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Olid-Cárdenas MJ, Lendínez-Jurado A, Monroy-Rodríguez G, Gómez-Perea A, Cano-Ortiz A, Ariza-Jiménez AB, García-Ruiz A, Jiménez-Cuenca P, Picón-César MJ, Leiva-Gea I. Real-World Use of Hybrid Closed-Loop Systems during Diabetes Camp: A Preliminary Study for Secure Configuration Strategies in Children and Adolescents. Nutrients 2024; 16:2210. [PMID: 39064653 PMCID: PMC11279836 DOI: 10.3390/nu16142210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Revised: 07/08/2024] [Accepted: 07/09/2024] [Indexed: 07/28/2024] Open
Abstract
The introduction of closed-loop systems in the pediatric population has been a revolution in the management and evolution of diabetes. However, there are not many published studies in situations in which the feeding, schedules, and activities of the children deviate from the routine for which the systems were programmed, as in the case of a summer camp for children and adolescents with diabetes, where the specific programming of this device is not well known. It was a single-center prospective preliminary study. A total of twenty-seven patients (mean age 11.9 ± 1.9 years, 40% male, duration of diabetes 6.44 ± 2.83 years) were included (twenty with Medtronic MiniMed 780G system and seven with Tandem Control-IQ). Glucometric variables and pump functionality were monitored during the 7-day camp and in the following 3 weeks. There was no decrease from the objective TIR 70% at any moment. The worst results in Time Below Range were at 72 h from starting the camp, and the worst results in Time Above Range were in the first 24 h, with a progressive improvement after that. No episodes of level 3 hypoglycemia or ketoacidosis occurred. The use of specific programming in two integrated systems, with complex blood glucose regulation algorithms and not-prepared-for situations with increased levels of physical activity or abrupt changes in feeding routines, did not result in an increased risk of level 3 hypoglycemia and ketoacidosis for our pediatric type 1 diabetes (T1D) patients, regardless of the closed-loop device.
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Affiliation(s)
- María José Olid-Cárdenas
- Department of Marketing and Communication, Faculty of Communication, European University of Madrid, 28670 Villaviciosa de Odón, Spain;
- Faculty of Tourism, University of Malaga, Campus de Teatinos s/n, 29071 Málaga, Spain
- Andalucía Tech, Universidad de Málaga, Campus de Teatinos s/n, 29071 Málaga, Spain;
| | - Alfonso Lendínez-Jurado
- Andalucía Tech, Universidad de Málaga, Campus de Teatinos s/n, 29071 Málaga, Spain;
- Department of Pediatric Endocrinology, Hospital Regional Universitario de Málaga, 29011 Málaga, Spain; (A.G.-P.); (P.J.-C.)
- Distrito Sanitario Málaga-Guadalhorce, 29009 Málaga, Spain;
| | - Gabriela Monroy-Rodríguez
- Department of Endocrinology and Nutrition, Parc Sanitari Sant Joan de Déu, 08830 Sant Boi de Llobregat, Spain
- Instituto de Investigación Sant Joan de Déu, 08950 Barcelona, Spain
| | - Ana Gómez-Perea
- Department of Pediatric Endocrinology, Hospital Regional Universitario de Málaga, 29011 Málaga, Spain; (A.G.-P.); (P.J.-C.)
- Instituto de Investigación Biomédica de Málaga (IBIMA), 29010 Málaga, Spain;
| | - Ana Cano-Ortiz
- Department of Didactics of Experimental, Social and Mathematical Sciences, Faculty of Education, Complutense University of Madrid, 28040 Madrid, Spain;
| | - Ana B. Ariza-Jiménez
- Department of Pediatric Endocrinology, Hospital Universitario Reina Sofía, 14004 Córdoba, Spain;
- Faculty of Medicine, University of Córdoba, Av. Menéndez Pidal, 7, 14004 Córdoba, Spain
- Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), 14004 Córdoba, Spain
| | | | - Patricia Jiménez-Cuenca
- Department of Pediatric Endocrinology, Hospital Regional Universitario de Málaga, 29011 Málaga, Spain; (A.G.-P.); (P.J.-C.)
| | - María José Picón-César
- Instituto de Investigación Biomédica de Málaga (IBIMA), 29010 Málaga, Spain;
- Department of Endocrinology and Nutrition, Hospital Universitario Virgen de la Victoria, 29010 Málaga, Spain
- Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Isabel Leiva-Gea
- Andalucía Tech, Universidad de Málaga, Campus de Teatinos s/n, 29071 Málaga, Spain;
- Department of Pediatric Endocrinology, Hospital Regional Universitario de Málaga, 29011 Málaga, Spain; (A.G.-P.); (P.J.-C.)
- Instituto de Investigación Biomédica de Málaga (IBIMA), 29010 Málaga, Spain;
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Michou P, Gkiourtzis N, Christoforidis A, Kotanidou EP, Galli-Tsinopoulou A. The efficacy of automated insulin delivery systems in children and adolescents with Type 1 Diabetes Mellitus: a systematic review and meta-analysis of randomized controlled trials. Diabetes Res Clin Pract 2023; 199:110678. [PMID: 37094750 DOI: 10.1016/j.diabres.2023.110678] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 03/28/2023] [Accepted: 04/18/2023] [Indexed: 04/26/2023]
Abstract
AIMS Insulin administration is the treatment of choice for people with type 1 diabetes mellitus (T1D). Technological advances have led to the development of automated insulin delivery (AID) systems, aiming to optimize the quality of life of patients with T1D. We present a systematic review and meta-analysis of the current literature about the efficacy of AID systems in children and adolescents with T1D. METHODS We conducted a systematic literature search for randomized controlled trials (RCTs) until August 8th, 2022, investigating the efficacy of AID systems in the management of patients <21 years of age with T1D. A priori subgroup and sensitivity analyses based on different settings (free-living settings, type of AID system, parallel group or crossover design) were also conducted. RESULTS In total, 26 RCTs reporting a total of 915 children and adolescents with T1D were included in the meta-analysis. AID systems revealed statistically significant differences in the main outcomes, such as the proportion of time in the target glucose range (3.9-10 mmol/L) (p<0.00001), in hypoglycemia (<3.9 mmol/L) (p=0.003) and mean proportion of HbA1C (p=0.0007) compared to control group. CONCLUSIONS According to the present meta-analysis, AID systems are superior to insulin pump therapy, sensor-augmented pumps and multiple daily insulin injections. Most of the included studies have a high risk of bias because of allocation, blinding of patients and blinding of assessment. Our sensitivity analyses showed that patients <21 years of age with T1D can use AID systems, after proper education, following their daily activities. Further RCTs examining the effect of AID systems on nocturnal hypoglycemia, under free-living settings and studies examining the effect of dual-hormone AID systems are pending.
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Affiliation(s)
- Panagiota Michou
- Program of Postgraduate Studies Adolescent Medicine and Adolescent Health Care, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece, 54124; Department of Pediatrics, Gennimatas General Hospital of Thessaloniki, Thessaloniki, Greece, 54635.
| | - Nikolaos Gkiourtzis
- 4th Department of Pediatrics, Papageorgiou General Hospital, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece, 56429.
| | - Athanasios Christoforidis
- 1st Department of Pediatrics, Ippokrateio General Hospital, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece, 54643.
| | - Eleni P Kotanidou
- Program of Postgraduate Studies Adolescent Medicine and Adolescent Health Care, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece, 54124; 2nd Department of Pediatrics, AHEPA University General Hospital, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece, 54636.
| | - Asimina Galli-Tsinopoulou
- Program of Postgraduate Studies Adolescent Medicine and Adolescent Health Care, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece, 54124; 2nd Department of Pediatrics, AHEPA University General Hospital, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece, 54636.
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Bassi M, Franzone D, Dufour F, Strati MF, Scalas M, Tantari G, Aloi C, Salina A, d’Annunzio G, Maghnie M, Minuto N. Automated Insulin Delivery (AID) Systems: Use and Efficacy in Children and Adults with Type 1 Diabetes and Other Forms of Diabetes in Europe in Early 2023. Life (Basel) 2023; 13:783. [PMID: 36983941 PMCID: PMC10053516 DOI: 10.3390/life13030783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2023] [Revised: 03/07/2023] [Accepted: 03/10/2023] [Indexed: 03/17/2023] Open
Abstract
Type 1 diabetes (T1D) patients' lifestyle and prognosis has remarkably changed over the years, especially after the introduction of insulin pumps, in particular advanced hybrid closed loop systems (AHCL). Emerging data in literature continuously confirm the improvement of glycemic control thanks to the technological evolution taking place in this disease. As stated in previous literature, T1D patients are seen to be more satisfied thanks to the use of these devices that ameliorate not only their health but their daily life routine as well. Limited findings regarding the use of new devices in different age groups and types of patients is their major limit. This review aims to highlight the main characteristics of each Automated Insulin Delivery (AID) system available for patients affected by Type 1 Diabetes Mellitus. Our main goal was to particularly focus on these systems' efficacy and use in different age groups and populations (i.e., children, pregnant women). Recent studies are emerging that demonstrate their efficacy and safety in younger patients and other forms of diabetes.
