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Peacock S, Frizelle I, Hussain S. A Systematic Review of Commercial Hybrid Closed-Loop Automated Insulin Delivery Systems. Diabetes Ther 2023; 14:839-855. [PMID: 37017916 PMCID: PMC10126177 DOI: 10.1007/s13300-023-01394-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 03/08/2023] [Indexed: 04/06/2023] Open
Abstract
INTRODUCTION Several different forms of automated insulin delivery systems (AID systems) have recently been developed and are now licensed for type 1 diabetes (T1D). We undertook a systematic review of reported trials and real-world studies for commercial hybrid closed-loop (HCL) systems. METHODS Pivotal, phase III and real-world studies using commercial HCL systems that are currently approved for use in type 1 diabetes were reviewed with a devised protocol using the Medline database. RESULTS Fifty-nine studies were included in the systematic review (19 for 670G; 8 for 780G; 11 for Control-IQ; 14 for CamAPS FX; 4 for Diabeloop; and 3 for Omnipod 5). Twenty were real-world studies, and 39 were trials or sub-analyses. Twenty-three studies, including 17 additional studies, related to psychosocial outcomes and were analysed separately. CONCLUSIONS These studies highlighted that HCL systems improve time In range (TIR) and arouse minimal concerns around severe hypoglycaemia. HCL systems are an effective and safe option for improving diabetes care. Real-world comparisons between systems and their effects on psychological outcomes require further study.
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Affiliation(s)
- Sofia Peacock
- Department of Diabetes, School of Cardiovascular, Metabolic Medicine and Sciences, King's College London, London, UK
- Department of Diabetes and Endocrinology, Guy's & St Thomas' NHS Foundation Trust, King's College London, 3rd Floor Lambeth Wing, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - Isolda Frizelle
- Department of Diabetes and Endocrinology, Guy's & St Thomas' NHS Foundation Trust, King's College London, 3rd Floor Lambeth Wing, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK
| | - Sufyan Hussain
- Department of Diabetes, School of Cardiovascular, Metabolic Medicine and Sciences, King's College London, London, UK.
- Department of Diabetes and Endocrinology, Guy's & St Thomas' NHS Foundation Trust, King's College London, 3rd Floor Lambeth Wing, St Thomas' Hospital, Westminster Bridge Road, London, SE1 7EH, UK.
- Institute of Diabetes, Endocrinology and Obesity, King's Health Partners, London, UK.
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Sanz R, García P, Romero-Vivó S, Díez JL, Bondia J. Near-optimal feedback control for postprandial glucose regulation in type 1 diabetes. ISA TRANSACTIONS 2023; 133:345-352. [PMID: 36116963 DOI: 10.1016/j.isatra.2022.06.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 04/19/2022] [Accepted: 06/26/2022] [Indexed: 06/15/2023]
Abstract
This paper is focused on feedback control of postprandial glucose levels for patients with type 1 Diabetes Mellitus. There are two important limitations that make this a challenging problem. First, the slow subcutaneous insulin pharmacokinetics that introduces a significant lag into the control loop. Second, the positivity constraint on the control action, meaning that it is not possible to remove insulin from the body. In this paper, both issues are explicitly considered in the design process using the internal model control framework, to derive a near-optimal feedback controller. Optimality is understood here as minimizing the blood glucose peak after a meal intake and, at the same time, preventing glucose values below a prescribed threshold. It is shown how the proposed controller approaches the optimal closed-loop performance as a limit case. The theoretical results are supported by a numerical example and the feasibility of the overall strategy under uncertainties is illustrated using an extended version UVa/Padova metabolic simulator.
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Affiliation(s)
- R Sanz
- Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 València, Spain.
| | - P García
- Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 València, Spain.
| | - S Romero-Vivó
- Instituto de Matemática Multidisciplinar, Universitat Politècnica de València, 46022 València, Spain; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, 28029 Madrid, Spain.
| | - J L Díez
- Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 València, Spain; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, 28029 Madrid, Spain.
| | - J Bondia
- Instituto de Automática e Informática Industrial, Universitat Politècnica de València, 46022 València, Spain; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, 28029 Madrid, Spain.
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3
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Renard E. Automated insulin delivery systems: from early research to routine care of type 1 diabetes. Acta Diabetol 2023; 60:151-161. [PMID: 35994106 DOI: 10.1007/s00592-022-01929-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 06/22/2022] [Indexed: 01/24/2023]
Abstract
Automated insulin delivery (AID) systems, so-called closed-loop systems or artificial pancreas, are based upon the concept of insulin supply driven by blood glucose levels and their variations according to body glucose needs, glucose intakes and insulin action. They include a continuous glucose monitoring device which provides a signal to a control algorithm tuning insulin delivery from an infusion pump. The control algorithm is the key of the system since it commands insulin administration in order to maintain blood glucose in a predefined target range and close to a near-normal glucose level. The last two decades have shown dramatic advances toward the use in free life of AID systems for routine care of type 1 diabetes through step-by-step demonstrations of feasibility, safety and efficacy in successive hospital, transitional and outpatient trials. Because of the constraints of pharmacokinetics and dynamics of subcutaneous insulin delivery, the currently available AID systems are all 'hybrid' or 'semi-automated' insulin delivery systems with a need of meal and exercise announcements in order to anticipate rapid glucose variations through pre-meal bolus or pre-exercise reduction of infusion rate. Nevertheless, these AID systems significantly improve time spent in a near-normal range with a reduction of the risk of hypoglycemia and the mental load of managing diabetes in everyday life, representing a milestone in insulin therapy. Expected progression toward fully automated, further miniaturized and integrated, possibly implantable on long-term and more physiological closed-loop systems paves the way for a functional cure of type 1 diabetes.
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Affiliation(s)
- Eric Renard
- Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital, Montpellier, France.
- INSERM Clinical Investigation Centre CIC 1411, Montpellier, France.
- Department of Physiology, Institute of Functional Genomics, CNRS, INSERM, University of Montpellier, Montpellier, France.
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Kang SL, Hwang YN, Kwon JY, Kim SM. Effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (T1D): systematic review and meta-analysis. Diabetol Metab Syndr 2022; 14:187. [PMID: 36494830 PMCID: PMC9733359 DOI: 10.1186/s13098-022-00962-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 12/02/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The purpose of this study was to assess the effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes. METHODS We searched PubMed, EMBASE, Cochrane Central, and the Web of Science to December 2021. The eligibility criteria for study selection were randomized controlled trials comparing artificial pancreas systems (MPC, PID, and fuzzy algorithms) with conventional insulin therapy in type 1 diabetes patients. The heterogeneity of the overall results was identified by subgroup analysis of two factors including the intervention duration (overnight and 24 h) and the follow-up periods (< 1 week, 1 week to 1 month, and > 1 month). RESULTS The meta-analysis included a total of 41 studies. Considering the effect on the percentage of time maintained in the target range between the MPC-based artificial pancreas and conventional insulin therapy, the results showed a statistically significantly higher percentage of time maintained in the target range in overnight use (10.03%, 95% CI [7.50, 12.56] p < 0.00001). When the follow-up period was considered, in overnight use, the MPC-based algorithm showed a statistically significantly lower percentage of time maintained in the hypoglycemic range (-1.34%, 95% CI [-1.87, -0.81] p < 0.00001) over a long period of use (> 1 month). CONCLUSIONS Overnight use of the MPC-based artificial pancreas system statistically significantly improved glucose control while increasing time maintained in the target range for outpatients with type 1 diabetes. Results of subgroup analysis revealed that MPC algorithm-based artificial pancreas system was safe while reducing the time maintained in the hypoglycemic range after an overnight intervention with a long follow-up period (more than 1 month).
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Affiliation(s)
- Su Lim Kang
- Department of Medical Device and Healthcare, Dongguk University-Seoul, 26, Pil-Dong 3-Ga, Seoul, Jung-Gu 04620 Republic of Korea
| | - Yoo Na Hwang
- Department of Medical Device and Healthcare, Dongguk University-Seoul, 26, Pil-Dong 3-Ga, Seoul, Jung-Gu 04620 Republic of Korea
| | - Ji Yean Kwon
- Department of Medical Device and Healthcare, Dongguk University-Seoul, 26, Pil-Dong 3-Ga, Seoul, Jung-Gu 04620 Republic of Korea
| | - Sung Min Kim
- Department of Medical Device and Healthcare, Dongguk University-Seoul, 26, Pil-Dong 3-Ga, Seoul, Jung-Gu 04620 Republic of Korea
- Department of Medical Device Regulatory Science, Dongguk University-Seoul, 26, Pil-dong 3-Ga, Seoul, Jung-Gu 04620 Republic of Korea
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5
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Rodríguez-Sarmiento DL, León-Vargas F, García-Jaramillo M. Artificial pancreas systems: experiences from concept to commercialisation. Expert Rev Med Devices 2022; 19:877-894. [DOI: 10.1080/17434440.2022.2150546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Abstract
Combining technologies including rapid insulin analogs, insulin pumps, continuous glucose monitors, and control algorithms has allowed for the creation of automated insulin delivery (AID) systems. These systems have proven to be the most effective technology for optimizing metabolic control and could hold the key to broadly achieving goal-level glycemic control for people with type 1 diabetes. The use of AID has exploded in the past several years with several options available in the United States and even more in Europe. In this article, we review the largest studies involving these AID systems, and then examine future directions for AID with an emphasis on usability.
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Affiliation(s)
- Gregory P. Forlenza
- School of Medicine, Barbara Davis Center, University of Colorado Anschutz Campus, Aurora, Colorado, USA
| | - Rayhan A. Lal
- Department of Medicine & Pediatrics, Divisions of Endocrinology Stanford Diabetes Research Center, Stanford University, Stanford, California, USA
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7
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Fang Z, Liu M, Tao J, Li C, Zou F, Zhang W. Efficacy and safety of closed-loop insulin delivery versus sensor-augmented pump in the treatment of adults with type 1 diabetes: a systematic review and meta-analysis of randomized-controlled trials. J Endocrinol Invest 2022; 45:471-481. [PMID: 34535888 DOI: 10.1007/s40618-021-01674-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 09/02/2021] [Indexed: 12/21/2022]
Abstract
BACKGROUND Controversy remains regarding whether closed-loop (CL) insulin delivery or insulin sensor-augmented pump (SAP) delivery is more efficient for clinical treatment. Therefore, we aimed to compare the efficacy and safety of CL insulin delivery systems versus insulin SAP delivery for adults with type 1 diabetes (T1D). METHODS Embase, Ovid MEDLINE, PubMed, ScienceDirect, Scopus, the Cochrane Library, and other databases were searched for related articles, and we analyzed the average blood glucose (BG), time in range (TIR), and adverse effects (AEs) as primary endpoints to evaluate efficacy and safety. RESULTS Of 1616 articles, 12 randomized-controlled trials (RCTs) were included in the final analysis. Regarding BG control efficacy, CL insulin delivery resulted better outcomes than SAP therapy with regard to the average BG value, which was detected and recorded by continuous glucose monitoring (mean difference [MD][mmol/L]: - 0.25 95% confidence interval [CI] - 0.42 to - 0.08, p = 0.003); TIR 3.9-10 mmol/L (MD [%]: 7.91 95% CI 4.45-11.37, p < 0.00001). Similar results were observed for the secondary outcomes including low blood glucose index (LBGI) (MD: - 0.41 95% CI - 0.55 to - 0.26, p < 0.00001), high blood glucose index (HBGI) (MD: - 2.56 95% CI - 3.38 to - 1.74, p < 0.00001), and standard deviation (SD) of glucose variability (MD [mmol/L]: -0.25 95% CI - 0.44 to - 0.06, p = 0.01). Furthermore, SAP therapy was associated with more adverse effects (risk ratio: 0.20 95% CI 0.07-0.52, p = 0.001) than CL insulin delivery, and one of the most common adverse effects was hypoglycemia. CONCLUSIONS CL insulin delivery appears to be a better treatment method than SAP therapy for adults with T1D because of its increased BG control efficacy and decreased number of hypoglycemic events.
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Affiliation(s)
- Z Fang
- Department of Thoracic Surgery, The Second Affiliated Hospital of Nanchang University, 1 Minde Road, Nanchang, 330006, China
- Jiangxi Medical College, Nanchang University, Nanchang, 330006, China
| | - M Liu
- Jiangxi Medical College, Nanchang University, Nanchang, 330006, China
- Department of Endocrinology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, China
| | - J Tao
- Jiangxi Medical College, Nanchang University, Nanchang, 330006, China
- Department of Endocrinology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, China
| | - C Li
- Jiangxi Medical College, Nanchang University, Nanchang, 330006, China
- Department of Endocrinology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, China
| | - F Zou
- Department of Endocrinology, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, China
| | - W Zhang
- Department of Thoracic Surgery, The Second Affiliated Hospital of Nanchang University, 1 Minde Road, Nanchang, 330006, China.
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8
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Morrison D, Zaharieva DP, Lee MH, Paldus B, Vogrin S, Grosman B, Roy A, Kurtz N, O'Neal DN. Comparable Glucose Control with Fast-Acting Insulin Aspart Versus Insulin Aspart Using a Second-Generation Hybrid Closed-Loop System During Exercise. Diabetes Technol Ther 2022; 24:93-101. [PMID: 34524022 DOI: 10.1089/dia.2021.0221] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
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.
