during this study. Personally adapted HCL parameters were associated with more time in range and less time below range than default parameters. Accurate estimates of meal CHO did not contribute to improved postprandial glycemia.

Reduced hypoglycemia and increased time in target using closed-loop insulin delivery during nights with or without antecedent afternoon exercise in type 1 diabetes.

OBJECTIVE: Afternoon exercise increases the risk of nocturnal hypoglycemia (NH) in subjects with type 1 diabetes. We hypothesized that automated feedback-controlled closed-loop (CL) insulin delivery would be superior to open-loop (OL) control in preventing NH and maintaining a higher proportion of blood glucose levels within the target blood glucose range on nights with and without antecedent afternoon exercise. RESEARCH DESIGN AND METHODS: Subjects completed two 48-h inpatient study periods in random order: usual OL control and CL control using a proportional-integrative-derivative plus insulin feedback algorithm. Each admission included a sedentary day and an exercise day, with a standardized protocol of 60 min of brisk treadmill walking to 65-70% maximum heart rate at 3:00 p.m. RESULTS: Among 12 subjects (age 12-26 years, A1C 7.4±0.6%), antecedent exercise increased the frequency of NH (reference blood glucose<60 mg/dL) during OL control from six to eight events. In contrast, there was only one NH event each on nights with and without antecedent exercise during CL control (P=0.04 vs. OL nights). Overnight, the percentage of glucose values in target range was increased with CL control (P<0.0001). Insulin delivery was lower between 10:00 p.m. and 2:00 a.m. on nights after exercise on CL versus OL, P=0.008. CONCLUSIONS: CL insulin delivery provides an effective means to reduce the risk of NH while increasing the percentage of time spent in target range, regardless of activity level in the mid-afternoon. These data suggest that CL control could be of benefit to patients with type 1 diabetes even if it is limited to the overnight period.

Model-based sensor-augmented pump therapy.

BACKGROUND: In insulin pump therapy, optimization of bolus and basal insulin dose settings is a challenge. We introduce a new algorithm that provides individualized basal rates and new carbohydrate ratio and correction factor recommendations. The algorithm utilizes a mathematical model of blood glucose (BG) as a function of carbohydrate intake and delivered insulin, which includes individualized parameters derived from sensor BG and insulin delivery data downloaded from a patient's pump. METHODS: A mathematical model of BG as a function of carbohydrate intake and delivered insulin was developed. The model includes fixed parameters and several individualized parameters derived from the subject's BG measurements and pump data. Performance of the new algorithm was assessed using n = 4 diabetic canine experiments over a 32 h duration. In addition, 10 in silico adults from the University of Virginia/Padova type 1 diabetes mellitus metabolic simulator were tested. RESULTS: The percentage of time in glucose range 80-180 mg/dl was 86%, 85%, 61%, and 30% using model-based therapy and [78%, 100%] (brackets denote multiple experiments conducted under the same therapy and animal model), [75%, 67%], 47%, and 86% for the control experiments for dogs 1 to 4, respectively. The BG measurements obtained in the simulation using our individualized algorithm were in 61-231 mg/dl min-max envelope, whereas use of the simulator's default treatment resulted in BG measurements 90-210 mg/dl min-max envelope. CONCLUSIONS: The study results demonstrate the potential of this method, which could serve as a platform for improving, facilitating, and standardizing insulin pump therapy based on a single download of data.

The use of an automated, portable glucose control system for overnight glucose control in adolescents and young adults with type 1 diabetes.

OBJECTIVE: A key milestone in progress towards providing an efficacious and safe closed-loop artificial pancreas system for outpatient use is the development of fully automated, portable devices with fault detection capabilities to ensure patient safety. The ability to remotely monitor the operation of the closed-loop system would facilitate future physician-supervised home studies. RESEARCH DESIGN AND METHODS: This study was designed to investigate the efficacy and safety of a fully automated, portable, closed-loop system. The Medtronic Portable Glucose Control System (PGCS) consists of two subcutaneous glucose sensors, a control algorithm based on proportional-integral-derivative with insulin feedback operating from a BlackBerry Storm smartphone platform, Bluetooth radiofrequency translator, and an off-the-shelf Medtronic Paradigm Veo insulin pump. Participants with type 1 diabetes using insulin pump therapy underwent two consecutive nights of in-clinic, overnight, closed-loop control after a baseline open-loop assessment. RESULTS: Eight participants attended for 16 overnight studies. The PGCS maintained mean overnight plasma glucose levels of 6.4 ± 1.7 mmol/L (115 ± 31 mg/dL). The proportion of time with venous plasma glucose <3.9, between 3.9 and 8 (70 and 144 mg/dL), and >8 mmol/L was 7, 78, and 15%, respectively. The proportion of time the sensor glucose values were maintained between 3.9 and 8 mmol/L was greater for closed-loop than open-loop (84.5 vs. 46.7%; P < 0.0001), and time spent <3.3 mmol/L was also reduced (0.9 vs. 3%; P < 0.0001). CONCLUSIONS: These results suggest that the PGCS, an automated closed-loop device, is safe and effective in achieving overnight glucose control in patients with type 1 diabetes.

The effect of insulin feedback on closed loop glucose control.

CONTEXT: Initial studies of closed-loop proportional integral derivative control in individuals with type 1 diabetes showed good overnight performance, but with breakfast meal being the hardest to control and requiring supplemental carbohydrate to prevent hypoglycemia. OBJECTIVE: The aim of this study was to assess the ability of insulin feedback to improve the breakfast-meal profile. DESIGN AND SETTING: We performed a single center study with closed-loop control over approximately 30 h at an inpatient clinical research facility. PATIENTS: Eight adult subjects with previously diagnosed type 1 diabetes participated. INTERVENTION: Subjects received closed-loop insulin delivery with supplemental carbohydrate as needed. MAIN OUTCOME MEASURES: Outcome measures were plasma insulin concentration, model-predicted plasma insulin concentration, 2-h postprandial and 3- to 4-h glucose rate-of-change following breakfast after 1 d of closed-loop control, and the need for supplemental carbohydrate in response to nadir hypoglycemia. RESULTS: Plasma insulin levels during closed loop were well correlated with model predictions (R = 0.86). Fasting glucose after 1 d of closed loop was not different from nighttime target (118 ± 9 vs. 110 mg/dl; P = 0.38). Two-hour postbreakfast glucose was 132 ± 16 mg/dl with stable values 3-4 h after the meal (0.03792 ± 0.0884 mg/dl · min, not different from 0; P = 0.68) and at target (97 ± 6 mg/dl, not different from 90; P = 0.28). Three subjects required supplemental carbohydrates after breakfast on d 2 of closed loop. CONCLUSIONS/INTERPRETATION: Insulin feedback can be implemented using a model estimate of concentration. Proportional integral derivative control with insulin feedback can achieve a desired breakfast response but still requires supplemental carbohydrate to be delivered in some instances. Studies assessing more optimal control configurations and safeguards need to be conducted.