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Affiliation(s)
- Marta Bassi
- IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16126 Genoa, Italy
| | - Daniele Franzone
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16126 Genoa, Italy
| | - Francesca Dufour
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16126 Genoa, Italy
| | - Marina Francesca Strati
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16126 Genoa, Italy
| | - Marta Scalas
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16126 Genoa, Italy
| | - Giacomo Tantari
- IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16126 Genoa, Italy
| | - Concetta Aloi
- LABSIEM (Laboratory for the Study of Inborn Errors of Metabolism), Pediatric Clinic, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy
| | - Alessandro Salina
- LABSIEM (Laboratory for the Study of Inborn Errors of Metabolism), Pediatric Clinic, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy
| | | | - Mohamad Maghnie
- IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, 16126 Genoa, Italy
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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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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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7
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Fushimi E, De Battista H, Garelli F. A Dual-Hormone Multicontroller for Artificial Pancreas Systems. IEEE J Biomed Health Inform 2022; 26:4743-4750. [PMID: 35704538 DOI: 10.1109/jbhi.2022.3182581] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Artificial pancreas (AP) algorithms can be divided into single-hormone (SH) and dual-hormone (DH). SH algorithms regulate glycemia using insulin as their control input. On the other hand, DH algorithms also use glucagon to counteract insulin. While SH-AP systems are already commercially available, DH-AP systems are still in an earlier research phase. DH-AP systems have been questioned since the added complexity of glucagon infusion does not always guarantee hypoglycemia prevention and might significantly raise insulin delivery. In this work, a DH multicontroller is proposed based on a SH linear quadratic gaussian (LQG) algorithm with an additional LQG controller to deliver glucagon. This strategy has a switched structure that allows activating one of the following three controllers when necessary: a conservative insulin LQG controller to modulate basal delivery ( K1), an aggressive insulin LQG controller to counteract meals ( K2), or a glucagon LQG controller to avoid imminent hypoglycemia ( K3). Here, an in silico study of the benefits of incorporating controller K3 is carried out. Intra-patient variability and mixed meals are considered. Results indicate that the proposed switched, dual-hormone strategy yields to a reduction in hypoglycemia without increasing hyperglycemia, with no significant rise in insulin delivery.
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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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Pinsker JE, Bartee A, Katz M, Lalonde A, Jones R, Dassau E, Wolpert H. Predictive Low-Glucose Suspend Necessitates Less Carbohydrate Supplementation to Rescue Hypoglycemia: Need to Revisit Current Hypoglycemia Treatment Guidelines. Diabetes Technol Ther 2021; 23:512-516. [PMID: 33535013 PMCID: PMC8252907 DOI: 10.1089/dia.2020.0619] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Current guidelines recommend 15-20 g of carbohydrate (CHO) for treatment of mild to moderate hypoglycemia. However, these guidelines do not account for reduced insulin during suspensions with predictive low-glucose suspend (PLGS). We assessed insulin suspensions, hypoglycemic events, and CHO treatment during a 20-h inpatient evaluation of an investigational system with a PLGS feature, including an overnight basal up-titration period to activate the PLGS. Among 10 adults with type 1 diabetes, there were 59 suspensions; 7 suspensions were associated with rescue CHO and 5 with hypoglycemia. Rescue treatment consisted of median 9 g CHO (range: 5-16 g), with no events requiring repeat CHO. No rescue CHO were given during or after insulin suspension for the overnight basal up-titration. To minimize rebound hyperglycemia and needless calorie intake from hypoglycemia overtreatment, updated guidance for PLGS systems should reflect possible need to reduce CHO amounts for hypoglycemia rescue associated with an insulin suspension. The clinical trial was registered with ClinicalTrials.gov (NCT03890003).
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Affiliation(s)
| | - Amy Bartee
- Eli Lilly and Company, Indianapolis, Indiana, USA
| | | | - Amy Lalonde
- Eli Lilly and Company, Indianapolis, Indiana, USA
| | | | - Eyal Dassau
- Eli Lilly and Company, Cambridge, Massachusetts, USA
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Colmegna P, Cengiz E, Garcia-Tirado J, Kraemer K, Breton MD. Impact of Accelerating Insulin on an Artificial Pancreas System Without Meal Announcement: An In Silico Examination. J Diabetes Sci Technol 2021; 15:833-841. [PMID: 32546001 PMCID: PMC8258534 DOI: 10.1177/1932296820928067] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Controlling postprandial blood glucose without the benefit of an appropriately sized premeal insulin bolus has been challenging given the delays in absorption and action of subcutaneously injected insulin during conventional and artificial pancreas (AP) system diabetes treatment. We aim to understand the impact of accelerating insulin and increasing aggressiveness of the AP controller as potential solutions to address the postprandial hyperglycemia challenge posed by unannounced meals through a simulation study. METHODS Accelerated rapid-acting insulin analogue is modeled within the UVA/Padova simulation platform by uniformly reducing its pharmacokinetic time constants (α multiplier) and used with a model predictive control, where the controller's aggressiveness depends on α. Two sets of single-meal simulations were performed: (1) where we only tune the controller's aggressiveness and (2) where we also accelerate insulin absorption and action to assess postprandial glycemic control during each intervention. RESULTS Mean percent of time spent within the 70 to 180 mg/dL postprandial glycemic range is significantly higher in set (2) than in set (1): 79.9, 95% confidence interval [77.0, 82.7] vs 88.8 [86.8, 90.9] ([Note to typesetter: Set all unnecessary math in text format and insert appropriate spaces between operators.] P < .05) for α = 2, and 81.4 [78.6, 84.3] vs 94.1 [92.6, 95.6] (P < .05) for α = 3. A decrease in percent of time below 70 mg/dL is also detected: 0.9 [0.4, 2.2] vs 0.6 [0.2, 1.4] (P = .23) for α = 2 and 1.4 [0.7, 2.8] vs 0.4 [0.1, 1.4] (P < .05) for α = 3. CONCLUSION These proof-of-concept simulations suggest that an AP without prandial insulin boluses combined with significantly faster insulin analogues could match the glycemic performance obtained with an optimal hybrid AP.
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Affiliation(s)
- Patricio Colmegna
- Center for Diabetes Technology, University of Virginia, Charlottesville, USA
- National Scientific and Technical Research Council, Buenos Aires, Argentina
- Patricio Colmegna, PhD, Center for Diabetes Technology, University of Virginia, 560 Ray C Hunt Dr, Charlottesville, VA 22903, USA.
| | - Eda Cengiz
- Division of Pediatric Endocrinology and Diabetes, Yale University School of Medicine, New Haven, CT, USA
- Bahcesehir University School of Medicine, Istanbul, Turkey
| | - Jose Garcia-Tirado
- Center for Diabetes Technology, University of Virginia, Charlottesville, USA
| | - Kristen Kraemer
- Division of Pediatric Endocrinology and Diabetes, Yale University School of Medicine, New Haven, CT, USA
| | - Marc D. Breton
- Center for Diabetes Technology, University of Virginia, Charlottesville, USA
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Atif Z, Halstrom A, Peragallo-Dittko V, Klek SP. Efficacy of Hybrid Closed-Loop Insulin Delivery System in a Hospital Setting: A Case Series. AACE Clin Case Rep 2021; 7:184-188. [PMID: 34095484 PMCID: PMC8165117 DOI: 10.1016/j.aace.2020.12.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 11/17/2020] [Accepted: 12/01/2020] [Indexed: 11/29/2022] Open
Abstract
Objective We report a case series of 4 patients with type 1 diabetes who used hybrid closed-loop insulin pumps (Medtronic MiniMed 670 G) during hospitalization. Methods Clinical data and point-of-care glucose values are presented for each patient. Glucose values are shown graphically while in manual mode as well as in auto mode. Results The first case was a 30-year-old man admitted for pancreatitis. Mean point-of-care blood glucose was 165.7 mg/dL while in auto mode, without hypoglycemia, compared with 221 mg/dL while in manual mode. The second case was a 28-year-old woman who was admitted for a laparoscopic cholecystectomy. Mean point-of-care blood glucose in auto mode was 131.3 mg/dL, without hypoglycemia, compared with 117.6 mg/dL while in manual mode. The third case was a 46-year-old man admitted to the intensive care unit for influenzal pneumonia. Mean point-of-care blood glucose in auto mode was 159.1 mg/dL without hypoglycemia, compared with 218.5 mg/dL while in manual mode. The fourth case was a 60-year-old man who remained in auto mode throughout his hospitalization except for a period when he removed his pump for an endoscopic retrograde cholangiopancreatography and endoscopic ultrasound. His mean point-of-care blood glucose while in auto mode was 156.8 mg/dL without hypoglycemia. Conclusion These case reports support the use of hybrid closed-loop insulin-pump therapy in the inpatient setting to maintain inpatient glycemic targets and avoid hypoglycemia when part of an institution-sanctioned strategy for safe use of insulin pumps that includes point-of-care blood glucose monitoring.