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Affiliation(s)
- Dale Morrison
- Department of Medicine, University of Melbourne, Melbourne, Australia
| | - Dessi P Zaharieva
- Division of Endocrinology, Department of Pediatrics, School of Medicine, Stanford University, Stanford, California, USA
| | - Melissa H Lee
- Department of Medicine, University of Melbourne, Melbourne, Australia
- Department of Endocrinology and Diabetes, St Vincent's Hospital Melbourne, Melbourne, Australia
| | - Barbora Paldus
- Department of Medicine, University of Melbourne, Melbourne, Australia
- Department of Endocrinology and Diabetes, St Vincent's Hospital Melbourne, Melbourne, Australia
| | - Sara Vogrin
- Department of Medicine, University of Melbourne, Melbourne, Australia
| | | | - Anirban Roy
- Medtronic Diabetes, Northridge, California, USA
| | | | - David Norman O'Neal
- Department of Medicine, University of Melbourne, Melbourne, Australia
- Department of Endocrinology and Diabetes, St Vincent's Hospital Melbourne, Melbourne, Australia
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Moon SJ, Jung I, Park CY. Current Advances of Artificial Pancreas Systems: A Comprehensive Review of the Clinical Evidence. Diabetes Metab J 2021; 45:813-839. [PMID: 34847641 PMCID: PMC8640161 DOI: 10.4093/dmj.2021.0177] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 10/24/2021] [Indexed: 12/19/2022] Open
Abstract
Since Banting and Best isolated insulin in the 1920s, dramatic progress has been made in the treatment of type 1 diabetes mellitus (T1DM). However, dose titration and timely injection to maintain optimal glycemic control are often challenging for T1DM patients and their families because they require frequent blood glucose checks. In recent years, technological advances in insulin pumps and continuous glucose monitoring systems have created paradigm shifts in T1DM care that are being extended to develop artificial pancreas systems (APSs). Numerous studies that demonstrate the superiority of glycemic control offered by APSs over those offered by conventional treatment are still being published, and rapid commercialization and use in actual practice have already begun. Given this rapid development, keeping up with the latest knowledge in an organized way is confusing for both patients and medical staff. Herein, we explore the history, clinical evidence, and current state of APSs, focusing on various development groups and the commercialization status. We also discuss APS development in groups outside the usual T1DM patients and the administration of adjunct agents, such as amylin analogues, in APSs.
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Affiliation(s)
- Sun Joon Moon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Inha Jung
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Cheol-Young Park
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
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10
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Kulawiec DG, Zhou T, Knopp JL, Chase JG. Continuous glucose monitoring to measure metabolic impact and recovery in sub-elite endurance athletes. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.103059] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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Mosquera-Lopez C, Dodier R, Tyler NS, Wilson LM, El Youssef J, Castle JR, Jacobs PG. Predicting and Preventing Nocturnal Hypoglycemia in Type 1 Diabetes Using Big Data Analytics and Decision Theoretic Analysis. Diabetes Technol Ther 2020; 22:801-811. [PMID: 32297795 PMCID: PMC7698985 DOI: 10.1089/dia.2019.0458] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Background: Despite new glucose sensing technologies, nocturnal hypoglycemia is still a problem for people with type 1 diabetes (T1D) as symptoms and sensor alarms may not be detected while sleeping. Accurately predicting nocturnal hypoglycemia before sleep may help minimize nighttime hypoglycemia. Methods: A support vector regression (SVR) model was trained to predict, before bedtime, the overnight minimum glucose and overnight nocturnal hypoglycemia for people with T1D. The algorithm was trained on continuous glucose measurements and insulin data collected from 124 people (22,804 valid nights of data) with T1D. The minimum glucose threshold for announcing nocturnal hypoglycemia risk was derived by applying a decision theoretic criterion to maximize expected net benefit. Accuracy was evaluated on a validation set from 10 people with T1D during a 4-week trial under free-living sensor-augmented insulin-pump therapy. The primary outcome measures were sensitivity and specificity of prediction, the correlation between predicted and actual minimum nocturnal glucose, and root-mean-square error. The impact of using the algorithm to prevent nocturnal hypoglycemia is shown in-silico. Results: The algorithm predicted 94.1% of nocturnal hypoglycemia events (<3.9 mmol/L, 95% confidence interval [CI], 71.3-99.9) with an area under the receiver operating characteristic curve of 0.86 (95% CI, 0.75-0.98). Correlation between actual and predicted minimum glucose was high (R = 0.71, P < 0.001). In-silico simulations showed that the algorithm could reduce nocturnal hypoglycemia by 77.0% (P = 0.006) without impacting time in target range (3.9-10 mmol/L). Conclusion: An SVR model trained on a big data set and optimized using decision theoretic criterion can accurately predict at bedtime if overnight nocturnal hypoglycemia will occur and may help reduce nocturnal hypoglycemia.
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Affiliation(s)
- Clara Mosquera-Lopez
- Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, USA
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, Oregon, USA
- Clara Mosquera-Lopez, PhD, Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, 3303 SW Bond Avenue, Portland, OR 97239, USA
| | - Robert Dodier
- Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, USA
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, Oregon, USA
| | - Nichole S. Tyler
- Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, USA
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, Oregon, USA
| | - Leah M. Wilson
- Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, USA
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, Oregon, USA
| | - Joseph El Youssef
- Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, USA
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, Oregon, USA
| | - Jessica R. Castle
- Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, USA
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, Oregon, USA
| | - Peter G. Jacobs
- Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, USA
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, Oregon, USA
- Address correspondence to: Peter G. Jacobs, PhD, Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, 3303 SW Bond Avenue, Portland, OR 97239, USA
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12
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Measuring glucose at the site of insulin delivery with a redox-mediated sensor. Biosens Bioelectron 2020; 165:112221. [PMID: 32729464 DOI: 10.1016/j.bios.2020.112221] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Revised: 04/14/2020] [Accepted: 04/15/2020] [Indexed: 11/22/2022]
Abstract
Automated insulin delivery systems for people with type 1 diabetes rely on an accurate subcutaneous glucose sensor and an infusion cannula that delivers insulin in response to measured glucose. Integrating the sensor with the infusion cannula would provide substantial benefit by reducing the number of devices inserted into subcutaneous tissue. We describe the sensor chemistry and a calibration algorithm to minimize impact of insulin delivery artifacts in a new glucose sensing cannula. Seven people with type 1 diabetes undergoing automated insulin delivery used two sensing cannulae whereby one delivered a rapidly-acting insulin analog and the other delivered a control phosphate buffered saline (PBS) solution with no insulin. While there was a small artifact in both conditions that increased for larger volumes, there was no difference between the artifacts in the sensing cannula delivering insulin compared with the sensing cannula delivering PBS as determined by integrating the area-under-the-curve of the sensor values following delivery of larger amounts of fluid (P = 0.7). The time for the sensor to recover from the artifact was found to be longer for larger fluid amounts compared with smaller fluid amounts (10.3 ± 8.5 min vs. 41.2 ± 78.3 s, P < 0.05). Using a smart-sampling Kalman filtering smoothing algorithm improved sensor accuracy. When using an all-point calibration on all sensors, the smart-sampling Kalman filter reduced the mean absolute relative difference from 10.9% to 9.5% and resulted in 96.7% of the data points falling within the A and B regions of the Clarke error grid. Despite a small artifact, which is likely due to dilution by fluid delivery, it is possible to continuously measure glucose in a cannula that simultaneously delivers insulin.
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13
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Maahs DM, Shalitin S. Diabetes Technology and Therapy in the Pediatric Age Group. Diabetes Technol Ther 2020; 22:S89-S108. [PMID: 32069148 DOI: 10.1089/dia.2020.2507] [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)
- David M Maahs
- Department of Pediatrics, Division of Endocrinology and Diabetes, Stanford University, Stanford, CA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA
- Department of Health Research and Policy (Epidemiology), Stanford University, Stanford, CA
| | - Shlomit Shalitin
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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Collard SS, Regmi PR, Hood KK, Laffel L, Weissberg‐Benchell J, Naranjo D, Barnard‐Kelly K. Exercising with an automated insulin delivery system: qualitative insight into the hopes and expectations of people with type 1 diabetes. PRACTICAL DIABETES 2020. [DOI: 10.1002/pdi.2255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Affiliation(s)
- Sarah S Collard
- Faculty of Health and Social SciencesBournemouth University Bournemouth UK
| | - Pramod R Regmi
- Faculty of Health and Social SciencesBournemouth University Bournemouth UK
| | - Korey K Hood
- Department of Pediatrics, Psychiatry, and Behavioral SciencesStanford University School of Medicine Stanford California USA
| | - Lori Laffel
- Joslin Diabetes CenterHarvard Medical School Boston Massachusetts USA
| | - Jill Weissberg‐Benchell
- Department of Psychiatry and Behavioral Sciences, Ann & Robert H Lurie Children's Hospital of ChicagoNorthwestern University Feinberg School of Medicine Chicago Illinois USA
| | - Diana Naranjo
- Department of Pediatrics, Psychiatry, and Behavioral SciencesStanford University School of Medicine Stanford California USA
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Sakr MA, Elgammal K, Delin A, Serry M. Performance-Enhanced Non-Enzymatic Glucose Sensor Based on Graphene-Heterostructure. SENSORS (BASEL, SWITZERLAND) 2019; 20:E145. [PMID: 31878328 PMCID: PMC6982948 DOI: 10.3390/s20010145] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 12/16/2019] [Accepted: 12/20/2019] [Indexed: 12/14/2022]
Abstract
Non-enzymatic glucose sensing is a crucial field of study because of the current market demand. This study proposes a novel design of glucose sensor with enhanced selectivity and sensitivity by using graphene Schottky diodes, which is composed of graphene (G)/platinum oxide (PtO)/n-silicon (Si) heterostructure. The sensor was tested with different glucose concentrations and interfering solutions to investigate its sensitivity and selectivity. Different structures of the device were studied by adjusting the platinum oxide film thickness to investigate its catalytic activity. It was found that the film thickness plays a significant role in the efficiency of glucose oxidation and hence in overall device sensitivity. 0.8-2 μA output current was obtained in the case of 4-10 mM with a sensitivity of 0.2 A/mM.cm2. Besides, results have shown that 0.8 A and 15 A were obtained by testing 4 mM glucose on two different PtO thicknesses, 30 nm and 50 nm, respectively. The sensitivity of the device was enhanced by 150% (i.e., up to 30 A/mM.cm2) by increasing the PtO layer thickness. This was attributed to both the increase of the number of active sites for glucose oxidation as well as the increase in the graphene layer thickness, which leads to enhanced charge carriers concentration and mobility. Moreover, theoretical investigations were conducted using the density function theory (DFT) to understand the detection method and the origins of selectivity better. The working principle of the sensors puts it in a competitive position with other non-enzymatic glucose sensors. DFT calculations provided a qualitative explanation of the charge distribution across the graphene sheet within a system of a platinum substrate with D-glucose molecules above. The proposed G/PtO/n-Si heterostructure has proven to satisfy these factors, which opens the door for further developments of more reliable non-enzymatic glucometers for continuous glucose monitoring systems.
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Affiliation(s)
- Mahmoud A. Sakr
- Graduate Program in Nanotechnology, The American University in Cairo (AUC), New Cairo 11835, Egypt;
- Department of Mechanical Engineering, The American University in Cairo (AUC), New Cairo 11835, Egypt
| | - Karim Elgammal
- Department of Applied Physics, School of Engineering Sciences, KTH Royal Institute of Technology, Electrum 229, SE-16440 Kista, Sweden; (K.E.); (A.D.)
- Swedish e-Science Research Center (SeRC), KTH Royal Institute of Technology, SE-10044 Stockholm, Sweden
| | - Anna Delin
- Department of Applied Physics, School of Engineering Sciences, KTH Royal Institute of Technology, Electrum 229, SE-16440 Kista, Sweden; (K.E.); (A.D.)
- Swedish e-Science Research Center (SeRC), KTH Royal Institute of Technology, SE-10044 Stockholm, Sweden
- Department of Physics and Astronomy, Materials Theory Division, Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | - Mohamed Serry
- Department of Mechanical Engineering, The American University in Cairo (AUC), New Cairo 11835, Egypt
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Lal RA, Ekhlaspour L, Hood K, Buckingham B. Realizing a Closed-Loop (Artificial Pancreas) System for the Treatment of Type 1 Diabetes. Endocr Rev 2019; 40:1521-1546. [PMID: 31276160 PMCID: PMC6821212 DOI: 10.1210/er.2018-00174] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 02/28/2019] [Indexed: 01/20/2023]
Abstract
Recent, rapid changes in the treatment of type 1 diabetes have allowed for commercialization of an "artificial pancreas" that is better described as a closed-loop controller of insulin delivery. This review presents the current state of closed-loop control systems and expected future developments with a discussion of the human factor issues in allowing automation of glucose control. The goal of these systems is to minimize or prevent both short-term and long-term complications from diabetes and to decrease the daily burden of managing diabetes. The closed-loop systems are generally very effective and safe at night, have allowed for improved sleep, and have decreased the burden of diabetes management overnight. However, there are still significant barriers to achieving excellent daytime glucose control while simultaneously decreasing the burden of daytime diabetes management. These systems use a subcutaneous continuous glucose sensor, an algorithm that accounts for the current glucose and rate of change of the glucose, and the amount of insulin that has already been delivered to safely deliver insulin to control hyperglycemia, while minimizing the risk of hypoglycemia. The future challenge will be to allow for full closed-loop control with minimal burden on the patient during the day, alleviating meal announcements, carbohydrate counting, alerts, and maintenance. The human factors involved with interfacing with a closed-loop system and allowing the system to take control of diabetes management are significant. It is important to find a balance between enthusiasm and realistic expectations and experiences with the closed-loop system.
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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
| | - Laya Ekhlaspour
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
| | - Korey Hood
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California.,Department of Psychiatry, Stanford University School of Medicine, Stanford, California
| | - Bruce Buckingham
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
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17
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Kovatchev B. Diabetes Technology: Monitoring, Analytics, and Optimal Control. Cold Spring Harb Perspect Med 2019; 9:cshperspect.a034389. [PMID: 30126835 DOI: 10.1101/cshperspect.a034389] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Over the past 50 years, the diabetes technology field progressed remarkably through self-monitoring of blood glucose (SMBG), continuous subcutaneous insulin infusion (CSII), risk and variability analysis, mathematical models and computer simulation of the human metabolic system, real-time continuous glucose monitoring (CGM), and control algorithms driving closed-loop control systems known as the "artificial pancreas" (AP). This review follows these developments, beginning with an overview of the functioning of the human metabolic system in health and in diabetes and of its detailed quantitative network modeling. The review continues with a brief account of the first AP studies that used intravenous glucose monitoring and insulin infusion, and with notes about CSII and CGM-the technologies that made possible the development of contemporary AP systems. In conclusion, engineering lessons learned from AP research, and the clinical need for AP systems to prove their safety and efficacy in large-scale clinical trials, are outlined.
