Dataset Information

Adaptive Control of an Artificial Pancreas Using Model Identification, Adaptive Postprandial Insulin Delivery, and Heart Rate and Accelerometry as Control Inputs.

ABSTRACT: BACKGROUND:People with type 1 diabetes (T1D) have varying sensitivities to insulin and also varying responses to meals and exercise. We introduce a new adaptive run-to-run model predictive control (MPC) algorithm that can be used to help people with T1D better manage their glucose levels using an artificial pancreas (AP). The algorithm adapts to individuals' different insulin sensitivities, glycemic response to meals, and adjustment during exercise as a continuous input during free-living conditions. METHODS:A new insulin sensitivity adaptation (ISA) algorithm is presented that updates each patient's insulin sensitivity during nonmeal periods to reduce the error between the actual glucose levels and the process model. We further demonstrate how an adaptive learning postprandial hypoglycemia prevention algorithm (ALPHA) presented in the previous work can complement the ISA algorithm, and the algorithm can adapt in several days. We further show that if physical activity is incorporated as a continuous input (heart rate and accelerometry), performance is improved. The contribution of this work is the description of the ISA algorithm and the evaluation of how ISA, ALPHA, and incorporation of exercise metrics as a continuous input can impact glycemic control. RESULTS:Incorporating ALPHA, ISA, and physical activity into the MPC improved glycemic outcome measures. The adaptive learning postprandial hypoglycemia prevention algorithm combined with ISA significantly reduced time spent in hypoglycemia by 71.7% and the total number of rescue carbs by 67.8% to 0.37% events/day/patient. Insulin sensitivity adaptation significantly reduced model-actual mismatch by 12.2% compared to an AP without ISA. Incorporating physical activity as a continuous input modestly improved time in the range 70 to 180 mg/dL during high physical activity days from 84.4% to 84.9% and reduced the percentage time in hypoglycemia by 23.8% from 2.1% to 1.6%. CONCLUSION:Adapting postprandial insulin delivery, insulin sensitivity, and adapting to physical exercise in an MPC-based AP systems can improve glycemic outcomes.

SUBMITTER: Resalat N

PROVIDER: S-EPMC6835177 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Adaptive Control of an Artificial Pancreas Using Model Identification, Adaptive Postprandial Insulin Delivery, and Heart Rate and Accelerometry as Control Inputs.

Resalat Navid N Hilts Wade W Youssef Joseph El JE Tyler Nichole N Castle Jessica R JR Jacobs Peter G PG

Journal of diabetes science and technology 20191009 6

<h4>Background</h4>People with type 1 diabetes (T1D) have varying sensitivities to insulin and also varying responses to meals and exercise. We introduce a new adaptive run-to-run model predictive control (MPC) algorithm that can be used to help people with T1D better manage their glucose levels using an artificial pancreas (AP). The algorithm adapts to individuals' different insulin sensitivities, glycemic response to meals, and adjustment during exercise as a continuous input during free-livin ...[more]