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Affiliation(s)
- Zulekha Atif
- Department of Endocrinology, Overlook Medical Center, Atlantic Health System, Summit, New Jersey
| | - Amanda Halstrom
- Department of Medicine, NYU Long Island School of Medicine, Mineola, New York
| | | | - Stanislaw P Klek
- Division of Endocrinology, NYU Long Island School of Medicine, Mineola, New York
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12
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Dovc K, Battelino T. Time in range centered diabetes care. Clin Pediatr Endocrinol 2021; 30:1-10. [PMID: 33446946 PMCID: PMC7783127 DOI: 10.1297/cpe.30.1] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 09/17/2020] [Indexed: 12/11/2022] Open
Abstract
Optimal glycemic control remains challenging and elusive for many people with diabetes. With the comprehensive clinical evidence on safety and efficiency in large populations, and with broader reimbursement, the adoption of continuous glucose monitoring (CGM) is rapidly increasing. Standardized visual reporting and interpretation of CGM data and clear and understandable clinical targets will help professionals and individuals with diabetes use diabetes technology more efficiently, and finally improve long-term outcomes with less everyday disease burden. For the majority of people with type 1 or type 2 diabetes, time in range (between 70 and 180 mg/dL, or 3.9 and 10 mmol/L) target of more than 70% is recommended, with each incremental increase of 5% towards this target being clinically meaningful. At the same time, the goal is to minimize glycemic excursions: a recommended target for a time below range (< 70 mg/dL or < 3.9 mmol/L) is less than 4%, and time above range (> 180 mg/dL or 10 mmol/L) less than 25%, with less stringent goals for older individuals or those at increased risk. These targets should be individualized: the personal use of CGM with the standardized data presentation provides all necessary means to accurately tailor diabetes management to the needs of each individual with diabetes.
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Affiliation(s)
- Klemen Dovc
- University Children's Hospital, University Medical Center Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Tadej Battelino
- University Children's Hospital, University Medical Center Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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13
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Joseph JI. Review of the Long-Term Implantable Senseonics Continuous Glucose Monitoring System and Other Continuous Glucose Monitoring Systems. J Diabetes Sci Technol 2021; 15:167-173. [PMID: 32345047 PMCID: PMC7783000 DOI: 10.1177/1932296820911919] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The article published by Kevin Cowart in this issue of the Journal of Diabetes Science and Technology (JDST) is a detailed overview of the clinical trial data and analysis used to demonstrate the safety and effectiveness of the Eversense continuous glucose monitoring (CGM) System for regulatory approval and clinical acceptance. The article describes the published study results for safety, accuracy, reliability, ease of insertion/removal, adverse events, and ease of diabetes patient-use for controlling their glucose levels short and long term. The author nicely compares Eversense CGM System safety and performance with the short-term subcutaneous tissue CGM systems being commercialized by Dexcom, Medtronic Diabetes, and Abbott Diabetes. This comparison may help the clinician define which type of patient with diabetes might benefit the most from the long-term implantable CGM system. The majority of studied patients describe a positive experience managing their diabetes with the Eversense CGM System and request implantation of a new sensor 90 or 180 days later.
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Affiliation(s)
- Jeffrey I. Joseph
- Jeffrey I. Joseph, DO, Department of Anesthesiology, Sidney Kimmel Medical College, Jefferson Artificial Pancreas Center, Thomas Jefferson University, 1020 Locust Street, JAH # 565, Philadelphia, PA 19072, USA.
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14
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Herzog AL, Busch J, Wanner C, von Jouanne-Diedrich HK. Survey about do-it-yourself closed loop systems in the treatment of diabetes in Germany. PLoS One 2020; 15:e0243465. [PMID: 33332410 PMCID: PMC7746287 DOI: 10.1371/journal.pone.0243465] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Accepted: 11/22/2020] [Indexed: 11/19/2022] Open
Abstract
Continuous glucose monitoring (CGM) improves treatment with lower blood glucose levels and less patient effort. In combination with continuous insulin application, glycemic control improves and hypoglycemic episodes should decrease. Direct feedback of CGM to continuous subcutaneous insulin application, using an algorithm is called a closed-loop (CL) artificial pancreas system. Commercial devices stop insulin application by predicting hypoglycemic blood glucose levels through direct interaction between the sensor and pump. The prediction is usually made for about 30 minutes and insulin delivery is restarted at the previous level if a rise in blood glucose is predicted within the next 30 minutes (hybrid closed loop system, HCL this is known as a predictive low glucose suspend system (PLGS)). In a fully CL system, sensor and pump communicate permanently with each other. Hybrid closed-loop (HCL) systems, which require the user to estimate the meal size and provide a meal insulin basis, are commercially available in Germany at the moment. These systems result in fewer hyperglycemic and hypoglycemic episodes with improved glucose control. Open source initiatives have provided support by building do-it-yourself CL (DIYCL) devices for automated insulin application since 2014, and are used by a tech-savvy subgroup of patients. The first commercial hybrid CL system has been available in Germany since September 2019. We surveyed 1054 patients to determine which devices are currently used, which features would be in demand by potential users, and the benefits of DIYCL systems. 9.7% of these used a DIYCL system, while 50% would most likely trust these systems but more than 85% of the patients would use a commercial closed loop system, if available. The DIYCL users had a better glucose control regarding their time in range (TIR) and glycated hemoglobin (HbA1c).
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Affiliation(s)
- Anna Laura Herzog
- Division of Nephrology, Transplantationszentrum, University of Würzburg, Universitätsklinikum, Würzburg, Germany
- * E-mail:
| | - Jonas Busch
- TH Aschaffenburg (University of Applied Sciences), Aschaffenburg, Germany
| | - Christoph Wanner
- Division of Nephrology, Medizinische Klinik I, University of Würzburg, Universitätsklinikum, Würzburg, Germany
| | - Holger K. von Jouanne-Diedrich
- Competence Center for Artificial Intelligence, Faculty of Engineering, TH Aschaffenburg (University of Applied Sciences), Aschaffenburg, Germany
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15
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Dovc K, Battelino T. Closed-loop insulin delivery systems in children and adolescents with type 1 diabetes. Expert Opin Drug Deliv 2020; 17:157-166. [PMID: 32077342 DOI: 10.1080/17425247.2020.1713747] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Introduction: Optimal glycemic control remains challenging in children and adolescents with type 1 diabetes due to highly variable day-to-day and night-to-night insulin requirements. This hurdle could be addressed by glucose-responsive insulin delivery based on real-time continuous glucose measurements.Areas covered: This review summaries recent advances of closed-loop systems in children and adolescents with type 1 diabetes, using both single- and dual-hormone closed-loop systems. The main outcomes, proportions of time spent in target range 70-180 mg/dl, and time spent in hypoglycemia below 70 mg/dl, are assessed particularly during unsupervised free-living randomized controlled trials.Expert opinion: Noteworthy and clinically meaningful translation of experimental investigations from controlled in-hospital settings to unrestricted home studies have been achieved over the past years, resulting in the regulatory approval of the first hybrid closed-loop system also in the pediatric population and with several other advanced devices in the pipeline. Large multinational and pivotal clinical trials including broad age populations are underway to facilitate the use of closed-loop systems in routine clinical practice.