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Affiliation(s)
- Boris Kovatchev
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia 22908
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18
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Musolino G, Allen JM, Hartnell S, Wilinska ME, Tauschmann M, Boughton C, Campbell F, Denvir L, Trevelyan N, Wadwa P, DiMeglio L, Buckingham BA, Weinzimer S, Acerini CL, Hood K, Fox S, Kollman C, Sibayan J, Borgman S, Cheng P, Hovorka R. Assessing the efficacy, safety and utility of 6-month day-and-night automated closed-loop insulin delivery under free-living conditions compared with insulin pump therapy in children and adolescents with type 1 diabetes: an open-label, multicentre, multinational, single-period, randomised, parallel group study protocol. BMJ Open 2019; 9:e027856. [PMID: 31164368 PMCID: PMC6561428 DOI: 10.1136/bmjopen-2018-027856] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
INTRODUCTION Closed-loop systems titrate insulin based on sensor glucose levels, providing novel means to reduce the risk of hypoglycaemia while improving glycaemic control. We will assess effectiveness of 6-month day-and-night closed-loop insulin delivery compared with usual care (conventional or sensor-augmented pump therapy) in children and adolescents with type 1 diabetes. METHODS AND ANALYSIS The trial adopts an open-label, multicentre, multinational (UK and USA), randomised, single-period, parallel design. Participants (n=130) are children and adolescents (aged ≥6 and <19 years) with type 1 diabetes for at least 1 year, and insulin pump use for at least 3 months with suboptimal glycaemic control (glycated haemoglobin ≥58 mmol/mol (7.5%) and ≤86 mmol/mol (10%)). After a 2-3 week run-in period, participants will be randomised to 6-month use of hybrid closed-loop insulin delivery, or to usual care. Analyses will be conducted on an intention-to-treat basis. The primary outcome is glycated haemoglobin at 6 months. Other key endpoints include time in the target glucose range (3.9-10 mmol/L, 70-180 mg/dL), mean sensor glucose and time spent above and below target. Secondary outcomes include SD and coefficient of variation of sensor glucose levels, time with sensor glucose levels <3.5 mmol/L (63 mg/dL) and <3.0 mmol/L (54 mg/dL), area under the curve of glucose <3.5 mmol/L (63 mg/dL), time with glucose levels >16.7 mmol/L (300 mg/dL), area under the curve of glucose >10.0 mmol/L (180 mg/dL), total, basal and bolus insulin dose, body mass index z-score and blood pressure. Cognitive, emotional and behavioural characteristics of participants and caregivers and their responses to the closed-loop and clinical trial will be assessed. An incremental cost-effectiveness ratio for closed-loop will be estimated. ETHICS AND DISSEMINATION Cambridge South Research Ethics Committee and Jaeb Center for Health Research Institutional Review Office approved the study. The findings will be disseminated by peer-review publications and conference presentations. TRIAL REGISTRATION NUMBER NCT02925299; Pre-results.
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Affiliation(s)
- Gianluca Musolino
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Janet M Allen
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Sara Hartnell
- Department of Diabetes and Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Malgorzata E Wilinska
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Martin Tauschmann
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Charlotte Boughton
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Fiona Campbell
- Department of Paediatric Diabetes, Leeds Children’s Hospital, Leeds, UK
| | - Louise Denvir
- Department of Paediatric Diabetes and Endocrinology, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Nicola Trevelyan
- Department of Paediatric Endocrinology and Diabetes, Southampton Children’s Hospital, Southampton General Hospital, Southampton, UK
| | - Paul Wadwa
- Barbara Davis Center for Childhood Diabetes, University of Colorado, Aurora, Colorado, USA
| | - Linda DiMeglio
- Department of Pediatrics, Division of Pediatric Endocrinology and Diabetology, Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Bruce A Buckingham
- Division of Pediatric Endocrinology, Stanford University, Stanford, California, USA
| | - Stuart Weinzimer
- Department of Pediatrics, Yale University, New Haven, Connecticut, USA
| | - Carlo L Acerini
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Korey Hood
- Division of Pediatric Endocrinology, Stanford University, Stanford, California, USA
| | - Steven Fox
- Department of Pharmaceutical and Health Economics, School of Pharmacy, University of Southern California, Los Angeles, California, USA
| | - Craig Kollman
- Jaeb Center for Health Research, Tampa, Florida, USA
| | - Judy Sibayan
- Jaeb Center for Health Research, Tampa, Florida, USA
| | - Sarah Borgman
- Jaeb Center for Health Research, Tampa, Florida, USA
| | - Peiyao Cheng
- Jaeb Center for Health Research, Tampa, Florida, USA
| | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
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19
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Anderson SM, Buckingham BA, Breton MD, Robic JL, Barnett CL, Wakeman CA, Oliveri MC, Brown SA, Ly TT, Clinton PK, Hsu LJ, Kingman RS, Norlander LM, Loebner SE, Reuschel-DiVirglio S, Kovatchev BP. Hybrid Closed-Loop Control Is Safe and Effective for People with Type 1 Diabetes Who Are at Moderate to High Risk for Hypoglycemia. Diabetes Technol Ther 2019; 21:356-363. [PMID: 31095423 PMCID: PMC6551970 DOI: 10.1089/dia.2019.0018] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Background: Typically, closed-loop control (CLC) studies excluded patients with significant hypoglycemia. We evaluated the effectiveness of hybrid CLC (HCLC) versus sensor-augmented pump (SAP) in reducing hypoglycemia in this high-risk population. Methods: Forty-four subjects with type 1 diabetes, 25 women, 37 ± 2 years old, HbA1c 7.4% ± 0.2% (57 ± 1.5 mmol/mol), diabetes duration 19 ± 2 years, on insulin pump, were enrolled at the University of Virginia (N = 33) and Stanford University (N = 11). Eligibility: increased risk of hypoglycemia confirmed by 1 week of blinded continuous glucose monitor (CGM); randomized to 4 weeks of home use of either HCLC or SAP. Primary/secondary outcomes: risk for hypoglycemia measured by the low blood glucose index (LBGI)/CGM-based time in ranges. Results: Values reported: mean ± standard deviation. From baseline to the final week of study: LBGI decreased more on HCLC (2.51 ± 1.17 to 1.28 ± 0.5) than on SAP (2.1 ± 1.05 to 1.79 ± 0.98), P < 0.001; percent time below 70 mg/dL (3.9 mmol/L) decreased on HCLC (7.2% ± 5.3% to 2.0% ± 1.4%) but not on SAP (5.8% ± 4.7% to 4.8% ± 4.5%), P = 0.001; percent time within the target range 70-180 mg/dL (3.9-10 mmol/L) increased on HCLC (67.8% ± 13.5% to 78.2% ± 10%) but decreased on SAP (65.6% ± 12.9% to 59.6% ± 16.5%), P < 0.001; percent time above 180 mg/dL (10 mmol/L) decreased on HCLC (25.1% ± 15.3% to 19.8% ± 10.1%) but increased on SAP (28.6% ± 14.6% to 35.6% ± 17.6%), P = 0.009. Mean glucose did not change significantly on HCLC (144.9 ± 27.9 to 143.8 ± 14.4 mg/dL [8.1 ± 1.6 to 8.0 ± 0.8 mmol/L]) or SAP (152.5 ± 24.3 to 162.4 ± 28.2 [8.5 ± 1.4 to 9.0 ± 1.6]), P = ns. Conclusions: Compared with SAP therapy, HCLC reduced the risk and frequency of hypoglycemia, while improving time in target range and reducing hyperglycemia in people at moderate to high risk of hypoglycemia.
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Affiliation(s)
- Stacey M. Anderson
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
- Address correspondence to: Stacey M. Anderson, MD, Center for Diabetes Technology, University of Virginia, PO Box 400888, Charlottesville VA 22908-4888
| | - Bruce A. Buckingham
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
| | - Marc D. Breton
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Jessica L. Robic
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | | | | | - Mary C. Oliveri
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Sue A. Brown
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Trang T. Ly
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
| | - Paula K. Clinton
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
| | - Liana J. Hsu
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
| | - Ryan S. Kingman
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
| | - Lisa M. Norlander
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
| | - Sarah E. Loebner
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
| | - Suzette Reuschel-DiVirglio
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
| | - Boris P. Kovatchev
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
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20
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Weissberg‐Benchell J, Shapiro JB, Hood K, Laffel LM, Naranjo D, Miller K, Barnard K. Assessing patient-reported outcomes for automated insulin delivery systems: the psychometric properties of the INSPIRE measures. Diabet Med 2019; 36:644-652. [PMID: 30761592 PMCID: PMC6593869 DOI: 10.1111/dme.13930] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/12/2019] [Indexed: 12/17/2022]
Abstract
AIM Participants in clinical trials assessing automated insulin delivery systems report perceived benefits and burdens that reflect their experiences and may predict their likelihood of uptake and continued use of this novel technology. Despite the importance of understanding their perspectives, there are no available validated and reliable measures assessing the psychosocial aspects of automated insulin delivery systems. The present study assesses the initial psychometric properties of the INSPIRE measures, which were developed for youth and adults with Type 1 diabetes, as well as parents and partners. METHODS Data from 292 youth, 159 adults, 150 parents of youth and 149 partners of individuals recruited from the Type 1 Diabetes Exchange Registry were analysed. Participants completed INSPIRE questionnaires and measures of quality of life, fear of hypoglycaemia, diabetes distress, glucose monitoring satisfaction. Exploratory factor analysis assessed factor structures. Associations between INSPIRE scores and other measures, HbA1c , and technology use assessed concurrent and discriminant validity. RESULTS Youth, adult, parent and partner measures assess positive expectancies of automated insulin delivery systems. Measures range from 17 to 22 items and are reliable (α = 0.95-0.97). Youth, adult and parent measures are unidimensional; the partner measure has a two-factor structure (perceptions of impact on partners versus the person with diabetes). Measures showed concurrent and discriminant validity. CONCLUSIONS INSPIRE measures assessing the positive expectancies of automated insulin delivery systems for youth, adults, parents and partners have meaningful factor structures and are internally consistent. The developmentally sensitive INSPIRE measures offer added value as clinical trials test newer systems, systems become commercially available and clinicians initiate using these systems.
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Affiliation(s)
- J. Weissberg‐Benchell
- Department of Psychiatry and Behavioral SciencesAnn and Robert H., Lurie Children's Hospital of ChicagoNorthwestern UniversityFeinberg School of MedicineChicagoIL
| | | | - K. Hood
- Departments of PediatricsPsychiatry& Behavioral Sciences, Stanford University School of MedicineStanfordCA
| | - L. M. Laffel
- Joslin Diabetes CenterHarvard Medical SchoolBostonMA
| | - D. Naranjo
- Departments of PediatricsPsychiatry& Behavioral Sciences, Stanford University School of MedicineStanfordCA
| | - K. Miller
- Jaeb Center for Health ResearchTampaFloridaUSA
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Biester T, Nir J, Remus K, Farfel A, Muller I, Biester S, Atlas E, Dovc K, Bratina N, Kordonouri O, Battelino T, Philip M, Danne T, Nimri R. DREAM5: An open-label, randomized, cross-over study to evaluate the safety and efficacy of day and night closed-loop control by comparing the MD-Logic automated insulin delivery system to sensor augmented pump therapy in patients with type 1 diabetes at home. Diabetes Obes Metab 2019; 21:822-828. [PMID: 30478937 DOI: 10.1111/dom.13585] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2018] [Revised: 11/02/2018] [Accepted: 11/13/2018] [Indexed: 12/22/2022]
Abstract
AIMS Previous DREAM studies demonstrated the safety and efficacy of the CE marked MD-Logic closed-loop system (DreaMed GlucoSitter) in different settings for overnight glycaemic control. The present study aimed to evaluate the system for day and night use for 60 hours during the weekend at home compared to sensor-augmented pump (SAP) therapy in participants with type 1 diabetes. METHODS This was a prospective, multicentre, crossover, controlled study (clinicaltrials.gov NCT01238406). All participants were connected in randomized order for one weekend to SAP therapy or the MD-Logic System. In the intervention arm only, the amount of carbohydrate was entered into the bolus calculator; the rest of insulin delivery was automated and wireless via a tablet computer. The primary endpoint was percentage of glucose values between 70 and 180 mg/dL. RESULTS The ITT population comprised 48 (19 males, 29 females) adolescents and adults experienced in sensor use: (median, [IQR]): age, 16.1years [13.2-18.5]; diabetes duration, 9.4 years [5.0-12.7]; pump use, 5.4 years [3.1-9.4]; HbA1c, 7.6% [7.0-8.1]. A significant increase in the percentage of time within target range (70-180 mg/dL) (66.6% vs 59.9%, P = 0.002) was observed with the closed-loop system vs control weekends with unchanged percentage of time below 70 mg/dL (2.3% vs 1.5%, P = 0.369). Mean weekend glucose level per participant was significantly lower (153 [142-175] vs 164 [150-186] mg/dL, P = 0.003). No safety signals were observed. CONCLUSIONS The MD-Logic system was safe and associated with better glycaemic control than SAP therapy for day and night use. The absence of remote monitoring did not lead to safety signals in adapting basal rates nor in administration of automated bolus corrections.
