401
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Forlenza GP, Deshpande S, Ly TT, Howsmon DP, Cameron F, Baysal N, Mauritzen E, Marcal T, Towers L, Bequette BW, Huyett LM, Pinsker JE, Gondhalekar R, Doyle FJ, Maahs DM, Buckingham BA, Dassau E. Application of Zone Model Predictive Control Artificial Pancreas During Extended Use of Infusion Set and Sensor: A Randomized Crossover-Controlled Home-Use Trial. Diabetes Care 2017; 40:1096-1102. [PMID: 28584075 PMCID: PMC5521973 DOI: 10.2337/dc17-0500] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Accepted: 05/06/2017] [Indexed: 02/03/2023]
Abstract
OBJECTIVE As artificial pancreas (AP) becomes standard of care, consideration of extended use of insulin infusion sets (IIS) and continuous glucose monitors (CGMs) becomes vital. We conducted an outpatient randomized crossover study to test the safety and efficacy of a zone model predictive control (zone-MPC)-based AP system versus sensor augmented pump (SAP) therapy in which IIS and CGM failures were provoked via extended wear to 7 and 21 days, respectively. RESEARCH DESIGN AND METHODS A smartphone-based AP system was used by 19 adults (median age 23 years [IQR 10], mean 8.0 ± 1.7% HbA1c) over 2 weeks and compared with SAP therapy for 2 weeks in a crossover, unblinded outpatient study with remote monitoring in both study arms. RESULTS AP improved percent time 70-140 mg/dL (48.1 vs. 39.2%; P = 0.016) and time 70-180 mg/dL (71.6 vs. 65.2%; P = 0.008) and decreased median glucose (141 vs. 153 mg/dL; P = 0.036) and glycemic variability (SD 52 vs. 55 mg/dL; P = 0.044) while decreasing percent time <70 mg/dL (1.3 vs. 2.7%; P = 0.001). AP also improved overnight control, as measured by mean glucose at 0600 h (140 vs. 158 mg/dL; P = 0.02). IIS failures (1.26 ± 1.44 vs. 0.78 ± 0.78 events; P = 0.13) and sensor failures (0.84 ± 0.6 vs. 1.1 ± 0.73 events; P = 0.25) were similar between AP and SAP arms. Higher percent time in closed loop was associated with better glycemic outcomes. CONCLUSIONS Zone-MPC significantly and safely improved glycemic control in a home-use environment despite prolonged CGM and IIS wear. This project represents the first home-use AP study attempting to provoke and detect component failure while successfully maintaining safety and effective glucose control.
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Affiliation(s)
| | - Sunil Deshpande
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
- William Sansum Diabetes Center, Santa Barbara, CA
| | - Trang T Ly
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - Daniel P Howsmon
- Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY
| | - Faye Cameron
- Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY
| | - Nihat Baysal
- Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY
| | - Eric Mauritzen
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA
| | - Tatiana Marcal
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - Lindsey Towers
- Barbara Davis Center, University of Colorado Denver, Denver, CO
| | - B Wayne Bequette
- Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY
| | - Lauren M Huyett
- William Sansum Diabetes Center, Santa Barbara, CA
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, CA
| | | | - Ravi Gondhalekar
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
- William Sansum Diabetes Center, Santa Barbara, CA
| | - Francis J Doyle
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
- William Sansum Diabetes Center, Santa Barbara, CA
| | - David M Maahs
- Barbara Davis Center, University of Colorado Denver, Denver, CO
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - Bruce A Buckingham
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
| | - Eyal Dassau
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA
- William Sansum Diabetes Center, Santa Barbara, CA
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402
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Kaufman FR, Shin J. Re: Castle, et al., 2017; Diabetes Technol Ther; DOI: 10.1089/dia.2017.0012. Diabetes Technol Ther 2017; 19:440. [PMID: 28704065 DOI: 10.1089/dia.2017.0995] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
| | - John Shin
- Medtronic Diabetes , Northridge, California
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403
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404
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Abstract
Toddlers with type 1 diabetes have distinctive combination of challenges to their families and healthcare providers. A major factor is the difficulty in achieving metabolic control without risking hypoglycemia. The rising incidence of type 1 diabetes in toddlers increases the magnitude of the problem and creates a greater need for providing specialized service to cater for this age group's unique need. Type 1 has a specific disease nature in younger children and its clinical presentation mimics common childhood diseases. Symptoms and signs in the newly presented toddler with diabetes might be unspecific causing diagnosis to be missed or delayed. With the low cognitive ability and immature communication, toddlers might not be able to express their ill-feeling resulting from hypoglycemia or hyperglycemia. Hypoglycemia fear is common, which aggravates stress and reduces adherence to strict metabolic control. Nocturnal hypoglycemia is more common in toddlers and can be undiagnosed unless continuous glucose monitoring is used. Insulin administration and adjustment can be challenging due to pain, fear, refusal, and frequent intercurrent illness. Glucose monitoring is crucial. However, it can be distressing to the child and difficult to adhere to due to commitment or financial reasons. Insulin pump therapy is proven to be an effective and a safe method of treatment for toddlers, but it requires intensive training, resources, and long-term support. Provision of multidisciplinary team with special expertise in managing toddlers with diabetes is essential. Providing more physiological insulin regimes and customized technology is required to improve treatment compliance and diabetes control.