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Affiliation(s)
- Klemen Dovc
- Department of Paediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children's Hospital, Ljubljana, Slovenia.,Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Tadej Battelino
- Department of Paediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children's Hospital, Ljubljana, Slovenia.,Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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16
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Cobry EC, Hamburger E, Jaser SS. Impact of the Hybrid Closed-Loop System on Sleep and Quality of Life in Youth with Type 1 Diabetes and Their Parents. Diabetes Technol Ther 2020; 22:794-800. [PMID: 32212971 PMCID: PMC7698988 DOI: 10.1089/dia.2020.0057] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Background: Insufficient sleep is common in youth with type 1 diabetes (T1D) and parents, likely secondary to diabetes-related disturbances, including fear of hypoglycemia, nocturnal glucose monitoring, hypoglycemia, and device alarms. Hybrid closed-loop (HCL) systems improve glycemic variability and potentially reduce nocturnal awakenings. Methods: Adolescents with T1D (N = 37, mean age 13.9 years, 62% female, mean HbA1c 8.3%) and their parents were enrolled in this observational study when starting the Medtronic 670G HCL system. Participants completed study measures (sleep and psychosocial surveys and actigraphy with sleep diaries) before starting auto mode and ∼3 months later. Results: Based on actigraphy data, neither adolescents' nor parents' sleep characteristics changed significantly pre-post device initiation. Adolescents' mean total sleep time decreased from 7 h 16 min (IQR: [6:43-7:47]) to 7 h 9 min (IQR: [6:44-7:52]), while parents' total sleep time decreased from 6 h 47 min (IQR: [6:16-7:10]) to 6 h 38 min (IQR: [5:57-6:57]). Although there were no significant differences in most of the survey measures, there was a moderate effect for improved sleep quality in parents and fear of hypoglycemia in adolescents. In addition, adolescents reported a significant increase in self-reported glucose monitoring satisfaction. Adolescents averaged 44.7% use of auto mode at 3 months. Conclusions: Our data support previous research showing youth with T1D and their parents are not achieving the recommended duration of sleep. Lack of improvement in sleep may be due to steep learning curves involved with new technology. We observed moderate improvements in parental subjective report of sleep quality despite no change in objective measures of sleep duration. Further evaluation of sleep with long-term HCL use and larger sample size is needed.
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Affiliation(s)
- Erin C. Cobry
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, Colorado, USA
- Address correspondence to: Erin C. Cobry, MD, Barbara Davis Center, University of Colorado School of Medicine, 1775 Aurora Court, MSA140, Aurora, CO 80045
| | - Emily Hamburger
- Department of Psychology Univeristy of Nebraska-Lincoln, Lincoln, Nebraska, USA
| | - Sarah S. Jaser
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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17
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Automatic glycemic regulation for the pediatric population based on switched control and time-varying IOB constraints: an in silico study. Med Biol Eng Comput 2020; 58:2325-2337. [PMID: 32710375 DOI: 10.1007/s11517-020-02213-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Accepted: 06/25/2020] [Indexed: 10/23/2022]
Abstract
Artificial pancreas (AP) systems have shown to improve glucose regulation in type 1 diabetes (T1D) patients. However, full closed-loop performance remains a challenge particularly in children and adolescents, since these age groups often present the worst glycemic control. In this work, an algorithm based on switched control and time-varying IOB constraints is presented. The proposed control strategy is evaluated in silico using the FDA-approved UVA/ Padova simulator and its performance contrasted with the previously introduced Automatic Regulation of Glucose (ARG) algorithm in the pediatric population. The effect of unannounced meals is also explored. Results indicate that the proposed strategy achieves lower hypo- and hyperglycemia than the ARG for both announced and unannounced meals. Graphical Abstract Block diagram and illustrative example of insulin and glucose evolution over time for the proposed algorithm (ARGAE).
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18
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Palisaitis E, El Fathi A, Von Oettingen JE, Krishnamoorthy P, Kearney R, Jacobs P, Rutkowski J, Legault L, Haidar A. The Efficacy of Basal Rate and Carbohydrate Ratio Learning Algorithm for Closed-Loop Insulin Delivery (Artificial Pancreas) in Youth with Type 1 Diabetes in a Diabetes Camp. Diabetes Technol Ther 2020; 22:185-194. [PMID: 31596127 DOI: 10.1089/dia.2019.0270] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Background: Optimizing programmed basal rates and carbohydrate ratios may improve the performance of the artificial pancreas. We tested, in a diabetes camp, the efficacy of a learning algorithm that updates daily basal rates and carbohydrate ratios in the artificial pancreas. Materials and Methods: We conducted a randomized crossover trial in campers and counselors aged 8-21 years with type 1 diabetes on pump therapy. Participants underwent 2 days of artificial pancreas alone and 6 days of artificial pancreas with learning. During the artificial pancreas with learning, programmed basal rates and carbohydrate ratios were updated daily based on the learning algorithm's recommendations. All algorithm recommendations were reviewed for safety by camp physicians. The primary outcome was the time in target range (3.9-10 mmol/L) of the last 2 days of each intervention. Results: Thirty-four campers (age 13.9 ± 3.9, hemoglobin A1c 8.3% ± 0.2%) were included. Ninety-six percent of algorithm recommendations were approved by the camp physicians. Participants were in closed-loop mode 74% of the time. There was no difference between interventions in time in target (55%-55%; P = 0.71) nor in hypoglycemia events (0.8-0.9 events per day; P = 0.63). This was despite changes in programmed basal rate ranging from -21% to +117%, and changes in breakfast, lunch, and supper carbohydrate ratios from -17% to +40%, -36% to +37%, and -35% to +63%, respectively. Morever, postprandial hyperglycemia and hypoglycemia did not decrease in participants whose carbohydrate ratios were decreased (more insulin boluses) and increased (less insulin boluses), respectively. Conclusions: In camp settings, despite adjustments to programmed basal rates and carbohydrate ratios, the learning algorithm did not change glycemia, which may point toward limited effect of these adjustments in environments with large day-to-day variability in insulin needs. Longer randomized studies in real-world settings are required to further assess the efficacy of automatic adjustments of programmed basal rates and carbohydrate ratios.
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Affiliation(s)
- Emilie Palisaitis
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Canada
| | - Anas El Fathi
- Department of Electrical and Computer Engineering, Faculty of Engineering, McGill University, Montreal, Canada
| | - Julia E Von Oettingen
- Department of Pediatric Endocrinology, McGill University Health Centre, Montreal Children's Hospital, Montreal, Canada
- The Research Institute of McGill University Health Centre, Montreal, Canada
| | - Preetha Krishnamoorthy
- Department of Pediatric Endocrinology, McGill University Health Centre, Montreal Children's Hospital, Montreal, Canada
| | - Robert Kearney
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Canada
| | - Peter Jacobs
- Department of Biomedical Engineering, Oregon Health and Science University, Portland, Oregon
| | - Joanna Rutkowski
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Canada
| | - Laurent Legault
- Department of Pediatric Endocrinology, McGill University Health Centre, Montreal Children's Hospital, Montreal, Canada
- The Research Institute of McGill University Health Centre, Montreal, Canada
| | - Ahmad Haidar
- Department of Biomedical Engineering, Faculty of Medicine, McGill University, Montreal, Canada
- The Research Institute of McGill University Health Centre, Montreal, Canada
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19
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Yu X, Rashid M, Feng J, Hobbs N, Hajizadeh I, Samadi S, Sevil M, Lazaro C, Maloney Z, Littlejohn E, Quinn L, Cinar A. Online Glucose Prediction Using Computationally Efficient Sparse Kernel Filtering Algorithms in Type-1 Diabetes. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY : A PUBLICATION OF THE IEEE CONTROL SYSTEMS SOCIETY 2020; 28:3-15. [PMID: 32699492 PMCID: PMC7375403 DOI: 10.1109/tcst.2018.2843785] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Streaming data from continuous glucose monitoring (CGM) systems enable the recursive identification of models to improve estimation accuracy for effective predictive glycemic control in patients with type-1 diabetes. A drawback of conventional recursive identification techniques is the increase in computational requirements, which is a concern for online and real-time applications such as the artificial pancreas systems implemented on handheld devices and smartphones where computational resources and memory are limited. To improve predictions in such computationally constrained hardware settings, efficient adaptive kernel filtering algorithms are developed in this paper to characterize the nonlinear glycemic variability by employing a sparsification criterion based on the information theory to reduce the computation time and complexity of the kernel filters without adversely deteriorating the predictive performance. Furthermore, the adaptive kernel filtering algorithms are designed to be insensitive to abnormal CGM measurements, thus compensating for measurement noise and disturbances. As such, the sparsification-based real-time model update framework can adapt the prediction models to accurately characterize the time-varying and nonlinear dynamics of glycemic measurements. The proposed recursive kernel filtering algorithms leveraging sparsity for improved computational efficiency are applied to both in-silico and clinical subjects, and the results demonstrate the effectiveness of the proposed methods.