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Affiliation(s)
- Torben Biester
- Children's Hospital "Auf der Bult," Diabetes-Center for Children and Adolescents, Hannover, Germany
| | - Judith Nir
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikvah, Israel
| | - Kerstin Remus
- Children's Hospital "Auf der Bult," Diabetes-Center for Children and Adolescents, Hannover, Germany
| | - Alon Farfel
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikvah, Israel
| | - Ido Muller
- DreaMed Diabetes Ltd, Petah Tikvah, Israel
| | - Sarah Biester
- Children's Hospital "Auf der Bult," Diabetes-Center for Children and Adolescents, Hannover, Germany
| | - Eran Atlas
- DreaMed Diabetes Ltd, Petah Tikvah, Israel
| | - Klemen Dovc
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, University Children's Hospital, UMC Ljubljana, Ljubljana, Slovenia
| | - Nataša Bratina
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, University Children's Hospital, UMC Ljubljana, Ljubljana, Slovenia
| | - Olga Kordonouri
- Children's Hospital "Auf der Bult," Diabetes-Center for Children and Adolescents, Hannover, Germany
| | - Tadej Battelino
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, University Children's Hospital, UMC Ljubljana, Ljubljana, Slovenia
| | - Moshe Philip
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikvah, Israel
| | - Thomas Danne
- Children's Hospital "Auf der Bult," Diabetes-Center for Children and Adolescents, Hannover, Germany
| | - Revital Nimri
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikvah, Israel
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22
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Messori M, Toffanin C, Del Favero S, De Nicolao G, Cobelli C, Magni L. Model individualization for artificial pancreas. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2019; 171:133-140. [PMID: 27424482 DOI: 10.1016/j.cmpb.2016.06.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2015] [Revised: 05/13/2016] [Accepted: 06/28/2016] [Indexed: 05/23/2023]
Abstract
BACKGROUND AND OBJECTIVE The inter-subject variability characterizing the patients affected by type 1 diabetes mellitus makes automatic blood glucose control very challenging. Different patients have different insulin responses, and a control law based on a non-individualized model could be ineffective. The definition of an individualized control law in the context of artificial pancreas is currently an open research topic. In this work we consider two novel identification approaches that can be used for individualizing linear glucose-insulin models to a specific patient. METHODS The first approach belongs to the class of black-box identification and is based on a novel kernel-based nonparametric approach, whereas the second is a gray-box identification technique which relies on a constrained optimization and requires to postulate a model structure as prior knowledge. The latter is derived from the linearization of the average nonlinear adult virtual patient of the UVA/Padova simulator. Model identification and validation are based on in silico data collected during simulations of clinical protocols designed to produce a sufficient signal excitation without compromising patient safety. The identified models are evaluated in terms of prediction performance by means of the coefficient of determination, fit, positive and negative max errors, and root mean square error. RESULTS Both identification approaches were used to identify a linear individualized glucose-insulin model for each adult virtual patient of the UVA/Padova simulator. The resulting model simulation performance is significantly improved with respect to the performance achieved by a linear average model. CONCLUSIONS The approaches proposed in this work have shown a good potential to identify glucose-insulin models for designing individualized control laws for artificial pancreas.
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Affiliation(s)
- Mirko Messori
- Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy.
| | - Chiara Toffanin
- Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy
| | - Simone Del Favero
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Giuseppe De Nicolao
- Department of Industrial and Information Engineering, University of Pavia, Pavia, Italy
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Lalo Magni
- Department of Civil Engineering and Architecture, University of Pavia, Pavia, Italy
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23
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Anderson SM, Dassau E, Raghinaru D, Lum J, Brown SA, Pinsker JE, Church MM, Levy C, Lam D, Kudva YC, Buckingham B, Forlenza GP, Wadwa RP, Laffel L, Doyle FJ, DeVries JH, Renard E, Cobelli C, Boscari F, Del Favero S, Kovatchev BP. The International Diabetes Closed-Loop Study: Testing Artificial Pancreas Component Interoperability. Diabetes Technol Ther 2019; 21:73-80. [PMID: 30649925 PMCID: PMC6354594 DOI: 10.1089/dia.2018.0308] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
BACKGROUND Use of artificial pancreas (AP) requires seamless interaction of device components, such as continuous glucose monitor (CGM), insulin pump, and control algorithm. Mobile AP configurations also include a smartphone as computational hub and gateway to cloud applications (e.g., remote monitoring and data review and analysis). This International Diabetes Closed-Loop study was designed to demonstrate and evaluate the operation of the inControl AP using different CGMs and pump modalities without changes to the user interface, user experience, and underlying controller. METHODS Forty-three patients with type 1 diabetes (T1D) were enrolled at 10 clinical centers (7 United States, 3 Europe) and 41 were included in the analyses (39% female, >95% non-Hispanic white, median T1D duration 16 years, median HbA1c 7.4%). Two CGMs and two insulin pumps were tested by different study participants/sites using the same system hub (a smartphone) during 2 weeks of in-home use. RESULTS The major difference between the system components was the stability of their wireless connections with the smartphone. The two sensors achieved similar rates of connectivity as measured by percentage time in closed loop (75% and 75%); however, the two pumps had markedly different closed-loop adherence (66% vs. 87%). When connected, all system configurations achieved similar glycemic outcomes on AP control (73% [mean] time in range: 70-180 mg/dL, and 1.7% [median] time <70 mg/dL). CONCLUSIONS CGMs and insulin pumps can be interchangeable in the same Mobile AP system, as long as these devices achieve certain levels of reliability and wireless connection stability.
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Affiliation(s)
- Stacey M. Anderson
- Center for Diabetes Technology, Department of Medicine, University of Virginia
- Address correspondence to: Stacey M. Anderson, MD, Center for Diabetes Technology, Department of Medicine, University of Virginia, PO Box 400888, Charlottesville, VA 22903
| | - Eyal Dassau
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
- Sansum Diabetes Research Institute, Santa Barbara, California
- Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts
| | | | - John Lum
- Jaeb Center for Health Research, Tampa, Florida
| | - Sue A. Brown
- Center for Diabetes Technology, Department of Medicine, University of Virginia
| | | | - Mei Mei Church
- Sansum Diabetes Research Institute, Santa Barbara, California
| | - Carol Levy
- Division of Endocrinology, Icahn School of Medicine at Mount Sinai, New York City, New York
| | - David Lam
- Division of Endocrinology, Icahn School of Medicine at Mount Sinai, New York City, New York
| | - Yogish C. Kudva
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Bruce Buckingham
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, California
| | - Gregory P. Forlenza
- Barbara Davis Center for Diabetes, University of Colorado, Anschutz Medical Campus, Aurora, Colorado
| | - R. Paul Wadwa
- Barbara Davis Center for Diabetes, University of Colorado, Anschutz Medical Campus, Aurora, Colorado
| | - Lori Laffel
- Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts
| | - Francis J. Doyle
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
| | - J. Hans DeVries
- Academic Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Eric Renard
- Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital, Montpellier, France
- INSERM 1411 Clinical Investigation Center, Institute of Functional Genomics, UMR CNRS 5203/INSERM U1191, University of Montpellier, Montpellier, France
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | | | - Simone Del Favero
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Boris P. Kovatchev
- Center for Diabetes Technology, Department of Medicine, University of Virginia
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Kovatchev B. Automated closed-loop control of diabetes: the artificial pancreas. Bioelectron Med 2018; 4:14. [PMID: 32232090 PMCID: PMC7098217 DOI: 10.1186/s42234-018-0015-6] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Accepted: 10/08/2018] [Indexed: 12/28/2022] Open
Abstract
The incidence of Diabetes Mellitus is on the rise worldwide, which exerts enormous health toll on the population and enormous pressure on the healthcare systems. Now, almost hundred years after the discovery of insulin in 1921, the optimization problem of diabetes is well formulated as maintenance of strict glycemic control without increasing the risk for hypoglycemia. External insulin administration is mandatory for people with type 1 diabetes; various medications, as well as basal and prandial insulin, are included in the daily treatment of type 2 diabetes. This review follows the development of the Diabetes Technology field which, since the 1970s, progressed remarkably through continuous subcutaneous insulin infusion (CSII), mathematical models and computer simulation of the human metabolic system, real-time continuous glucose monitoring (CGM), and control algorithms driving closed-loop control systems known as the "artificial pancreas" (AP). All of these developments included significant engineering advances and substantial bioelectronics progress in the sensing of blood glucose levels, insulin delivery, and control design. The key technologies that enabled contemporary AP systems are CSII and CGM, both of which became available and sufficiently portable in the beginning of this century. This powered the quest for wearable home-use AP, which is now under way with prototypes tested in outpatient studies during the past 6 years. Pivotal trials of new AP technologies are ongoing, and the first hybrid closed-loop system has been approved by the FDA for clinical use. Thus, the closed-loop AP is well on its way to become the digital-age treatment of diabetes.
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Affiliation(s)
- Boris Kovatchev
- Center for Diabetes Technology, University of Virginia, P.O. Box 400888, Charlottesville, VA 22908 USA
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Beneyto A, Vehi J. Postprandial fuzzy adaptive strategy for a hybrid proportional derivative controller for the artificial pancreas. Med Biol Eng Comput 2018; 56:1973-1986. [PMID: 29725915 DOI: 10.1007/s11517-018-1832-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Accepted: 04/19/2018] [Indexed: 11/24/2022]
Abstract
This paper presents a support fuzzy adaptive system for a hybrid proportional derivative controller that will refine its parameters during postprandial periods to enhance performance. Even though glucose controllers have improved over the last decade, tuning them and keeping them tuned are still major challenges. Changes in a patient's lifestyle, stress, exercise, or other activities may modify their blood glucose system, making it necessary to retune or change the insulin dosing algorithm. This paper presents a strategy to adjust the parameters of a proportional derivative controller using the so-called safety auxiliary feedback element loop for type 1 diabetic patients. The main parameters, such as the insulin on board limit and proportional gain are tuned using postprandial performance indexes and the information given by the controller itself. The adaptive and robust performance of the control algorithm was assessed "in silico" on a cohort of virtual patients under challenging realistic scenarios considering mixed meals, circadian variations, time-varying uncertainties, sensor errors, and other disturbances. The results showed that an adaptive strategy can significantly improve the performance of postprandial glucose control, individualizing the tuning by directly taking into account the intra-patient variability of type 1 patients. Graphical Abstract title: Postprandial glycaemia improvement via fuzzy adaptive control A fuzzy inference engine was implemented within a clinically tested artificial pancreas control system. The aim of the fuzzy system was to adapt controller parameters to improve postprandial blood glucose control while ensuring safety. Results show a significant improvement over time of the postprandial glucose response due to the adaptation, thus demonstrating the usefulness of the fuzzy adaptive system.
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Affiliation(s)
- Aleix Beneyto
- Institut d'Informàtica i Aplicacions, Universitat de Girona, Campus de Montilivi, s/n, Edifici P4, 17071, Girona, Spain
| | - Josep Vehi
- Institut d'Informàtica i Aplicacions, Universitat de Girona, Campus de Montilivi, s/n, Edifici P4, 17071, Girona, Spain. .,CIBERDEM, Girona, Spain.
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Sherr JL, Tauschmann M, Battelino T, de Bock M, Forlenza G, Roman R, Hood KK, Maahs DM. ISPAD Clinical Practice Consensus Guidelines 2018: Diabetes technologies. Pediatr Diabetes 2018; 19 Suppl 27:302-325. [PMID: 30039513 DOI: 10.1111/pedi.12731] [Citation(s) in RCA: 128] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2018] [Accepted: 07/10/2018] [Indexed: 12/12/2022] Open
Affiliation(s)
- Jennifer L Sherr
- Department of Pediatrics, Yale School of Medicine, Yale University, New Haven, Connecticut
| | - Martin Tauschmann
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK.,Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Tadej Battelino
- UMC-University Children's Hospital, Ljubljana, Slovenia.,Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Martin de Bock
- Department of Paediatrics, University of Otago, Christchurch, New Zealand
| | - Gregory Forlenza
- University of Colorado Denver, Barbara Davis Center, Aurora, Colorado
| | - Rossana Roman
- Medical Sciences Department, University of Antofagasta and Antofagasta Regional Hospital, Antofagasta, Chile
| | - Korey K Hood
- Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Palo Alto, California
| | - David M Maahs
- Department of Pediatrics, Stanford University School of Medicine, Palo Alto, California
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Sánchez-Peña R, Colmegna P, Garelli F, De Battista H, García-Violini D, Moscoso-Vásquez M, Rosales N, Fushimi E, Campos-Náñez E, Breton M, Beruto V, Scibona P, Rodriguez C, Giunta J, Simonovich V, Belloso WH, Cherñavvsky D, Grosembacher L. Artificial Pancreas: Clinical Study in Latin America Without Premeal Insulin Boluses. J Diabetes Sci Technol 2018; 12:914-925. [PMID: 29998754 PMCID: PMC6134619 DOI: 10.1177/1932296818786488] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND Emerging therapies such as closed-loop (CL) glucose control, also known as artificial pancreas (AP) systems, have shown significant improvement in type 1 diabetes mellitus (T1DM) management. However, demanding patient intervention is still required, particularly at meal times. To reduce treatment burden, the automatic regulation of glucose (ARG) algorithm mitigates postprandial glucose excursions without feedforward insulin boluses. This work assesses feasibility of this new strategy in a clinical trial. METHODS A 36-hour pilot study was performed on five T1DM subjects to validate the ARG algorithm. Subjects wore a subcutaneous continuous glucose monitor (CGM) and an insulin pump. Insulin delivery was solely commanded by the ARG algorithm, without premeal insulin boluses. This was the first clinical trial in Latin America to validate an AP controller. RESULTS For the total 36-hour period, results were as follows: average time of CGM readings in range 70-250 mg/dl: 88.6%, in range 70-180 mg/dl: 74.7%, <70 mg/dl: 5.8%, and <50 mg/dl: 0.8%. Results improved analyzing the final 15-hour period of this trial. In that case, the time spent in range was 70-250 mg/dl: 94.7%, in range 70-180 mg/dl: 82.6%, <70 mg/dl: 4.1%, and <50 mg/dl: 0.2%. During the last night the time spent in range was 70-250 mg/dl: 95%, in range 70-180 mg/dl: 87.7%, <70 mg/dl: 5.0%, and <50 mg/dl: 0.0%. No severe hypoglycemia occurred. No serious adverse events were reported. CONCLUSIONS The ARG algorithm was successfully validated in a pilot clinical trial, encouraging further tests with a larger number of patients and in outpatient settings.