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Affiliation(s)
- Asma Deeb
- Paediatric Endocrinology Department, Mafraq Hospital , Abu Dhabi, United Arab Emirates
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405
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Rodbard D. Continuous Glucose Monitoring: A Review of Recent Studies Demonstrating Improved Glycemic Outcomes. Diabetes Technol Ther 2017; 19:S25-S37. [PMID: 28585879 PMCID: PMC5467105 DOI: 10.1089/dia.2017.0035] [Citation(s) in RCA: 259] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Continuous Glucose Monitoring (CGM) has been demonstrated to be clinically valuable, reducing risks of hypoglycemia and hyperglycemia, glycemic variability (GV), and improving patient quality of life for a wide range of patient populations and clinical indications. Use of CGM can help reduce HbA1c and mean glucose. One CGM device, with accuracy (%MARD) of approximately 10%, has recently been approved for self-adjustment of insulin dosages (nonadjuvant use) and approved for reimbursement for therapeutic use in the United States. CGM had previously been used off-label for that purpose. CGM has been demonstrated to be clinically useful in both type 1 and type 2 diabetes for patients receiving a wide variety of treatment regimens. CGM is beneficial for people using either multiple daily injections (MDI) or continuous subcutaneous insulin infusion (CSII). CGM is used both in retrospective (professional, masked) and real-time (personal, unmasked) modes: both approaches can be beneficial. When CGM is used to suspend insulin infusion when hypoglycemia is detected until glucose returns to a safe level (low-glucose suspend), there are benefits beyond sensor-augmented pump (SAP), with greater reduction in the risk of hypoglycemia. Predictive low-glucose suspend provides greater benefits in this regard. Closed-loop control with insulin provides further improvement in quality of glycemic control. A hybrid closed-loop system has recently been approved by the U.S. FDA. Closed-loop control using both insulin and glucagon can reduce risk of hypoglycemia even more. CGM facilitates rigorous evaluation of new forms of therapy, characterizing pharmacodynamics, assessing frequency and severity of hypo- and hyperglycemia, and characterizing several aspects of GV.