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Affiliation(s)
- Xia Yu
- School of Information Science and Engineering, Northeastern University, Shenyang 110819, China
| | - Mudassir Rashid
- Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL 60616 USA
| | - Jianyuan Feng
- Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL 60616 USA
| | - Nicole Hobbs
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL 60616 USA
| | - Iman Hajizadeh
- Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL 60616 USA
| | - Sediqeh Samadi
- Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL 60616 USA
| | - Mert Sevil
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL 60616 USA
| | - Caterina Lazaro
- Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL 60616 USA
| | - Zacharie Maloney
- Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL 60616 USA
| | - Elizabeth Littlejohn
- Kovler Diabetes Center, Department of Pediatrics and Medicine, University of Chicago, Chicago, IL 60637 USA
| | - Laurie Quinn
- Department of Biobehavioral Health Science, College of Nursing, University of Illinois at Chicago, Chicago, IL 60612 USA
| | - Ali Cinar
- Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL 60616 USA, and also with the Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL 60616 USA
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20
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Lal RA, Basina M, Maahs DM, Hood K, Buckingham B, Wilson DM. One Year Clinical Experience of the First Commercial Hybrid Closed-Loop System. Diabetes Care 2019; 42:2190-2196. [PMID: 31548247 PMCID: PMC6868462 DOI: 10.2337/dc19-0855] [Citation(s) in RCA: 155] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Accepted: 08/31/2019] [Indexed: 02/03/2023]
Abstract
OBJECTIVE In September 2016, the U.S. Food and Drug Administration approved the Medtronic 670G "hybrid" closed-loop system. In Auto Mode, this system automatically controls basal insulin delivery based on continuous glucose monitoring data but requires users to enter carbohydrates and blood glucose for boluses. To track real-world experience with this first commercial closed-loop device, we prospectively followed pediatric and adult patients starting the 670G system. RESEARCH DESIGN AND METHODS This was a 1-year prospective observational study of patients with type 1 diabetes starting the 670G system between May 2017 and May 2018 in clinic. RESULTS Of the total of 84 patients who received 670G and consented, 5 never returned for follow-up, with 79 (aged 9-61 years) providing data at 1 week and 3, 6, 9, and/or 12 months after Auto Mode initiation. For the 86% (68 out of 79) with 1-week data, 99% (67 out of 68) successfully started. By 3 months, at least 28% (22 out of 79) had stopped using Auto Mode; at 6 months, 34% (27 out of 79); at 9 months, 35% (28 out of 79); and by 12 months, 33% (26 out of 79). The primary reason for continuing Auto Mode was desire for increased time in range. Reasons for discontinuation included sensor issues in 62% (16 out of 26), problems obtaining supplies in 12% (3 out of 26), hypoglycemia fear in 12% (3 out of 26), multiple daily injection preference in 8% (2 out of 26), and sports in 8% (2 out of 26). At all visits, there was a significant correlation between hemoglobin A1c (HbA1c) and Auto Mode utilization. CONCLUSIONS While Auto Mode utilization correlates with improved glycemic control, a focus on usability and human factors is necessary to ensure use of Auto Mode. Alarms and sensor calibration are a major patient concern, which future technology should alleviate.
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Affiliation(s)
- Rayhan A Lal
- Division of Endocrinology, Department of Medicine, Stanford University School of Medicine, Stanford, CA
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford, CA
| | - Marina Basina
- Division of Endocrinology, Department of Medicine, Stanford University School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford, CA
| | - David M Maahs
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford, CA
| | - Korey Hood
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford, CA
| | - Bruce Buckingham
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford, CA
| | - Darrell M Wilson
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA
- Stanford Diabetes Research Center, Stanford, CA
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21
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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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22
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Fushimi E, Colmegna P, De Battista H, Garelli F, Sánchez-Peña R. Artificial Pancreas: Evaluating the ARG Algorithm Without Meal Announcement. J Diabetes Sci Technol 2019; 13:1035-1043. [PMID: 31339059 PMCID: PMC6835180 DOI: 10.1177/1932296819864585] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Either under standard basal-bolus treatment or hybrid closed-loop control, subjects with type 1 diabetes are required to count carbohydrates (CHOs). However, CHO counting is not only burdensome but also prone to errors. Recently, an artificial pancreas algorithm that does not require premeal insulin boluses-the so-called automatic regulation of glucose (ARG)-was introduced. In its first pilot clinical study, although the exact CHO counting was not required, subjects still needed to announce the meal time and classify the meal size. METHOD An automatic switching signal generator (SSG) is proposed in this work to remove the manual mealtime announcement from the control strategy. The SSG is based on a Kalman filter and works with continuous glucose monitoring readings only. RESULTS The ARG algorithm with unannounced meals (ARGum) was tested in silico under the effect of different types of mixed meals and intrapatient variability, and contrasted with the ARG algorithm with announced meals (ARGam). Simulations reveal that, for slow-absorbing meals, the time in the euglycemic range, [70-180] mg/dL, increases using the unannounced strategy (ARGam: 78.1 [68.6-80.2]% (median [IQR]) and ARGum: 87.8 [84.5-90.6]%), while similar results were found with fast-absorbing meals (ARGam: 87.4 [86.0-88.9]% and ARGum: 87.6 [86.1-88.8]%). On the other hand, when intrapatient variability is considered, time in euglycemia is also comparable (ARGam: 81.4 [75.4-83.5]% and ARGum: 80.9 [77.0-85.1]%). CONCLUSION In silico results indicate that it is feasible to perform an in vivo evaluation of the ARG algorithm with unannounced meals.
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Affiliation(s)
- Emilia Fushimi
- Grupo de Control Aplicado (GCA), Instituto LEICI (UNLP-CONICET), Facultad de Ingeniería, Universidad Nacional de La Plata (UNLP), Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Argentina
- Emilia Fushimi. Instituto LEICI (Grupo de Control Aplicado), Depto. Electrotecnia, Facultad de Ingeniería, Universidad Nacional de La Plata (UNLP),, Calle 48 y116, La Plata 1900, Argentina.
| | - Patricio Colmegna
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Argentina
- University of Virginia (UVA), Center for Diabetes Technology, Charlottesville, VA, USA
- Universidad Nacional de Quilmes (UNQ), Argentina
| | - Hernán De Battista
- Grupo de Control Aplicado (GCA), Instituto LEICI (UNLP-CONICET), Facultad de Ingeniería, Universidad Nacional de La Plata (UNLP), Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Argentina
| | - Fabricio Garelli
- Grupo de Control Aplicado (GCA), Instituto LEICI (UNLP-CONICET), Facultad de Ingeniería, Universidad Nacional de La Plata (UNLP), Argentina
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Argentina
| | - Ricardo Sánchez-Peña
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) Argentina
- Universidad Nacional de Quilmes (UNQ), Argentina
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23
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Ekhlaspour L, Nally LM, El-Khatib FH, Ly TT, Clinton P, Frank E, Tanenbaum ML, Hanes SJ, Selagamsetty RR, Hood K, Damiano ER, Buckingham BA. Feasibility Studies of an Insulin-Only Bionic Pancreas in a Home-Use Setting. J Diabetes Sci Technol 2019; 13:1001-1007. [PMID: 31470740 PMCID: PMC6835195 DOI: 10.1177/1932296819872225] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND We tested the safety and performance of the "insulin-only" configuration of the bionic pancreas (BP) closed-loop blood-glucose control system in a home-use setting to assess glycemic outcomes using different static and dynamic glucose set-points. METHOD This is an open-label non-randomized study with three consecutive intervention periods. Participants had consecutive weeks of usual care followed by the insulin-only BP with (1) an individualized static set-point of 115 or 130 mg/dL and (2) a dynamic set-point that automatically varied within 110 to 130 mg/dL, depending on hypoglycemic risk. Human factors (HF) testing was conducted using validated surveys. The last five days of each study arm were used for data analysis. RESULTS Thirteen participants were enrolled with a mean age of 28 years, mean A1c of 7.2%, and mean daily insulin dose of 0.6 U/kg (0.4-1.0 U/kg). The usual care arm had an average glucose of 145 ± 20 mg/dL, which increased in the static set-point arm (159 ± 8 mg/dL, P = .004) but not in the dynamic set-point arm (154 ± 10 mg/dL, P = ns). There was no significant difference in time spent in range (70-180 mg/dL) among the three study arms. There was less time <70 mg/dL with both the static (1.8% ± 1.4%, P = .009) and dynamic set-point (2.7±1.5, P = .051) arms compared to the usual-care arm (5.5% ± 4.2%). HF testing demonstrated preliminary user satisfaction and no increased risk of diabetes burden or distress. CONCLUSIONS The insulin-only configuration of the BP using either static or dynamic set-points and initialized only with body weight performed similarly to other published insulin-only systems.