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Affiliation(s)
- Ricardo Sánchez-Peña
- Instituto Tecnológico de Buenos Aires, Buenos Aires, Argentina
- National Scientific and Technical Research Council, Buenos Aires, Argentina
- Ricardo Sánchez-Peña, PhD, National Scientific and Technical Research Council (CONICET), Instituto Tecnológico de Buenos Aires (ITBA), Av Madero 399, Buenos Aires, C1106ACD, Argentina.
| | - Patricio Colmegna
- National Scientific and Technical Research Council, Buenos Aires, Argentina
- University of Virginia, Charlottesville, VA, USA
- Universidad Nacional de Quilmes, Bernal, Buenos Aires, Argentina
| | - Fabricio Garelli
- National Scientific and Technical Research Council, Buenos Aires, Argentina
- Universidad Nacional de La Plata, La Plata, Buenos Aires Argentina
| | - Hernán De Battista
- National Scientific and Technical Research Council, Buenos Aires, Argentina
- Universidad Nacional de La Plata, La Plata, Buenos Aires Argentina
| | - Demián García-Violini
- Instituto Tecnológico de Buenos Aires, Buenos Aires, Argentina
- National Scientific and Technical Research Council, Buenos Aires, Argentina
| | - Marcela Moscoso-Vásquez
- Instituto Tecnológico de Buenos Aires, Buenos Aires, Argentina
- National Scientific and Technical Research Council, Buenos Aires, Argentina
| | - Nicolás Rosales
- Universidad Nacional de La Plata, La Plata, Buenos Aires Argentina
| | - Emilia Fushimi
- National Scientific and Technical Research Council, Buenos Aires, Argentina
- Universidad Nacional de La Plata, La Plata, Buenos Aires Argentina
| | | | - Marc Breton
- University of Virginia, Charlottesville, VA, USA
| | - Valeria Beruto
- Hospital Italiano de Buenos Aires, Buenos Aires, Argentina
| | - Paula Scibona
- Hospital Italiano de Buenos Aires, Buenos Aires, Argentina
| | | | - Javier Giunta
- Hospital Italiano de Buenos Aires, Buenos Aires, Argentina
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Esposito S, Santi E, Mancini G, Rogari F, Tascini G, Toni G, Argentiero A, Berioli MG. Efficacy and safety of the artificial pancreas in the paediatric population with type 1 diabetes. J Transl Med 2018; 16:176. [PMID: 29954380 PMCID: PMC6022450 DOI: 10.1186/s12967-018-1558-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 06/23/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Type 1 diabetes (DM1) is one of the most common chronic diseases in childhood and requires life-long insulin therapy and continuous health care support. An artificial pancreas (AP) or closed-loop system (CLS) have been developed with the aim of improving metabolic control without increasing the risk of hypoglycaemia in patients with DM1. As the impact of APs have been studied mainly in adults, the aim of this review is to evaluate the efficacy and safety of the AP in the paediatric population with DM1. MAIN BODY The real advantage of a CLS compared to last-generation sensor-augmented pumps is the gradual modulation of basal insulin infusion in response to glycaemic variations (towards both hyperglycaemia and hypoglycaemia), which has the aim of improving the proportion of time spent in the target glucose range and reducing the mean glucose level without increasing the risk of hypoglycaemia. Some recent studies demonstrated that also in children and adolescents an AP is able to reduce the frequency of hypoglycaemic events, an important limiting factor in reaching good metabolic control, particularly overnight. However, the advantages of the AP in reducing hyperglycaemia, increasing the time spent in the target glycaemic range and thus reducing glycated haemoglobin are less clear and require more clinical trials in the paediatric population, in particular in younger children. CONCLUSIONS Although the first results from bi-hormonal CLS are promising, long-term, head-to-head studies will have to prove their superiority over insulin-only approaches. More technological progress, the availability of more fast-acting insulin, further developments of algorithms that could improve glycaemic control after meals and physical activity are the most important challenges in reaching an optimal metabolic control with the use of the AP in children and adolescents.
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Affiliation(s)
- Susanna Esposito
- Pediatric Clinic, Department of Surgical and Biomedical Sciences, Università degli Studi di Perugia, Piazza Menghini 1, 06129, Perugia, Italy.
| | - Elisa Santi
- Pediatric Clinic, Department of Surgical and Biomedical Sciences, Università degli Studi di Perugia, Piazza Menghini 1, 06129, Perugia, Italy
| | - Giulia Mancini
- Pediatric Clinic, Department of Surgical and Biomedical Sciences, Università degli Studi di Perugia, Piazza Menghini 1, 06129, Perugia, Italy
| | - Francesco Rogari
- Pediatric Clinic, Department of Surgical and Biomedical Sciences, Università degli Studi di Perugia, Piazza Menghini 1, 06129, Perugia, Italy
| | - Giorgia Tascini
- Pediatric Clinic, Department of Surgical and Biomedical Sciences, Università degli Studi di Perugia, Piazza Menghini 1, 06129, Perugia, Italy
| | - Giada Toni
- Pediatric Clinic, Department of Surgical and Biomedical Sciences, Università degli Studi di Perugia, Piazza Menghini 1, 06129, Perugia, Italy
| | - Alberto Argentiero
- Pediatric Clinic, Department of Surgical and Biomedical Sciences, Università degli Studi di Perugia, Piazza Menghini 1, 06129, Perugia, Italy
| | - Maria Giulia Berioli
- Pediatric Clinic, Department of Surgical and Biomedical Sciences, Università degli Studi di Perugia, Piazza Menghini 1, 06129, Perugia, Italy
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Dai X, Luo ZC, Zhai L, Zhao WP, Huang F. Artificial Pancreas as an Effective and Safe Alternative in Patients with Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis. Diabetes Ther 2018; 9:1269-1277. [PMID: 29744820 PMCID: PMC5984939 DOI: 10.1007/s13300-018-0436-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2018] [Indexed: 12/13/2022] Open
Abstract
INTRODUCTION Insulin injection is the main treatment in patients with type 1 diabetes mellitus (T1DM). Even though continuous glucose monitoring has significantly improved the conditions of these patients, limitations still exist. To further enhance glucose control in patients with T1DM, an artificial pancreas has been developed. We aimed to systematically compare artificial pancreas with its control group during a 24-h basis in patients with T1DM. METHODS Electronic databases were carefully searched for English publications comparing artificial pancreas with its control group. Overall daytime and nighttime glucose parameters were considered as the endpoints. Data were evaluated by means of weighted mean differences (WMDs) and 95% confidence intervals (CIs) generated by RevMan 5.3 software. RESULTS A total number of 354 patients were included. Artificial pancreas significantly maintained a better mean concentration of glucose (WMD - 1.03, 95% CI - 1.32 to - 0.75; P = 0.00001). Time spent in the hypoglycemic phase was also significantly lower (WMD - 1.23, 95% CI - 1.56 to - 0.91; P = 0.00001). Daily insulin requirement also significantly favored artificial pancreas (WMD - 3.43, 95% CI - 4.27 to - 2.59; P = 0.00001). Time spent outside the euglycemic phase and hyperglycemia phase (glucose > 10.0 mmol/L) also significantly favored artificial pancreas. Also, the numbers of hypoglycemic events were not significantly different. CONCLUSION Artificial pancreas might be considered an effective and safe alternative to be used during a 24-h basis in patients with T1DM.
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Affiliation(s)
- Xia Dai
- Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, People's Republic of China
| | - Zu-Chun Luo
- Department of Internal Medicine Education, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, People's Republic of China
| | - Lu Zhai
- Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, People's Republic of China
| | - Wen-Piao Zhao
- Department of Endocrinology, The First Affiliated Hospital of Guangxi Medical University, Nanning, 530021, Guangxi, People's Republic of China
| | - Feng Huang
- Institute of Cardiovascular Diseases and Guangxi Key Laboratory Base of Precision Medicine in Cardio-cerebrovascular Diseases Control and Prevention, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, 530021, People's Republic of China.
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Scholten K, Meng E. A review of implantable biosensors for closed-loop glucose control and other drug delivery applications. Int J Pharm 2018; 544:319-334. [DOI: 10.1016/j.ijpharm.2018.02.022] [Citation(s) in RCA: 42] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Revised: 01/30/2018] [Accepted: 02/15/2018] [Indexed: 12/19/2022]
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Bekiari E, Kitsios K, Thabit H, Tauschmann M, Athanasiadou E, Karagiannis T, Haidich AB, Hovorka R, Tsapas A. Artificial pancreas treatment for outpatients with type 1 diabetes: systematic review and meta-analysis. BMJ 2018; 361:k1310. [PMID: 29669716 PMCID: PMC5902803 DOI: 10.1136/bmj.k1310] [Citation(s) in RCA: 246] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
OBJECTIVE To evaluate the efficacy and safety of artificial pancreas treatment in non-pregnant outpatients with type 1 diabetes. DESIGN Systematic review and meta-analysis of randomised controlled trials. DATA SOURCES Medline, Embase, Cochrane Library, and grey literature up to 2 February 2018. ELIGIBILITY CRITERIA FOR SELECTING STUDIES Randomised controlled trials in non-pregnant outpatients with type 1 diabetes that compared the use of any artificial pancreas system with any type of insulin based treatment. Primary outcome was proportion (%) of time that sensor glucose level was within the near normoglycaemic range (3.9-10 mmol/L). Secondary outcomes included proportion (%) of time that sensor glucose level was above 10 mmol/L or below 3.9 mmol/L, low blood glucose index overnight, mean sensor glucose level, total daily insulin needs, and glycated haemoglobin. The Cochrane Collaboration risk of bias tool was used to assess study quality. RESULTS 40 studies (1027 participants with data for 44 comparisons) were included in the meta-analysis. 35 comparisons assessed a single hormone artificial pancreas system, whereas nine comparisons assessed a dual hormone system. Only nine studies were at low risk of bias. Proportion of time in the near normoglycaemic range (3.9-10.0 mmol/L) was significantly higher with artificial pancreas use, both overnight (weighted mean difference 15.15%, 95% confidence interval 12.21% to 18.09%) and over a 24 hour period (9.62%, 7.54% to 11.7%). Artificial pancreas systems had a favourable effect on the proportion of time with sensor glucose level above 10 mmol/L (-8.52%, -11.14% to -5.9%) or below 3.9 mmol/L (-1.49%, -1.86% to -1.11%) over 24 hours, compared with control treatment. Robustness of findings for the primary outcome was verified in sensitivity analyses, by including only trials at low risk of bias (11.64%, 9.1% to 14.18%) or trials under unsupervised, normal living conditions (10.42%, 8.63% to 12.2%). Results were consistent in a subgroup analysis both for single hormone and dual hormone artificial pancreas systems. CONCLUSIONS Artificial pancreas systems are an efficacious and safe approach for treating outpatients with type 1 diabetes. The main limitations of current research evidence on artificial pancreas systems are related to inconsistency in outcome reporting, small sample size, and short follow-up duration of individual trials.
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Affiliation(s)
- Eleni Bekiari
- Clinical Research and Evidence Based Medicine Unit, Aristotle University of Thessaloniki, 54642 Thessaloniki, Greece
| | - Konstantinos Kitsios
- Diabetes Centre, Second Medical Department, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Hood Thabit
- Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Martin Tauschmann
- Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Eleni Athanasiadou
- Clinical Research and Evidence Based Medicine Unit, Aristotle University of Thessaloniki, 54642 Thessaloniki, Greece
| | - Thomas Karagiannis
- Clinical Research and Evidence Based Medicine Unit, Aristotle University of Thessaloniki, 54642 Thessaloniki, Greece
| | - Anna-Bettina Haidich
- Department of Hygiene and Epidemiology, Medical School, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Roman Hovorka
- Wellcome Trust-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Apostolos Tsapas
- Clinical Research and Evidence Based Medicine Unit, Aristotle University of Thessaloniki, 54642 Thessaloniki, Greece
- Harris Manchester College, University of Oxford, Oxford, UK
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Bertachi A, Ramkissoon CM, Bondia J, Vehí J. Automated blood glucose control in type 1 diabetes: A review of progress and challenges. ACTA ACUST UNITED AC 2017; 65:172-181. [PMID: 29279252 DOI: 10.1016/j.endinu.2017.10.011] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2017] [Revised: 10/11/2017] [Accepted: 10/21/2017] [Indexed: 12/27/2022]
Abstract
Since the 2000s, research teams worldwide have been working to develop closed-loop (CL) systems able to automatically control blood glucose (BG) levels in patients with type 1 diabetes. This emerging technology is known as artificial pancreas (AP), and its first commercial version just arrived in the market. The main objective of this paper is to present an extensive review of the clinical trials conducted since 2011, which tested various implementations of the AP for different durations under varying conditions. A comprehensive table that contains key information from the selected publications is provided, and the main challenges in AP development and the mitigation strategies used are discussed. The development timelines for different AP systems are also included, highlighting the main evolutions over the clinical trials for each system.