PMID: 31595784

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Project description:ObjectiveTo compare the safety and efficacy of overnight closed loop delivery of insulin (artificial pancreas) with conventional insulin pump therapy in adults with type 1 diabetes.DesignTwo sequential, open label, randomised controlled crossover, single centre studies.SettingClinical research facility.Participants24 adults (10 men, 14 women) with type 1 diabetes, aged 18-65, who had used insulin pump therapy for at least three months: 12 were tested after consuming a medium sized meal and the other 12 after consuming a larger meal accompanied by alcohol.InterventionDuring overnight closed loop delivery, sensor measurements of glucose were fed into a computer algorithm, which advised on insulin pump infusion rates at 15 minute intervals. During control nights, conventional insulin pump settings were applied. One study compared closed loop delivery of insulin with conventional pump therapy after a medium sized evening meal (60 g of carbohydrates) at 1900, depicting the scenario of "eating in." The other study was carried out after a later large evening meal (100 g of carbohydrates) at 2030, accompanied by white wine (0.75 g/kg ethanol) and depicted the scenario of "eating out."Main outcome measuresThe primary outcome was the time plasma glucose levels were in target (3.91-8.0 mmol/L) during closed loop delivery and a comparable control period. Secondary outcomes included pooled data analysis and time plasma glucose levels were below target (≤ 3.9 mmol/L).ResultsFor the eating in scenario, overnight closed loop delivery of insulin increased the time plasma glucose levels were in target by a median 15% (interquartile range 3-35%), P = 0.002. For the eating out scenario, closed loop delivery increased the time plasma glucose levels were in target by a median 28% (2-39%), P = 0.01. Analysis of pooled data showed that the overall time plasma glucose was in target increased by a median 22% (3-37%) with closed loop delivery (P < 0.001). Closed loop delivery reduced overnight time spent hypoglycaemic (plasma glucose ≤ 3.9 mmol/L) by a median 3% (0-20%), P=0.04, and eliminated plasma glucose concentrations below 3.0 mmol/L after midnight.ConclusionThese two small crossover trials suggest that closed loop delivery of insulin may improve overnight control of glucose levels and reduce the risk of nocturnal hypoglycaemia in adults with type 1 diabetes. Trial registration ClinicalTrials.gov NCT00910767 and NCT00944619.

Project description:Artificial pancreas system (APS) is an emerging new treatment for type 1 diabetes mellitus. The aim of this study was to develop a rat APS as a research tool and demonstrate its application. We established a rat APS using Medtronic Minimed Pump 722, Medtronic Enlite sensor, and the open artificial pancreas system as a controller. We tested different dilutions of Humalog (100 units/ml) in saline ranged from 1:3 to 1:20 and determined that 1:7 dilution works well for rats with ~500g bodyweight. Blood glucose levels (BGL) of diabetic rats fed with chow diet (58% carbohydrate) whose BGL was managed by the closed-loop APS for the total duration of 207h were in euglycemic range (70-180 mg/dl) for 94.5% of the time with 2.1% and 3.4% for hyperglycemia (>180mg/dl) and hypoglycemia (<70 mg/dl), respectively. Diabetic rats fed with Sucrose pellets (94.8% carbohydrate) for the experimental duration of 175h were in euglycemic range for 61% of the time with 35% and 4% for hyperglycemia and hypoglycemia, respectively. Heathy rats fed with chow diet showed almost a straight line of BGL ~ 95 mg/dl (average 94.8 mg/dl) during the entire experimental period (281h), which was minimally altered by food intake. In the healthy rats, feeding sucrose pellets caused greater range of BGL in high and low levels but still within euglycemic range (99.9%). Next, to study how healthy and diabetic rats handle supra-physiological concentrations of glucose, we intraperitoneally injected various amounts of 50% dextrose (2, 3, 4g/kg) and monitored BGL. Duration of hyperglycemia after injection of 50% dextrose at all three different concentrations was significantly greater for healthy rats than diabetic rats, suggesting that insulin infusion by APS was superior in reducing BGL as compared to natural insulin released from pancreatic β-cells. Ex vivo studies showed that islets isolated from diabetic rats were almost completely devoid of pancreatic β-cells but with intact α-cells as expected. Lipid droplet deposition in the liver of diabetic rats was significantly lower with higher levels of triacylglyceride in the blood as compared to those of healthy rats, suggesting lipid metabolism was altered in diabetic rats. However, glycogen storage in the liver determined by Periodic acid-Schiff staining was not altered in diabetic rats as compared to healthy rats. A rat APS may be used as a powerful tool not only to study alterations of glucose and insulin homeostasis in real-time caused by diet, exercise, hormones, or antidiabetic agents, but also to test mathematical and engineering models of blood glucose prediction or new algorithms for closed-loop APS.