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Affiliation(s)
- Laya Ekhlaspour
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Laya Ekhlaspour, MD, Pediatric Endocrinology and Diabetes, Lucille Packard Children’s Hospital at Stanford, 780 Welch Road, Stanford, CA 94305, USA.
| | - Laura M. Nally
- Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Firas H. El-Khatib
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Trang T. Ly
- Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Paula Clinton
- Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Eliana Frank
- Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Molly L. Tanenbaum
- Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Sarah J. Hanes
- Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Palo Alto, CA, USA
| | | | - Korey Hood
- Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Edward R. Damiano
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Bruce A. Buckingham
- Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Palo Alto, CA, USA
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24
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Bowers DT, Song W, Wang LH, Ma M. Engineering the vasculature for islet transplantation. Acta Biomater 2019; 95:131-151. [PMID: 31128322 PMCID: PMC6824722 DOI: 10.1016/j.actbio.2019.05.051] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 04/13/2019] [Accepted: 05/20/2019] [Indexed: 12/17/2022]
Abstract
The microvasculature in the pancreatic islet is highly specialized for glucose sensing and insulin secretion. Although pancreatic islet transplantation is a potentially life-changing treatment for patients with insulin-dependent diabetes, a lack of blood perfusion reduces viability and function of newly transplanted tissues. Functional vasculature around an implant is not only necessary for the supply of oxygen and nutrients but also required for rapid insulin release kinetics and removal of metabolic waste. Inadequate vascularization is particularly a challenge in islet encapsulation. Selectively permeable membranes increase the barrier to diffusion and often elicit a foreign body reaction including a fibrotic capsule that is not well vascularized. Therefore, approaches that aid in the rapid formation of a mature and robust vasculature in close proximity to the transplanted cells are crucial for successful islet transplantation or other cellular therapies. In this paper, we review various strategies to engineer vasculature for islet transplantation. We consider properties of materials (both synthetic and naturally derived), prevascularization, local release of proangiogenic factors, and co-transplantation of vascular cells that have all been harnessed to increase vasculature. We then discuss the various other challenges in engineering mature, long-term functional and clinically viable vasculature as well as some emerging technologies developed to address them. The benefits of physiological glucose control for patients and the healthcare system demand vigorous pursuit of solutions to cell transplant challenges. STATEMENT OF SIGNIFICANCE: Insulin-dependent diabetes affects more than 1.25 million people in the United States alone. Pancreatic islets secrete insulin and other endocrine hormones that control glucose to normal levels. During preparation for transplantation, the specialized islet blood vessel supply is lost. Furthermore, in the case of cell encapsulation, cells are protected within a device, further limiting delivery of nutrients and absorption of hormones. To overcome these issues, this review considers methods to rapidly vascularize sites and implants through material properties, pre-vascularization, delivery of growth factors, or co-transplantation of vessel supporting cells. Other challenges and emerging technologies are also discussed. Proper vascular growth is a significant component of successful islet transplantation, a treatment that can provide life-changing benefits to patients.
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Affiliation(s)
- Daniel T Bowers
- Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA
| | - Wei Song
- Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA
| | - Long-Hai Wang
- Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA
| | - Minglin Ma
- Department of Biological and Environmental Engineering, Cornell University, Ithaca, NY 14853, USA.
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25
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Abstract
IN BRIEF Automated insulin delivery (AID; also known as artificial pancreas) has improved the regulation of blood glucose concentrations, reduced the frequency of hyperglycemic and hypoglycemic episodes, and improved the quality of life of people with diabetes and their families. Three different types of algorithms-proportional-integral-derivative control, model predictive control, and fuzzy-logic knowledge-based systems-have been used in AID control systems. This article will highlight the foundations of these algorithms and discuss their strengths and limitations. Multivariable artificial pancreas and dual-hormone (insulin and glucagon) systems will be introduced.
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Affiliation(s)
- Ali Cinar
- Departments of Chemical and Biological Engineering and Biomedical Engineering, Engineering Center for Diabetes Research and Education, Illinois Institute of Technology, Chicago, IL
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26
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Cobry EC, Jaser SS. Brief Literature Review: The Potential of Diabetes Technology to Improve Sleep in Youth With Type 1 Diabetes and Their Parents: An Unanticipated Benefit of Hybrid Closed-Loop Insulin Delivery Systems. Diabetes Spectr 2019; 32:284-287. [PMID: 31462886 PMCID: PMC6695262 DOI: 10.2337/ds18-0098] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Affiliation(s)
- Erin C Cobry
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN
| | - Sarah S Jaser
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN
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27
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Hajizadeh I, Rashid M, Cinar A. Plasma-Insulin-Cognizant Adaptive Model Predictive Control for Artificial Pancreas Systems. JOURNAL OF PROCESS CONTROL 2019; 77:97-113. [PMID: 31814659 PMCID: PMC6897508 DOI: 10.1016/j.jprocont.2019.03.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/06/2023]
Abstract
An adaptive model predictive control (MPC) algorithm with dynamic adjustments of constraints and objective function weights based on estimates of the plasma insulin concentration (PIC) is proposed for artificial pancreas (AP) systems. A personalized compartment model that translates the infused insulin into estimates of PIC is integrated with a recursive subspace-based system identification to characterize the transient dynamics of glycemic measurements. The system identification approach is able to identify stable, reliable linear time-varying models from closed-loop data. An MPC algorithm using the adaptive models is designed to compute the optimal exogenous insulin delivery for AP systems without requiring any manually-entered meal information. A dynamic safety constraint derived from the estimation of PIC is incorporated in the adaptive MPC to improve the efficacy of the AP and prevent insulin overdosing. Simulation case studies demonstrate the performance of the proposed adaptive MPC algorithm.
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Affiliation(s)
- Iman Hajizadeh
- Dept of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL 60616
| | - Mudassir Rashid
- Dept of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL 60616
| | - Ali Cinar
- Dept of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL 60616
- Dept of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL 60616
- Correspondence concerning this article should be addressed to A. Cinar at
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28
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Luckett DJ, Laber EB, Kahkoska AR, Maahs DM, Mayer-Davis E, Kosorok MR. Estimating Dynamic Treatment Regimes in Mobile Health Using V-learning. J Am Stat Assoc 2019; 115:692-706. [PMID: 32952236 DOI: 10.1080/01621459.2018.1537919] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
The vision for precision medicine is to use individual patient characteristics to inform a personalized treatment plan that leads to the best possible health-care for each patient. Mobile technologies have an important role to play in this vision as they offer a means to monitor a patient's health status in real-time and subsequently to deliver interventions if, when, and in the dose that they are needed. Dynamic treatment regimes formalize individualized treatment plans as sequences of decision rules, one per stage of clinical intervention, that map current patient information to a recommended treatment. However, most existing methods for estimating optimal dynamic treatment regimes are designed for a small number of fixed decision points occurring on a coarse time-scale. We propose a new reinforcement learning method for estimating an optimal treatment regime that is applicable to data collected using mobile technologies in an out-patient setting. The proposed method accommodates an indefinite time horizon and minute-by-minute decision making that are common in mobile health applications. We show that the proposed estimators are consistent and asymptotically normal under mild conditions. The proposed methods are applied to estimate an optimal dynamic treatment regime for controlling blood glucose levels in patients with type 1 diabetes.