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Affiliation(s)
- Arthur Bertachi
- Institute of Informatics and Applications, University of Girona, Campus de Montilivi, s/n, Edifici P4, 17071 Girona, Spain; Federal University of Technology - Paraná (UTFPR), Guarapuava, Avenida Professora Laura Pacheco Bastos 800, 85053-525 Guarapuava, Paraná, Brazil
| | - Charrise M Ramkissoon
- Institute of Informatics and Applications, University of Girona, Campus de Montilivi, s/n, Edifici P4, 17071 Girona, Spain
| | - Jorge Bondia
- Instituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, Camino de Vera, s/n, Edificio 8G, 46022 Valencia, Spain
| | - Josep Vehí
- Institute of Informatics and Applications, University of Girona, Campus de Montilivi, s/n, Edifici P4, 17071 Girona, Spain.
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Bally L, Thabit H, Hovorka R. Glucose-responsive insulin delivery for type 1 diabetes: The artificial pancreas story. Int J Pharm 2017; 544:309-318. [PMID: 29258910 DOI: 10.1016/j.ijpharm.2017.12.022] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Revised: 12/04/2017] [Accepted: 12/10/2017] [Indexed: 12/20/2022]
Abstract
Insulin replacement therapy is integral to the management of type 1 diabetes, which is characterised by absolute insulin deficiency. Optimal glycaemic control, as assessed by glycated haemoglobin, and avoidance of hyper- and hypoglycaemic excursions have been shown to prevent diabetes-related complications. Insulin pump use has increased considerably over the past decade with beneficial effects on glycaemic control, quality of life and treatment satisfaction. The advent and progress of ambulatory glucose sensor technology has enabled continuous glucose monitoring based on real-time glucose levels to be integrated with insulin therapy. Low glucose and predictive low glucose suspend systems are currently used in clinical practice to mitigate against hypoglycaemia, and provide the first step towards feedback glucose control. The more advanced technology approach, an artificial pancreas or a closed-loop system, gradually increases and decreases insulin delivery in a glucose-responsive fashion to mitigate against hyper- and hypoglycaemia. Randomised outpatient clinical trials over the past 5 years have demonstrated the feasibility, safety and efficacy of the approach, and the recent FDA approval of the first single hormone closed-loop system establishes a new standard of care for people with type 1 diabetes.
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Affiliation(s)
- Lia Bally
- Department of Diabetes, Endocrinology Clinical Nutrition & Metabolism, Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of General Internal Medicine, Inselspital, Bern University Hospital, University of Bern, Switzerland.
| | - Hood Thabit
- Central Manchester University Hospitals NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom; Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health, University of Manchester, United Kingdom
| | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom; Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom
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Dassau E, Pinsker JE, Kudva YC, Brown SA, Gondhalekar R, Dalla Man C, Patek S, Schiavon M, Dadlani V, Dasanayake I, Church MM, Carter RE, Bevier WC, Huyett LM, Hughes J, Anderson S, Lv D, Schertz E, Emory E, McCrady-Spitzer SK, Jean T, Bradley PK, Hinshaw L, Laguna Sanz AJ, Basu A, Kovatchev B, Cobelli C, Doyle FJ. Twelve-Week 24/7 Ambulatory Artificial Pancreas With Weekly Adaptation of Insulin Delivery Settings: Effect on Hemoglobin A 1c and Hypoglycemia. Diabetes Care 2017; 40:1719-1726. [PMID: 29030383 PMCID: PMC5711334 DOI: 10.2337/dc17-1188] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Accepted: 09/14/2017] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Artificial pancreas (AP) systems are best positioned for optimal treatment of type 1 diabetes (T1D) and are currently being tested in outpatient clinical trials. Our consortium developed and tested a novel adaptive AP in an outpatient, single-arm, uncontrolled multicenter clinical trial lasting 12 weeks. RESEARCH DESIGN AND METHODS Thirty adults with T1D completed a continuous glucose monitor (CGM)-augmented 1-week sensor-augmented pump (SAP) period. After the AP was started, basal insulin delivery settings used by the AP for initialization were adapted weekly, and carbohydrate ratios were adapted every 4 weeks by an algorithm running on a cloud-based server, with automatic data upload from devices. Adaptations were reviewed by expert study clinicians and patients. The primary end point was change in hemoglobin A1c (HbA1c). Outcomes are reported adhering to consensus recommendations on reporting of AP trials. RESULTS Twenty-nine patients completed the trial. HbA1c, 7.0 ± 0.8% at the start of AP use, improved to 6.7 ± 0.6% after 12 weeks (-0.3, 95% CI -0.5 to -0.2, P < 0.001). Compared with the SAP run-in, CGM time spent in the hypoglycemic range improved during the day from 5.0 to 1.9% (-3.1, 95% CI -4.1 to -2.1, P < 0.001) and overnight from 4.1 to 1.1% (-3.1, 95% CI -4.2 to -1.9, P < 0.001). Whereas carbohydrate ratios were adapted to a larger extent initially with minimal changes thereafter, basal insulin was adapted throughout. Approximately 10% of adaptation recommendations were manually overridden. There were no protocol-related serious adverse events. CONCLUSIONS Use of our novel adaptive AP yielded significant reductions in HbA1c and hypoglycemia.
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Affiliation(s)
- Eyal Dassau
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA.,William Sansum Diabetes Center, Santa Barbara, CA
| | | | | | - Sue A Brown
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Ravi Gondhalekar
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA.,William Sansum Diabetes Center, Santa Barbara, CA
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Steve Patek
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Michele Schiavon
- Department of Information Engineering, University of Padova, Padova, Italy
| | | | - Isuru Dasanayake
- William Sansum Diabetes Center, Santa Barbara, CA.,Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA
| | | | - Rickey E Carter
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | | | - Lauren M Huyett
- William Sansum Diabetes Center, Santa Barbara, CA.,Department of Chemical Engineering, University of California, Santa Barbara, Santa Barbara, CA
| | - Jonathan Hughes
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Stacey Anderson
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Dayu Lv
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Elaine Schertz
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Emma Emory
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | | | - Tyler Jean
- William Sansum Diabetes Center, Santa Barbara, CA
| | | | - Ling Hinshaw
- Endocrine Research Unit, Mayo Clinic, Rochester, MN
| | - Alejandro J Laguna Sanz
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA.,William Sansum Diabetes Center, Santa Barbara, CA
| | - Ananda Basu
- Endocrine Research Unit, Mayo Clinic, Rochester, MN
| | - Boris Kovatchev
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Claudio Cobelli
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Francis J Doyle
- 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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Graveling AJ, Frier BM. The risks of nocturnal hypoglycaemia in insulin-treated diabetes. Diabetes Res Clin Pract 2017; 133:30-39. [PMID: 28888993 DOI: 10.1016/j.diabres.2017.08.012] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2017] [Accepted: 08/17/2017] [Indexed: 12/29/2022]
Abstract
Over half of all episodes of severe hypoglycaemia (requiring external help) occur during sleep, but nocturnal hypoglycaemia is often asymptomatic and unrecognised. The precise incidence of nocturnal hypoglycaemia is difficult to determine with no agreed definition, but continuous glucose monitoring has shown that it occurs frequently in people taking insulin. Attenuation of the counter-regulatory responses to hypoglycaemia during sleep may explain why some episodes are undetected and more prolonged, and modifies cardiovascular responses. The morbidity and mortality associated with nocturnal hypoglycaemia is probably much greater than realised, causing seizures, coma and cardiovascular events and affecting quality of life, mood and work performance the following day. It may induce impaired awareness of hypoglycaemia. Cardiac arrhythmias that occur during nocturnal hypoglycaemia include bradycardia and ectopics that may provoke dangerous arrhythmias. Treatment strategies are discussed that may help to minimise the frequency of nocturnal hypoglycaemia.
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Affiliation(s)
- Alex J Graveling
- JJR Macleod Centre for Diabetes & Endocrinology, Aberdeen Royal Infirmary, Foresterhill, Aberdeen AB25 2ZP, UK.
| | - Brian M Frier
- The Queen's Medical Research Institute, The University of Edinburgh, Edinburgh EH16 4TJ, UK.
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Brown SA, Breton MD, Anderson SM, Kollar L, Keith-Hynes P, Levy CJ, Lam DW, Levister C, Baysal N, Kudva YC, Basu A, Dadlani V, Hinshaw L, McCrady-Spitzer S, Bruttomesso D, Visentin R, Galasso S, Del Favero S, Leal Y, Boscari F, Avogaro A, Cobelli C, Kovatchev BP. Overnight Closed-Loop Control Improves Glycemic Control in a Multicenter Study of Adults With Type 1 Diabetes. J Clin Endocrinol Metab 2017; 102:3674-3682. [PMID: 28666360 PMCID: PMC5630248 DOI: 10.1210/jc.2017-00556] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2017] [Accepted: 06/22/2017] [Indexed: 11/19/2022]
Abstract
CONTEXT Closed-loop control (CLC) for the management of type 1 diabetes (T1D) is a novel method for optimizing glucose control, and strategies for individualized implementation are being developed. OBJECTIVE To analyze glycemic control in an overnight CLC system designed to "reset" the patient to near-normal glycemic targets every morning. DESIGN Randomized, crossover, multicenter clinical trial. PARTICIPANTS Forty-four subjects with T1D requiring insulin pump therapy. INTERVENTION Sensor-augmented pump therapy (SAP) at home vs 5 nights of CLC (active from 23:00 to 07:00) in a supervised outpatient setting (research house or hotel), with a substudy of 5 nights of CLC subsequently at home. MAIN OUTCOME MEASURE The percentage of time spent in the target range (70 to 180 mg/dL measured using a continuous glucose monitor). RESULTS Forty subjects (age, 45.5 ± 9.5 years; hemoglobin A1c, 7.4% ± 0.8%) completed the study. The time in the target range (70 to 180 mg/dL) significantly improved in CLC vs SAP over 24 hours (78.3% vs 71.4%; P = 0.003) and overnight (85.7% vs 67.6%; P < 0.001). The time spent in a hypoglycemic range (<70 mg/dL) decreased significantly in the CLC vs SAP group over 24 hours (2.5% vs 4.3%; P = 0.002) and overnight (0.9% vs 3.2%; P < 0.001). The mean glucose level at 07:00 was lower with CLC than with SAP (123.7 vs 145.3 mg/dL; P < 0.001). The substudy at home, involving 10 T1D subjects, showed similar trends with an increased time in target (70 to 180 mg/dL) overnight (75.2% vs 62.2%; P = 0.07) and decreased time spent in the hypoglycemic range (<70 mg/dL) overnight in CLC vs SAP (0.6% vs 3.7%; P = 0.03). CONCLUSION Overnight-only CLC increased the time in the target range over 24 hours and decreased the time in hypoglycemic range over 24 hours in a supervised outpatient setting. A pilot extension study at home showed a similar nonsignificant trend.
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Affiliation(s)
- Sue A Brown
- Center for Diabetes Technology, Division of Endocrinology, University of Virginia, Charlottesville, Virginia 22903
| | - Marc D Breton
- Center for Diabetes Technology, Division of Endocrinology, University of Virginia, Charlottesville, Virginia 22903
| | - Stacey M Anderson
- Center for Diabetes Technology, Division of Endocrinology, University of Virginia, Charlottesville, Virginia 22903
| | - Laura Kollar
- Center for Diabetes Technology, Division of Endocrinology, University of Virginia, Charlottesville, Virginia 22903
| | | | - Carol J Levy
- Icahn School of Medicine at Mount Sinai, New York, New York 10029
| | - David W Lam
- Icahn School of Medicine at Mount Sinai, New York, New York 10029
| | - Camilla Levister
- Icahn School of Medicine at Mount Sinai, New York, New York 10029
| | - Nihat Baysal
- Rensselaer Polytechnic Institute, Troy, New York 12180
| | | | | | | | | | | | - Daniela Bruttomesso
- Unit of Metabolic Diseases, Department of Internal Medicine, University of Padua, Padua 35122, Italy
| | - Roberto Visentin
- Department of Information Engineering, University of Padua, Padua 35122, Italy
| | - Silvia Galasso
- Unit of Metabolic Diseases, Department of Internal Medicine, University of Padua, Padua 35122, Italy
| | - Simone Del Favero
- Department of Information Engineering, University of Padua, Padua 35122, Italy
| | - Yenny Leal
- Department of Information Engineering, University of Padua, Padua 35122, Italy
| | - Federico Boscari
- Unit of Metabolic Diseases, Department of Internal Medicine, University of Padua, Padua 35122, Italy
| | - Angelo Avogaro
- Unit of Metabolic Diseases, Department of Internal Medicine, University of Padua, Padua 35122, Italy
| | - Claudio Cobelli
- Department of Information Engineering, University of Padua, Padua 35122, Italy
| | - Boris P Kovatchev
- Center for Diabetes Technology, Division of Endocrinology, University of Virginia, Charlottesville, Virginia 22903
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Guilhem I, Penet M, Paillard A, Carpentier M, Esvant A, Lefebvre MA, Poirier JY. Manual Closed-Loop Insulin Delivery Using a Saddle Point Model Predictive Control Algorithm: Results of a Crossover Randomized Overnight Study. J Diabetes Sci Technol 2017; 11:1007-1014. [PMID: 28677416 PMCID: PMC5951001 DOI: 10.1177/1932296817717503] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND The purpose was to assess the efficacy of a new closed-loop algorithm (Saddle Point Model Predictive Control, SP-MPC) in achieving nocturnal normoglycemia while reducing the risk of hypoglycemia in patients with type 1 diabetes. METHOD In this randomized crossover study, 10 adult patients (mean hemoglobin A1c 7.35 ± 1.04%) were assigned to be treated overnight by open loop using sensor-augmented pump therapy (open-loop SAP) or manual closed-loop delivery. During closed loop, insulin doses were calculated using the SP-MPC algorithm and administered as manual boluses every 15 minutes from 9:00 pm to 8:00 am. Patients consumed a self-selected meal (65-125 g of carbohydrates) at 7:00 pm accompanied by their usual prandial bolus. Blood glucose was measured every 30 minutes. The primary endpoints were the time spent in target (70-145 mg/dl) and time spent below 70 mg/dl from 11:00 pm to 8:00 am. RESULTS Time spent in target did not differ between closed-loop and open-loop SAP. The number of hypoglycemic events (<70 mg/dl) was reduced 2.8-fold in closed loop (n = 5, median = 0/patient/hour; interquartile range: 0-0.11) as compared to open-loop SAP (n = 14, median = 0.22/patient/hour, 0.02-0.22) ( P = .02). The area under the curve for sensor glucose values >145 mg/dl was significantly lower during closed-loop than during open-loop SAP ( P = .03) as well as HBGI ( P = .02). CONCLUSIONS This pilot study suggests that the use of the SP-MPC algorithm may improve mean overnight glucose control and reduce the number of hypoglycemic events as compared to SAP therapy.