Project description:BackgroundMost patients with type 1 diabetes do not achieve their glycemic targets. We aimed to assess the efficacy of glucose-responsive insulin and glucagon closed-loop delivery for controlling glucose levels in adults with type 1 diabetes.MethodsWe conducted a randomized crossover trial involving 15 adults with type 1 diabetes, comparing standard insulin-pump therapy with dual-hormone, closed-loop delivery. Patients were admitted twice to a clinical research facility and received, in random order, both treatments. Each 15-hour visit (from 1600 to 0700) included an evening exercise session, followed by a medium-sized meal, a bedtime snack and an overnight stay. During visits that involved closed-loop delivery, basal insulin and glucagon miniboluses were delivered according to recommendations based on glucose sensor readings and a predictive dosing algorithm at 10-minute intervals. During visits involving standard insulin-pump therapy (control visits), patients used conventional treatment.ResultsDual-hormone closed-loop delivery increased the percentage of time for which patients' plasma glucose levels were in the target range (median 70.7% [interquartile range (IQR) 46.1%-88.4%] for closed-loop delivery v. 57.3% [IQR 25.2%-71.8%] for control, p = 0.003) and decreased the percentage of time for which plasma glucose levels were in the low range (bottom of target range [< 4.0 mmol/L], 0.0% [IQR 0.0%-3.0%] for closed-loop delivery v. 10.2% [IQR 0.0%-13.0%] for control, p = 0.01; hypoglycemia threshold [< 3.3 mmol/L], 0.0% [IQR 0.0%-0.0%] for closed-loop delivery v. 2.8% [IQR 0.0%-5.9%] for control, p = 0.006). Eight participants (53%) had at least 1 hypoglycemic event (plasma glucose < 3.0 mmol/L) during standard treatment, compared with just 1 participant (7%) during closed-loop treatment (p = 0.02).InterpretationDual-hormone, closed-loop delivery guided by advanced algorithms improved short-term glucose control and reduced the risk of hypoglycemia in a group of 15 adults with type 1 diabetes.Trial registrationClinicalTrials.gov, no. NCT01297946.

Project description:Aims/hypothesisImbalances in glucose metabolism are hallmarks of clinically silent prediabetes (defined as impaired fasting glucose and/or impaired glucose tolerance) representing dysmetabolism trajectories leading to type 2 diabetes. CD26/dipeptidyl peptidase 4 (DPP4) is a clinically proven molecular target of diabetes-controlling drugs but the DPP4 gene control of dysglycaemia is not proven.MethodsWe dissected the genetic control of post-OGTT and insulin release responses by the DPP4 gene in a Portuguese population-based cohort of mainly European ancestry that comprised individuals with normoglycaemia and prediabetes, and in mouse experimental models of Dpp4 deficiency and hyperenergetic diet.ResultsIn individuals with normoglycaemia, DPP4 single-nucleotide variants governed glycaemic excursions (rs4664446, p=1.63x10-7) and C-peptide release responses (rs2300757, p=6.86x10-5) upon OGTT. Association with blood glucose levels was stronger at 30 min OGTT, but a higher association with the genetic control of insulin secretion was detected in later phases of the post-OGTT response, suggesting that the DPP4 gene directly senses glucose challenges. Accordingly, in mice fed a normal chow diet but not a high-fat diet, we found that, under OGTT, expression of Dpp4 is strongly downregulated at 30 min in the mouse liver. Strikingly, no genetic association was found in prediabetic individuals, indicating that post-OGTT control by DPP4 is abrogated in prediabetes. Furthermore, Dpp4 KO mice provided concordant evidence that Dpp4 modulates post-OGTT C-peptide release in normoglycaemic but not dysmetabolic states.Conclusions/interpretationThese results showed the DPP4 gene as a strong determinant of post-OGTT levels via glucose-sensing mechanisms that are abrogated in prediabetes. We propose that impairments in DPP4 control of post-OGTT insulin responses are part of molecular mechanisms underlying early metabolic disturbances associated with type 2 diabetes.

Dataset Information

Adaptive Control of an Artificial Pancreas Using Model Identification, Adaptive Postprandial Insulin Delivery, and Heart Rate and Accelerometry as Control Inputs.

Publications

Adaptive Control of an Artificial Pancreas Using Model Identification, Adaptive Postprandial Insulin Delivery, and Heart Rate and Accelerometry as Control Inputs.

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