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Affiliation(s)
- Daniel J Luckett
- Department of Biostatistics, University of North Carolina at Chapel Hill
| | - Eric B Laber
- Department of Statistics, North Carolina State University
| | - Anna R Kahkoska
- Department of Nutrition, University of North Carolina at Chapel Hill
| | | | | | - Michael R Kosorok
- Department of Biostatistics, University of North Carolina at Chapel Hill
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29
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Karageorgiou V, Papaioannou TG, Bellos I, Alexandraki K, Tentolouris N, Stefanadis C, Chrousos GP, Tousoulis D. Effectiveness of artificial pancreas in the non-adult population: A systematic review and network meta-analysis. Metabolism 2019; 90:20-30. [PMID: 30321535 DOI: 10.1016/j.metabol.2018.10.002] [Citation(s) in RCA: 69] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2018] [Revised: 09/20/2018] [Accepted: 10/09/2018] [Indexed: 01/19/2023]
Abstract
OBJECTIVE Artificial pancreas is a technology that minimizes user input by bridging continuous glucose monitoring and insulin pump treatment, and has proven safety in the adult population. The purpose of this systematic review and meta-analysis is to evaluate the efficacy of closed-loop (CL) systems in the glycemic control of non-adult type 1 diabetes patients in both a pairwise and network meta-analysis (NMA) context and investigate various parameters potentially affecting the outcome. METHODS Literature was systematically searched using the MEDLINE (1966-2018), Scopus (2004-2018), Cochrane Central Register of Controlled Trials (CENTRAL) (1999-2018), Clinicaltrials.gov (2008-2018) and Google Scholar (2004-2018) databases. Studies comparing the glycemic control in CL (either single- or dual-hormone) with continuous subcutaneous insulin infusion (CSII) in people with diabetes (PWD) aged <18 years old were deemed eligible. The primary outcome analysis was conducted with regard to time spent in the target glycemic range. All outcomes were evaluated in NMA in order to investigate potential between-algorithm differences. Pairwise meta-analysis and meta-regression were performed using the RevMan 5.3 and Open Meta-Analyst software. For NMA, the package pcnetmetain R 3.5.1 was used. RESULTS The meta-analysis was based on 25 studies with a total of 504 PWD. The CL group was associated with significantly higher percentage of time spent in the target glycemic range (Mean (SD): 67.59% (SD: 8.07%) in the target range and OL PWD spending 55.77% (SD: 11.73%), MD: -11.97%, 95% CI [-18.40, -5.54%]) and with lower percentages of time in hyperglycemia (MD: 3.01%, 95% CI [1.68, 4.34%]) and hypoglycemia (MD: 0.67%, 95% CI [0.21, 1.13%]. Mean glucose was also decreased in the CL group (MD: 0.75 mmol/L, 95% CI [0.18-1.33]). The NMA arm of the study showed that the bihormonal modality was superior to other algorithms and standard treatment in lowering mean glucose and increasing time spent in the target range. The DiAs platform was superior to PID in controlling hypoglycemia and mean glucose. Time in target range and mean glucose were unaffected by the confounding factors tested. CONCLUSIONS The findings of this meta-analysis suggest that artificial pancreas systems are superior to the standard sensor-augmented pump treatment of type 1 diabetes mellitus in non-adult PWD. Between-algorithm differences are also addressed, implying a superiority of the bihormonal treatment modality. Future large-scale studies are needed in the field to verify these outcomes and to determine the optimal algorithm to be used in the clinical setting.
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Affiliation(s)
- Vasilios Karageorgiou
- First Department of Cardiology, Biomedical Engineering Unit, Hippokration Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Theodoros G Papaioannou
- First Department of Cardiology, Biomedical Engineering Unit, Hippokration Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece.
| | - Ioannis Bellos
- First Department of Cardiology, Biomedical Engineering Unit, Hippokration Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Krystallenia Alexandraki
- Clinic of Endocrine Oncology, Section of Endocrinology, Department of Pathophysiology, Laiko Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Nikolaos Tentolouris
- First Department of Propaedeutic Internal Medicine, Laiko General Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | | | - George P Chrousos
- First Department of Pediatrics, Aghia Sophia Children's Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Dimitrios Tousoulis
- First Department of Cardiology, Biomedical Engineering Unit, Hippokration Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece
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30
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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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31
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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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32
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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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33
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Artificial pancreas clinical trials: Moving towards closed-loop control using insulin-on-board constraints. Biomed Signal Process Control 2018. [DOI: 10.1016/j.bspc.2018.05.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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34
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Sherr JL. Closing the Loop on Managing Youth With Type 1 Diabetes: Children Are Not Just Small Adults. Diabetes Care 2018; 41:1572-1578. [PMID: 29936422 PMCID: PMC6054496 DOI: 10.2337/dci18-0003] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2018] [Accepted: 04/24/2018] [Indexed: 02/03/2023]
Abstract
As hybrid closed-loop (HCL) insulin delivery systems permeate clinical practice, it is critical to ensure all with diabetes are afforded the opportunity to benefit from this technology. Indeed, due to the suboptimal control achieved by the vast majority of youth with type 1 diabetes (T1D), pediatric patients are positioned to see the greatest benefit from automated insulin delivery systems. To ensure these systems are well poised to deliver the promise of more targeted control, it is essential to understand the unique characteristics and factors of childhood. Herein, the developmental and physiological needs of youth with T1D are reviewed and consideration is given to how HCL could address these issues. Studies of HCL technologies in youth are briefly reviewed. As future-generation closed-loop systems are being devised, features that could make this technology more attractive to youth and to their families are discussed. Integration of HCL has the potential to minimize the burden of this chronic medical condition while improving glycemic control and ultimately allowing our pediatric patients to fulfill the primary goal of childhood, to be a kid.
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Affiliation(s)
- Jennifer L Sherr
- Pediatric Endocrinology & Diabetes Section, Department of Pediatrics, Yale School of Medicine, New Haven, CT
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35
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Majeed W, Thabit H. Closed-loop insulin delivery: current status of diabetes technologies and future prospects. Expert Rev Med Devices 2018; 15:579-590. [PMID: 30027775 DOI: 10.1080/17434440.2018.1503530] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
INTRODUCTION Type 1 diabetes is characterised by destruction of pancreatic beta cells, leading to insulin deficiency and hyperglycaemia. The mainstay of treatment remains lifelong insulin therapy as a sustainable cure has as yet proven elusive. The burden of daily management of type 1 diabetes has contributed to suboptimal outcomes for people living with the condition. Innovative technological approaches have been shown to improve glycaemic and patient-related outcomes. AREAS COVERED We discuss recent advances in technologies in type 1 diabetes including closed-loop systems, also known as the 'artificial pancreas. Its various components, technical aspects and limitations are reviewed. We also discuss its advent into clinical practice, and other systems in development. Evidence from clinical studies are summarised. EXPERT COMMENTARY The recent approval of a hybrid closed-loop system for clinical use highlights the significant progress made in this field. Results from clinical studies have shown safety and glycaemic benefit, however challenges remain around improving performance and acceptability. More data is required to establish long-term clinical efficacy and cost-effectiveness, to fulfil the expectations of people with type 1 diabetes.
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Affiliation(s)
- Waseem Majeed
- a Manchester Academic Health Science Centre , Manchester University Hospitals NHS Foundation Trust , Manchester , UK
| | - Hood Thabit
- a Manchester Academic Health Science Centre , Manchester University Hospitals NHS Foundation Trust , Manchester , UK.,b Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health , University of Manchester , Manchester , UK
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36
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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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Hajizadeh I, Rashid M, Samadi S, Feng J, Sevil M, Hobbs N, Lazaro C, Maloney Z, Brandt R, Yu X, Turksoy K, Littlejohn E, Cengiz E, Cinar A. Adaptive and Personalized Plasma Insulin Concentration Estimation for Artificial Pancreas Systems. J Diabetes Sci Technol 2018; 12:639-649. [PMID: 29566547 PMCID: PMC6154239 DOI: 10.1177/1932296818763959] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND The artificial pancreas (AP) system, a technology that automatically administers exogenous insulin in people with type 1 diabetes mellitus (T1DM) to regulate their blood glucose concentrations, necessitates the estimation of the amount of active insulin already present in the body to avoid overdosing. METHOD An adaptive and personalized plasma insulin concentration (PIC) estimator is designed in this work to accurately quantify the insulin present in the bloodstream. The proposed PIC estimation approach incorporates Hovorka's glucose-insulin model with the unscented Kalman filtering algorithm. Methods for the personalized initialization of the time-varying model parameters to individual patients for improved estimator convergence are developed. Data from 20 three-days-long closed-loop clinical experiments conducted involving subjects with T1DM are used to evaluate the proposed PIC estimation approach. RESULTS The proposed methods are applied to the clinical data containing significant disturbances, such as unannounced meals and exercise, and the results demonstrate the accurate real-time estimation of the PIC with the root mean square error of 7.15 and 9.25 mU/L for the optimization-based fitted parameters and partial least squares regression-based testing parameters, respectively. CONCLUSIONS The accurate real-time estimation of PIC will benefit the AP systems by preventing overdelivery of insulin when significant insulin is present in the bloodstream.