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Affiliation(s)
- Isabelle Guilhem
- CHU de Rennes, Department of Endocrinology, Diabetes and Nutrition, Rennes, France
- CHU de Rennes, CIC INSERM 1414, Rennes, France
- Isabelle Guilhem, MD, MSc, service d’Endocrinologie-Diabétologie-Nutrition, CHU de Rennes, hôpital sud, 16 boulevard de Bulgarie, 35203 Rennes cedex, France.
| | - Maxime Penet
- CentraleSupélec/I.E.T.R, Hybrid System Control Team, Cesson-Sévigné, France
| | - Anaïs Paillard
- CHU de Rennes, Department of Endocrinology, Diabetes and Nutrition, Rennes, France
- CHU de Rennes, CIC INSERM 1414, Rennes, France
| | - Marc Carpentier
- CHU de Rennes, Département d’Information Médicale, Rennes, France
| | - Annabelle Esvant
- CHU de Rennes, Department of Endocrinology, Diabetes and Nutrition, Rennes, France
- CHU de Rennes, CIC INSERM 1414, Rennes, France
| | | | - Jean-Yves Poirier
- CHU de Rennes, Department of Endocrinology, Diabetes and Nutrition, Rennes, France
- CHU de Rennes, CIC INSERM 1414, Rennes, France
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Ang KH, Sherr JL. Moving beyond subcutaneous insulin: the application of adjunctive therapies to the treatment of type 1 diabetes. Expert Opin Drug Deliv 2017; 14:1113-1131. [DOI: 10.1080/17425247.2017.1360862] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Kathleen H. Ang
- Yale Children’s Diabetes Program, Yale University School of Medicine, New Haven, CT, USA
| | - Jennifer L. Sherr
- Yale Children’s Diabetes Program, Yale University School of Medicine, New Haven, CT, USA
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40
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Weisman A, Bai JW, Cardinez M, Kramer CK, Perkins BA. Effect of artificial pancreas systems on glycaemic control in patients with type 1 diabetes: a systematic review and meta-analysis of outpatient randomised controlled trials. Lancet Diabetes Endocrinol 2017; 5:501-512. [PMID: 28533136 DOI: 10.1016/s2213-8587(17)30167-5] [Citation(s) in RCA: 304] [Impact Index Per Article: 43.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Revised: 04/11/2017] [Accepted: 04/11/2017] [Indexed: 12/27/2022]
Abstract
BACKGROUND Closed-loop artificial pancreas systems have been in development for several years, including assessment in numerous varied outpatient clinical trials. We aimed to summarise the efficacy and safety of artificial pancreas systems in outpatient settings and explore the clinical and technical factors that can affect their performance. METHODS We did a systematic review and meta-analysis of randomised controlled trials comparing artificial pancreas systems (insulin only or insulin plus glucagon) with conventional pump therapy (continuous subcutaneous insulin infusion [CSII] with blinded continuous glucose monitoring [CGM] or unblinded sensor-augmented pump [SAP] therapy) in adults and children with type 1 diabetes. We searched Medline, Embase, and the Cochrane Central Register of Controlled Trials for studies published from 1946, to Jan 1, 2017. We excluded studies not published in English, those involving pregnant women or participants who were in hospital, and those testing adjunct medications other than glucagon. The primary outcome was the mean difference in percentage of time blood glucose concentration remained in target range (3·9-10 mmol/L or 3·9-8 mmol/L, depending on the study), assessed by random-effects meta-analysis. This study is registered with PROSPERO, number 2015:CRD42015026854. FINDINGS We identified 984 reports; after exclusions, 27 comparisons from 24 studies (23 crossover and one parallel design) including a total of 585 participants (219 in adult studies, 265 in paediatric studies, and 101 in combined studies) were eligible for analysis. Five comparisons assessed dual-hormone (insulin and glucagon), two comparisons assessed both dual-hormone and single-hormone (insulin only), and 20 comparisons assessed single-hormone artificial pancreas systems. Time in target was 12·59% higher with artificial pancreas systems (95% CI 9·02-16·16; p<0·0001), from a weighted mean of 58·21% for conventional pump therapy (I2=84%). Dual-hormone artificial pancreas systems were associated with a greater improvement in time in target range compared with single-hormone systems (19·52% [95% CI 15·12-23·91] vs 11·06% [6·94 to 15·18]; p=0·006), although six of seven comparisons compared dual-hormone systems to CSII with blinded CGM, whereas 21 of 22 single-hormone comparisons had SAP as the comparator. Single-hormone studies had higher heterogeneity than dual-hormone studies (I2 79% vs 66%). Bias assessment characteristics were incompletely reported in 12 of 24 studies, no studies masked participants to the intervention assignment, and masking of outcome assessment was not done in 12 studies and was unclear in 12 studies. INTERPRETATION Artificial pancreas systems uniformly improved glucose control in outpatient settings, despite heterogeneous clinical and technical factors. FUNDING None.
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Affiliation(s)
- Alanna Weisman
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada; Division of Endocrinology and Metabolism, Department of Medicine, University of Toronto, Toronto, ON, Canada.
| | - Johnny-Wei Bai
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | - Marina Cardinez
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada
| | - Caroline K Kramer
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada; Division of Endocrinology and Metabolism, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Bruce A Perkins
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada; Division of Endocrinology and Metabolism, Department of Medicine, University of Toronto, Toronto, ON, Canada
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Turksoy K, Frantz N, Quinn L, Dumin M, Kilkus J, Hibner B, Cinar A, Littlejohn E. Automated Insulin Delivery-The Light at the End of the Tunnel. J Pediatr 2017; 186:17-28.e9. [PMID: 28396030 DOI: 10.1016/j.jpeds.2017.02.055] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2016] [Revised: 02/13/2017] [Accepted: 02/20/2017] [Indexed: 12/28/2022]
Affiliation(s)
- Kamuran Turksoy
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL
| | - Nicole Frantz
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL
| | - Laurie Quinn
- College of Nursing, University of Illinois at Chicago, Chicago, IL
| | - Magdalena Dumin
- Biological Sciences Division, University of Chicago, Chicago, IL
| | - Jennifer Kilkus
- Biological Sciences Division, University of Chicago, Chicago, IL
| | - Brooks Hibner
- Biological Sciences Division, University of Chicago, Chicago, IL
| | - Ali Cinar
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL; Biological Sciences Division, University of Chicago, Chicago, IL; Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL
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Christiansen SC, Fougner AL, Stavdahl Ø, Kölle K, Ellingsen R, Carlsen SM. A Review of the Current Challenges Associated with the Development of an Artificial Pancreas by a Double Subcutaneous Approach. Diabetes Ther 2017; 8:489-506. [PMID: 28503717 PMCID: PMC5446388 DOI: 10.1007/s13300-017-0263-6] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Indexed: 01/01/2023] Open
Abstract
INTRODUCTION Patients with diabetes type 1 (DM1) struggle daily to achieve good glucose control. The last decade has seen a rush of research groups working towards an artificial pancreas (AP) through the application of a double subcutaneous approach, i.e., subcutaneous (SC) continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion. Few have focused on the fundamental limitations of this approach, especially regarding outcome measures beyond time in range. METHODS Based on insulin physiology, the limitations of CGM, SC insulin absorption, meal challenge, and physical activity in DM1 patients, we discuss the limitations of the double SC approach. Finally, we discuss safety measures and the achievements reported in some recent AP studies that have utilized the double SC approach. RESULTS Most studies show that a double SC AP increases the time in range compared to a sensor-augmented insulin pump and shortens the time in hypoglycemia. Despite these achievements, the proportion of time spent in hyperglycemia is still roughly 20-40%, and hypoglycemia is still present 1-4% of the time. The main factors limiting further progress are the latency of SC CGM (at least 5-10 min) and the slow pharmacokinetics of SC-delivered fast-acting insulin. The maximum blood insulin level is reached after 45 min and the maximum glucose-lowering effect is observed after 1.5-2 h, while the glucose-lowering effect lasts for at least 5 h. CONCLUSIONS Although using a double SC AP leads to significant improvements in glucose control, the SC approach has severe limitations that hamper further progress towards a robust AP.
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Affiliation(s)
- Sverre Christian Christiansen
- Department of Endocrinology, St Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
| | - Anders Lyngvi Fougner
- Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Central Norway Regional Health Authority, Stjørdal, Norway
| | - Øyvind Stavdahl
- Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Konstanze Kölle
- Department of Engineering Cybernetics, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Central Norway Regional Health Authority, Stjørdal, Norway
| | - Reinold Ellingsen
- Department of Electronic Systems, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Sven Magnus Carlsen
- Department of Endocrinology, St Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
- Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
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Oviedo S, Vehí J, Calm R, Armengol J. A review of personalized blood glucose prediction strategies for T1DM patients. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2017; 33:e2833. [PMID: 27644067 DOI: 10.1002/cnm.2833] [Citation(s) in RCA: 107] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Revised: 09/15/2016] [Accepted: 09/16/2016] [Indexed: 06/06/2023]
Abstract
This paper presents a methodological review of models for predicting blood glucose (BG) concentration, risks and BG events. The surveyed models are classified into three categories, and they are presented in summary tables containing the most relevant data regarding the experimental setup for fitting and testing each model as well as the input signals and the performance metrics. Each category exhibits trends that are presented and discussed. This document aims to be a compact guide to determine the modeling options that are currently being exploited for personalized BG prediction.
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Affiliation(s)
- Silvia Oviedo
- Institut d'Informàtica i Aplicacions, Parc Científic i Tecnològic de la Universitat de Girona, 17003, Girona, Spain
| | - Josep Vehí
- Institut d'Informàtica i Aplicacions, Universitat de Girona, Campus Montilivi, Edifici P4, 17071, Girona, Spain
| | - Remei Calm
- Institut d'Informàtica i Aplicacions, Universitat de Girona, Campus Montilivi, Edifici P4, 17071, Girona, Spain
| | - Joaquim Armengol
- Institut d'Informàtica i Aplicacions, Universitat de Girona, Campus Montilivi, Edifici P4, 17071, Girona, Spain
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Buckingham BA, Bailey TS, Christiansen M, Garg S, Weinzimer S, Bode B, Anderson SM, Brazg R, Ly TT, Kaufman FR. Evaluation of a Predictive Low-Glucose Management System In-Clinic. Diabetes Technol Ther 2017; 19:288-292. [PMID: 28221823 DOI: 10.1089/dia.2016.0319] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
BACKGROUND Predictions based on continuous glucose monitoring (CGM) data are the basis for automatic suspension and resumption of insulin delivery by a predictive low-glucose management feature termed "suspend before low," which is part of the Medtronic MiniMed® 640G combined insulin pump and CGM system. This study assessed the safety and performance characteristics of the system in an in-clinic setting at eight sites. MATERIALS AND METHODS In-clinic standardized increases in basal insulin delivery rates were used to induce nocturnal hypoglycemia in subjects (14-75 years) with type 1 diabetes wearing the MiniMed 640G system. The "suspend before low" feature was set at 65 mg/dL, and as a result, the predictive algorithm suspended insulin delivery when the forecasted glucose was predicted to be ≤85 mg/dL in 30 min (a 20 mg/dL safety buffer). Reference plasma glucose values (Yellow Springs Instruments [YSI], Yellow Springs, OH) were used to establish hypoglycemia and were defined as ≥2 consecutive values ≤65 mg/dL. RESULTS Eighty subjects were screened. Among the 69 successful completers, 27 experienced a hypoglycemic event and 42 did not, a prevention rate of 60%. The mean (±standard deviation) YSI value at the time of pump suspension was 101 ± 18.5 mg/dL, and the mean duration of the 68 "suspend before low" events was 105 ± 27 min. At 120 min after the start of the pump suspension events, the mean YSI value was 102 ± 34.6 mg/dL. CONCLUSION The MiniMed 640G "suspend before low" feature prevented 60% of induced predicted hypoglycemic events without significant rebound hyperglycemia.