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Affiliation(s)
- David Rodbard
- Biomedical Informatics Consultants LLC , Potomac, Maryland
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406
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Affiliation(s)
- Satish K. Garg
- School of Medicine, University of Colorado Denver, Aurora, Colorado
- Barbara Davis Center for Diabetes, Aurora, Colorado
| | - Halis K. Akturk
- School of Medicine, University of Colorado Denver, Aurora, Colorado
- Barbara Davis Center for Diabetes, Aurora, Colorado
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407
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Chakrabarty A, Zavitsanou S, Doyle FJ, Dassau E. Event-Triggered Model Predictive Control for Embedded Artificial Pancreas Systems. IEEE Trans Biomed Eng 2017; 65:575-586. [PMID: 28541890 DOI: 10.1109/tbme.2017.2707344] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVE The development of artificial pancreas (AP) technology for deployment in low-energy, embedded devices is contingent upon selecting an efficient control algorithm for regulating glucose in people with type 1 diabetes mellitus. In this paper, we aim to lower the energy consumption of the AP by reducing controller updates, that is, the number of times the decision-making algorithm is invoked to compute an appropriate insulin dose. METHODS Physiological insights into glucose management are leveraged to design an event-triggered model predictive controller (MPC) that operates efficiently, without compromising patient safety. The proposed event-triggered MPC is deployed on a wearable platform. Its robustness to latent hypoglycemia, model mismatch, and meal misinformation is tested, with and without meal announcement, on the full version of the US-FDA accepted UVA/Padova metabolic simulator. RESULTS The event-based controller remains on for 18 h of 41 h in closed loop with unannounced meals, while maintaining glucose in 70-180 mg/dL for 25 h, compared to 27 h for a standard MPC controller. With meal announcement, the time in 70-180 mg/dL is almost identical, with the controller operating a mere 25.88% of the time in comparison with a standard MPC. CONCLUSION A novel control architecture for AP systems enables safe glycemic regulation with reduced processor computations. SIGNIFICANCE Our proposed framework integrated seamlessly with a wide variety of popular MPC variants reported in AP research, customizes tradeoff between glycemic regulation and efficacy according to prior design specifications, and eliminates judicious prior selection of controller sampling times.
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408
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Affiliation(s)
- Rayhan A. Lal
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
- Division of Endocrinology, Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - David M. Maahs
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
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409
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Abstract
The accuracy of a continuous glucose monitor (CGM) now supports its use by persons with diabetes and clinicians caring for them. This article reviews measures of CGM accuracy, factors contributing to accuracy, comparative accuracy assessment, clinical implications of CGM sensor accuracy, and recent clinical trials that have demonstrated the utility of CGMs.
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410
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Forlenza GP. Insulin Infusion Sets and Continuous Glucose Monitoring Sensors: Where the Artificial Pancreas Meets the Patient. Diabetes Technol Ther 2017; 19:206-208. [PMID: 28418732 PMCID: PMC5583547 DOI: 10.1089/dia.2017.0048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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411
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Abstract
Type 1 diabetes mellitus (T1DM), also known as autoimmune diabetes, is a chronic disease characterized by insulin deficiency due to pancreatic β-cell loss and leads to hyperglycaemia. Although the age of symptomatic onset is usually during childhood or adolescence, symptoms can sometimes develop much later. Although the aetiology of T1DM is not completely understood, the pathogenesis of the disease is thought to involve T cell-mediated destruction of β-cells. Islet-targeting autoantibodies that target insulin, 65 kDa glutamic acid decarboxylase, insulinoma-associated protein 2 and zinc transporter 8 - all of which are proteins associated with secretory granules in β-cells - are biomarkers of T1DM-associated autoimmunity that are found months to years before symptom onset, and can be used to identify and study individuals who are at risk of developing T1DM. The type of autoantibody that appears first depends on the environmental trigger and on genetic factors. The pathogenesis of T1DM can be divided into three stages depending on the absence or presence of hyperglycaemia and hyperglycaemia-associated symptoms (such as polyuria and thirst). A cure is not available, and patients depend on lifelong insulin injections; novel approaches to insulin treatment, such as insulin pumps, continuous glucose monitoring and hybrid closed-loop systems, are in development. Although intensive glycaemic control has reduced the incidence of microvascular and macrovascular complications, the majority of patients with T1DM are still developing these complications. Major research efforts are needed to achieve early diagnosis, prevent β-cell loss and develop better treatment options to improve the quality of life and prognosis of those affected.
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412
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Castle JR. Will the First Approved Automated Insulin Delivery System Be a Game-Changer in Type 1 Diabetes Management? Diabetes Technol Ther 2017; 19:137-139. [PMID: 28287846 PMCID: PMC5359679 DOI: 10.1089/dia.2017.0052] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Jessica R Castle
- Division of Endocrinology, Harold Schnitzer Diabetes Health Center, Oregon Health & Science University , Portland, Oregon
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413
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Affiliation(s)
- Irl B Hirsch
- Department of Medicine, Division of Metabolism, Endocrinology, & Nutrition, University of Washington School of Medicine , Seattle, Washington
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