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Affiliation(s)
- Bruce A Buckingham
- 1 Department of Pediatric Endocrinology, Stanford University , Stanford, California
| | | | | | - Satish Garg
- 4 Barbara Davis Center for Diabetes , Aurora, Colorado
| | - Stuart Weinzimer
- 5 Department of Pediatrics, Yale University School of Medicine , New Haven, Connecticut
| | - Bruce Bode
- 6 Atlanta Diabetes Center , Atlanta, Georgia
| | | | - Ronald Brazg
- 8 Rainier Clinical Research Center , Renton, Washington
| | - Trang T Ly
- 1 Department of Pediatric Endocrinology, Stanford University , Stanford, California
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Haidar A, Messier V, Legault L, Ladouceur M, Rabasa-Lhoret R. Outpatient 60-hour day-and-night glucose control with dual-hormone artificial pancreas, single-hormone artificial pancreas, or sensor-augmented pump therapy in adults with type 1 diabetes: An open-label, randomised, crossover, controlled trial. Diabetes Obes Metab 2017; 19:713-720. [PMID: 28094472 DOI: 10.1111/dom.12880] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2016] [Revised: 01/03/2017] [Accepted: 01/12/2017] [Indexed: 01/17/2023]
Abstract
AIMS To assess whether the dual-hormone (insulin and glucagon) artificial pancreas reduces hypoglycaemia compared to the single-hormone (insulin alone) artificial pancreas in outpatient settings during the day and night. MATERIAL AND METHODS In a randomized, three-way, crossover trial we compared the dual-hormone artificial pancreas, the single-hormone artificial pancreas and sensor-augmented pump therapy (control) in 23 adults with type 1 diabetes. Each intervention was applied from 8 AM Day 1 to 8 PM Day 3 (60 hours) in outpatient free-living conditions. The primary outcome was time spent with sensor glucose levels below 4.0 mmol/L. A P value of less than .017 was regarded as significant. RESULTS The median difference between the dual-hormone system and the single-hormone system was -2.3% (P = .072) for time spent below 4.0 mmol/L, -1.3% (P = .017) for time below 3.5 mmol/L, and -0.7% (P = .031) for time below 3.3 mmol/L. Both systems reduced (P < .017) hypoglycaemia below 4.0, 3.5 and 3.3 mmol/L compared to control therapy, but reductions were larger with the dual-hormone system than with the single-hormone system (medians -4.0% vs -3.4% for 4.0 mmol/L; -2.7% vs -2.2% for 3.5 mmol/L; and -2.2% vs -1.2% for 3.3 mmol/L). There were 34 hypoglycaemic events (<3.0 mmol/L for 20 minutes) with control therapy, 14 with the single-hormone system and 6 with the dual-hormone system. These differences in hypoglycaemia were observed while mean glucose level was low and comparable in all interventions (P = NS). CONCLUSIONS The dual-hormone artificial pancreas had the lowest risk of hypoglycaemia, but the differences were not statistically significant. Larger studies are needed.
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Affiliation(s)
- Ahmad Haidar
- Faculty of Medicine, Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada
- Faculty of Medicine, Division of Endocrinology and Metabolism, McGill University, Montréal, Québec, Canada
| | - Virginie Messier
- Institut de recherches cliniques de Montréal, Montréal, Québec, Canada
| | - Laurent Legault
- Montreal Children's Hospital, McGill University Health Centre, Montréal, Québec, Canada
| | - Martin Ladouceur
- The Research Center of the Université de Montréal Hospital Center, Montréal, Québec, Canada
- Département de Médecine Sociale et Préventive, School of Public Health, Université de Montréal, Montréal, Québec, Canada
| | - Rémi Rabasa-Lhoret
- Institut de recherches cliniques de Montréal, Montréal, Québec, Canada
- The Research Center of the Université de Montréal Hospital Center, Montréal, Québec, Canada
- Faculty of Medicine, Nutrition Department, Université de Montréal, Montréal, Québec, Canada
- Montreal Diabetes Research Center, Montréal, Québec, Canada
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Nimri R, Bratina N, Kordonouri O, Avbelj Stefanija M, Fath M, Biester T, Muller I, Atlas E, Miller S, Fogel A, Phillip M, Danne T, Battelino T. MD-Logic overnight type 1 diabetes control in home settings: A multicentre, multinational, single blind randomized trial. Diabetes Obes Metab 2017; 19:553-561. [PMID: 27981804 DOI: 10.1111/dom.12852] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2016] [Revised: 11/25/2016] [Accepted: 12/08/2016] [Indexed: 01/17/2023]
Abstract
AIMS To evaluate the safety, efficacy and need for remote monitoring of the MD-Logic closed-loop system during short-term overnight use at home. METHODS Seventy-five patients (38 male; aged 10-54 years; average A1c, 7.8% ± 0.7%, 61.8 ± 7.2 mmol/mol) were enrolled from 3 clinical sites. Patients were randomly assigned to participate in 2 overnight crossover periods, each including 4 consecutive nights, 1 under closed-loop control and 1 under sensor-augmented pump (SAP) therapy in the patient's home. Both study arms were supervised using a remote-monitoring system in a blinded manner. Primary endpoints were time spent with glucose levels below 70 mg/dL and percentage of nights in which mean overnight glucose levels were within 90 to 140 mg/dL. RESULTS The median [interquartile range] percentage of time spent in hypoglycaemia was significantly lower on nights when MD-Logic was used, compared to SAP therapy (2.07 [0, 4.78] and 2.6 [0, 10.34], respectively; P = .004) and the percentage of individual nights with a mean overnight glucose level in target was significantly greater (75 [42, 75] and 50 [25,75], respectively; P = .008). The time spent in target range was increased by a median of 28% (P = .001), with the same amount of insulin (10.69 [7.28, 13.94] and 10.41[6.9, 14.07], respectively; P = .087). The remote monitoring triggered calls for hypoglycaemia at twice the rate during SAP therapy compared to closed-loop control (62 and 29, respectively; P = .002). CONCLUSIONS The MD-Logic system demonstrated a safe and efficient profile during overnight use by children, adolescents and adults with type 1 diabetes and, therefore, provides an effective means of mitigating the risk of nocturnal hypoglycaemia.
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Affiliation(s)
- Revital Nimri
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
| | - Natasa Bratina
- Department of Pediatric Endocrinology, Diabetes and Metabolism, University Children's Hospital, Ljubljana, Slovenia
| | - Olga Kordonouri
- Diabetes Centre for Children and Adolescents, AUF DER BULT, Kinder- und Jugendkrankenhaus, Hannover, Germany
| | - Magdalena Avbelj Stefanija
- Department of Pediatric Endocrinology, Diabetes and Metabolism, University Children's Hospital, Ljubljana, Slovenia
| | - Maryam Fath
- Diabetes Centre for Children and Adolescents, AUF DER BULT, Kinder- und Jugendkrankenhaus, Hannover, Germany
| | - Torben Biester
- Diabetes Centre for Children and Adolescents, AUF DER BULT, Kinder- und Jugendkrankenhaus, Hannover, Germany
| | - Ido Muller
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
| | - Eran Atlas
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
| | - Shahar Miller
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
| | - Aviel Fogel
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
| | - Moshe Phillip
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Thomas Danne
- Diabetes Centre for Children and Adolescents, AUF DER BULT, Kinder- und Jugendkrankenhaus, Hannover, Germany
| | - Tadej Battelino
- Department of Pediatric Endocrinology, Diabetes and Metabolism, University Children's Hospital, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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Spaic T, Driscoll M, Raghinaru D, Buckingham BA, Wilson DM, Clinton P, Chase HP, Maahs DM, Forlenza GP, Jost E, Hramiak I, Paul T, Bequette BW, Cameron F, Beck RW, Kollman C, Lum JW, Ly TT. Predictive Hyperglycemia and Hypoglycemia Minimization: In-Home Evaluation of Safety, Feasibility, and Efficacy in Overnight Glucose Control in Type 1 Diabetes. Diabetes Care 2017; 40:359-366. [PMID: 28100606 PMCID: PMC5319476 DOI: 10.2337/dc16-1794] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2016] [Accepted: 12/22/2016] [Indexed: 02/03/2023]
Abstract
OBJECTIVE The objective of this study was to determine the safety, feasibility, and efficacy of a predictive hyperglycemia and hypoglycemia minimization (PHHM) system compared with predictive low-glucose insulin suspension (PLGS) alone in overnight glucose control. RESEARCH DESIGN AND METHODS A 42-night trial was conducted in 30 individuals with type 1 diabetes in the age range 15-45 years. Participants were randomly assigned each night to either PHHM or PLGS and were blinded to the assignment. The system suspended the insulin pump on both the PHHM and PLGS nights for predicted hypoglycemia but delivered correction boluses for predicted hyperglycemia on PHHM nights only. The primary outcome was the percentage of time spent in a sensor glucose range of 70-180 mg/dL during the overnight period. RESULTS The addition of automated insulin delivery with PHHM increased the time spent in the target range (70-180 mg/dL) from 71 ± 10% during PLGS nights to 78 ± 10% during PHHM nights (P < 0.001). The average morning blood glucose concentration improved from 163 ± 23 mg/dL after PLGS nights to 142 ± 18 mg/dL after PHHM nights (P < 0.001). Various sensor-measured hypoglycemic outcomes were similar on PLGS and PHHM nights. All participants completed 42 nights with no episodes of severe hypoglycemia, diabetic ketoacidosis, or other study- or device-related adverse events. CONCLUSIONS The addition of a predictive hyperglycemia minimization component to our existing PLGS system was shown to be safe, feasible, and effective in overnight glucose control.
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Affiliation(s)
- Tamara Spaic
- St. Joseph's Health Care London, London, Ontario, Canada
| | | | | | - Bruce A Buckingham
- Department of Pediatrics, Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, CA
| | - Darrell M Wilson
- Department of Pediatrics, Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, CA
| | - Paula Clinton
- Department of Pediatrics, Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, CA
| | - H Peter Chase
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - David M Maahs
- Department of Pediatrics, Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, CA.,Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Gregory P Forlenza
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Emily Jost
- Barbara Davis Center for Childhood Diabetes, University of Colorado School of Medicine, Aurora, CO
| | - Irene Hramiak
- St. Joseph's Health Care London, London, Ontario, Canada
| | - Terri Paul
- St. Joseph's Health Care London, London, Ontario, Canada
| | | | | | - Roy W Beck
- Jaeb Center for Health Research, Tampa, FL
| | | | - John W Lum
- Jaeb Center for Health Research, Tampa, FL
| | - Trang T Ly
- Department of Pediatrics, Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, CA
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Kovatchev B, Cheng P, Anderson SM, Pinsker JE, Boscari F, Buckingham BA, Doyle FJ, Hood KK, Brown SA, Breton MD, Chernavvsky D, Bevier WC, Bradley PK, Bruttomesso D, Del Favero S, Calore R, Cobelli C, Avogaro A, Ly TT, Shanmugham S, Dassau E, Kollman C, Lum JW, Beck RW. Feasibility of Long-Term Closed-Loop Control: A Multicenter 6-Month Trial of 24/7 Automated Insulin Delivery. Diabetes Technol Ther 2017; 19:18-24. [PMID: 27982707 DOI: 10.1089/dia.2016.0333] [Citation(s) in RCA: 92] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
BACKGROUND In the past few years, the artificial pancreas-the commonly accepted term for closed-loop control (CLC) of blood glucose in diabetes-has become a hot topic in research and technology development. In the summer of 2014, we initiated a 6-month trial evaluating the safety of 24/7 CLC during free-living conditions. RESEARCH DESIGN AND METHODS Following an initial 1-month Phase 1, 14 individuals (10 males/4 females) with type 1 diabetes at three clinical centers in the United States and one in Italy continued with a 5-month Phase 2, which included 24/7 CLC using the wireless portable Diabetes Assistant (DiAs) developed at the University of Virginia Center for Diabetes Technology. Median subject characteristics were age 45 years, duration of diabetes 27 years, total daily insulin 0.53 U/kg/day, and baseline HbA1c 7.2% (55 mmol/mol). RESULTS Compared with the baseline observation period, the frequency of hypoglycemia below 3.9 mmol/L during the last 3 months of CLC was lower: 4.1% versus 1.3%, P < 0.001. This was accompanied by a downward trend in HbA1c from 7.2% (55 mmol/mol) to 7.0% (53 mmol/mol) at 6 months. HbA1c improvement was correlated with system use (Spearman r = 0.55). The user experience was favorable with identified benefit particularly at night and overall trust in the system. There were no serious adverse events, severe hypoglycemia, or diabetic ketoacidosis. CONCLUSION We conclude that CLC technology has matured and is safe for prolonged use in patients' natural environment. Based on these promising results, a large randomized trial is warranted to assess long-term CLC efficacy and safety.
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Affiliation(s)
- Boris Kovatchev
- 1 University of Virginia Center for Diabetes Technology, Charlottesville, Virginia
| | - Peiyao Cheng
- 2 Jaeb Center for Health Research , Tampa, Florida
| | - Stacey M Anderson
- 1 University of Virginia Center for Diabetes Technology, Charlottesville, Virginia
| | | | | | - Bruce A Buckingham
- 5 Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine , Stanford, California
| | - Francis J Doyle
- 6 Department of Chemical Engineering, University of California , Santa Barbara, Santa Barbara, California
- 7 Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University , Cambridge, Massachusetts
| | - Korey K Hood
- 5 Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine , Stanford, California
| | - Sue A Brown
- 1 University of Virginia Center for Diabetes Technology, Charlottesville, Virginia
| | - Marc D Breton
- 1 University of Virginia Center for Diabetes Technology, Charlottesville, Virginia
| | - Daniel Chernavvsky
- 1 University of Virginia Center for Diabetes Technology, Charlottesville, Virginia
| | - Wendy C Bevier
- 3 William Sansum Diabetes Center , Santa Barbara, California
| | - Paige K Bradley
- 3 William Sansum Diabetes Center , Santa Barbara, California
| | | | | | | | | | | | - Trang T Ly
- 5 Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine , Stanford, California
| | - Satya Shanmugham
- 5 Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine , Stanford, California
| | - Eyal Dassau
- 6 Department of Chemical Engineering, University of California , Santa Barbara, Santa Barbara, California
- 7 Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University , Cambridge, Massachusetts
| | | | - John W Lum
- 2 Jaeb Center for Health Research , Tampa, Florida
| | - Roy W Beck
- 2 Jaeb Center for Health Research , Tampa, Florida
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49
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Ramkissoon CM, Aufderheide B, Bequette BW, Vehi J. A Review of Safety and Hazards Associated With the Artificial Pancreas. IEEE Rev Biomed Eng 2017; 10:44-62. [DOI: 10.1109/rbme.2017.2749038] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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50
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Ekhlaspour L, Maahs DM. In-Home Closed Loop Control for Artificial Pancreas: Patient and Provider Perspective. Diabetes Technol Ther 2017; 19:4-6. [PMID: 28055224 PMCID: PMC6435341 DOI: 10.1089/dia.2016.0432] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Laya Ekhlaspour
- Division of Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine , Stanford, California
| | - David M Maahs
- Division of Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine , Stanford, California
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