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Affiliation(s)
- Iman Hajizadeh
- Department of Chemical and Biological
Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Mudassir Rashid
- Department of Chemical and Biological
Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Sediqeh Samadi
- Department of Chemical and Biological
Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Jianyuan Feng
- Department of Chemical and Biological
Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Mert Sevil
- Department of Biomedical Engineering,
Illinois Institute of Technology, Chicago, IL, USA
| | - Nicole Hobbs
- Department of Biomedical Engineering,
Illinois Institute of Technology, Chicago, IL, USA
| | - Caterina Lazaro
- Department of Electrical and Computer
Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Zacharie Maloney
- Department of Biomedical Engineering,
Illinois Institute of Technology, Chicago, IL, USA
| | - Rachel Brandt
- Department of Biomedical Engineering,
Illinois Institute of Technology, Chicago, IL, USA
| | - Xia Yu
- School of Information Science and
Technology, Northeastern University, Shenyang, China
| | - Kamuran Turksoy
- Department of Biomedical Engineering,
Illinois Institute of Technology, Chicago, IL, USA
| | - Elizabeth Littlejohn
- Department of Pediatrics and Medicine,
Section of Endocrinology, Kovler Diabetes Center, University of Chicago, Chicago,
IL, USA
| | - Eda Cengiz
- Department of Pediatrics, Yale
University School of Medicine, New Haven, CT, USA
| | - Ali Cinar
- Department of Chemical and Biological
Engineering, Illinois Institute of Technology, Chicago, IL, USA
- Department of Biomedical Engineering,
Illinois Institute of Technology, Chicago, IL, USA
- Ali Cinar, PhD, Illinois Institute of
Technology, Department of Chemical and Biological Engineering, 10 W 33rd St,
Chicago, IL 60616, USA.
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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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40
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Perez KM, Hamburger ER, Lyttle M, Williams R, Bergner E, Kahanda S, Cobry E, Jaser SS. Sleep in Type 1 Diabetes: Implications for Glycemic Control and Diabetes Management. Curr Diab Rep 2018; 18:5. [PMID: 29399719 PMCID: PMC5842802 DOI: 10.1007/s11892-018-0974-8] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
PURPOSE OF REVIEW To highlight recent findings from studies of sleep in type 1 diabetes (T1D), with a focus on the role of sleep in self-management, the cognitive and psychosocial outcomes related to sleep disturbances, and factors associated with sleep disturbances specific to T1D. RECENT FINDINGS People with T1D experience higher rates of sleep disturbances than people without diabetes, and these disturbances have negative implications for glycemic control and diabetes management, as well as psychosocial and cognitive outcomes. Inconsistent sleep timing (bedtime and wake time) has emerged as a potential target for interventions, as variability in sleep timing has been linked with poorer glycemic control and adherence to treatment. Sleep-promoting interventions and new diabetes technology have the potential to improve sleep in people with T1D. Sleep is increasingly considered a critical factor in diabetes management, but more multi-method and longitudinal research is needed. We emphasize the importance of sufficient and consistent sleep for people with T1D, and the need for providers to routinely assess sleep among patients with T1D.
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Affiliation(s)
- Katia M Perez
- Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Emily R Hamburger
- Vanderbilt University Medical Center, Village at Vanderbilt, 1500 21st Ave. South, Suite 1514, Nashville, TN, 37212, USA
| | - Morgan Lyttle
- Vanderbilt University Medical Center, Village at Vanderbilt, 1500 21st Ave. South, Suite 1514, Nashville, TN, 37212, USA
| | - Rodayne Williams
- Vanderbilt University Medical Center, Village at Vanderbilt, 1500 21st Ave. South, Suite 1514, Nashville, TN, 37212, USA
| | - Erin Bergner
- Vanderbilt University Medical Center, Village at Vanderbilt, 1500 21st Ave. South, Suite 1514, Nashville, TN, 37212, USA
| | - Sachini Kahanda
- Vanderbilt University Medical Center, Village at Vanderbilt, 1500 21st Ave. South, Suite 1514, Nashville, TN, 37212, USA
| | - Erin Cobry
- Vanderbilt University Medical Center, Village at Vanderbilt, 1500 21st Ave. South, Suite 1514, Nashville, TN, 37212, USA
| | - Sarah S Jaser
- Vanderbilt University Medical Center, Village at Vanderbilt, 1500 21st Ave. South, Suite 1514, Nashville, TN, 37212, USA.
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Iturralde E, Tanenbaum ML, Hanes SJ, Suttiratana SC, Ambrosino JM, Ly TT, Maahs DM, Naranjo D, Walders-Abramson N, Weinzimer SA, Buckingham BA, Hood KK. Expectations and Attitudes of Individuals With Type 1 Diabetes After Using a Hybrid Closed Loop System. DIABETES EDUCATOR 2017; 43:223-232. [PMID: 28340542 DOI: 10.1177/0145721717697244] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
Purpose The first hybrid closed loop (HCL) system, which automates insulin delivery but requires user inputs, was approved for treatment of type 1 diabetes (T1D) by the US Food and Drug Administration in September 2016. The purpose of this study was to explore the benefits, expectations, and attitudes of individuals with T1D following a clinical trial of an HCL system. Methods Thirty-two individuals with T1D (17 adults, 15 adolescents) participated in focus groups after 4 to 5 days of system use. Content analysis generated themes regarding perceived benefits, hassles, and limitations. Results Some participants felt misled by terms such as "closed loop" and "artificial pancreas," which seemed to imply a more "hands-off" experience. Perceived benefits were improved glycemic control, anticipated reduction of long-term complications, better quality of life, and reduced mental burden of diabetes. Hassles and limitations included unexpected tasks for the user, difficulties wearing the system, concerns about controlling highs, and being reminded of diabetes. Conclusion Users are willing to accept some hassles and limitations if they also perceive health and quality-of-life benefits beyond current self-management. It is important for clinicians to provide a balanced view of positives and negatives to help manage expectations.
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Affiliation(s)
- Esti Iturralde
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California (Dr Iturralde, Dr Tanenbaum, Ms Hanes, Dr Ly, Dr Maahs, Dr Buckingham, Dr Hood)
| | - Molly L Tanenbaum
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California (Dr Iturralde, Dr Tanenbaum, Ms Hanes, Dr Ly, Dr Maahs, Dr Buckingham, Dr Hood)
| | - Sarah J Hanes
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California (Dr Iturralde, Dr Tanenbaum, Ms Hanes, Dr Ly, Dr Maahs, Dr Buckingham, Dr Hood)
| | - Sakinah C Suttiratana
- Department of Social and Behavioral Sciences, University of California San Francisco, San Francisco, California (Ms Suttiratana)
| | - Jodie M Ambrosino
- Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut (Dr Ambrosino, Dr Weinzimer)
| | - Trang T Ly
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California (Dr Iturralde, Dr Tanenbaum, Ms Hanes, Dr Ly, Dr Maahs, Dr Buckingham, Dr Hood).,Insulet Corporation, Billerica, Massachusetts (Dr Ly)
| | - David M Maahs
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California (Dr Iturralde, Dr Tanenbaum, Ms Hanes, Dr Ly, Dr Maahs, Dr Buckingham, Dr Hood).,Barbara Davis Center for Childhood Diabetes, University of Colorado, Aurora, Colorado (Dr Maahs, Dr Walders-Abramson)
| | - Diana Naranjo
- Department of Psychiatry, Stanford University School of Medicine, Stanford, California (Dr Naranjo, Dr Hood)
| | - Natalie Walders-Abramson
- Barbara Davis Center for Childhood Diabetes, University of Colorado, Aurora, Colorado (Dr Maahs, Dr Walders-Abramson)
| | - Stuart A Weinzimer
- Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut (Dr Ambrosino, Dr Weinzimer)
| | - Bruce A Buckingham
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California (Dr Iturralde, Dr Tanenbaum, Ms Hanes, Dr Ly, Dr Maahs, Dr Buckingham, Dr Hood)
| | - Korey K Hood
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California (Dr Iturralde, Dr Tanenbaum, Ms Hanes, Dr Ly, Dr Maahs, Dr Buckingham, Dr Hood).,Department of Psychiatry, Stanford University School of Medicine, Stanford, California (Dr Naranjo, Dr Hood)
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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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Review of a commercially available hybrid closed-loop insulin-delivery system in the treatment of Type 1 diabetes. Ther Deliv 2017; 9:77-87. [PMID: 29235423 DOI: 10.4155/tde-2017-0099] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Type 1 diabetes is an important medical condition causing significant burden and morbidity to those persons affected by it. Improvements in insulin products, insulin delivery and glucose monitoring technology have all contributed to reductions in long-term complications and hypoglycemia. This article reviews the Medtronic 670G device and summarizes the data supporting how this product reduces the burden and increases the safety of insulin dosing in Type 1 diabetes.
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Agiostratidou G, Anhalt H, Ball D, Blonde L, Gourgari E, Harriman KN, Kowalski AJ, Madden P, McAuliffe-Fogarty AH, McElwee-Malloy M, Peters A, Raman S, Reifschneider K, Rubin K, Weinzimer SA. Standardizing Clinically Meaningful Outcome Measures Beyond HbA 1c for Type 1 Diabetes: A Consensus Report of the American Association of Clinical Endocrinologists, the American Association of Diabetes Educators, the American Diabetes Association, the Endocrine Society, JDRF International, The Leona M. and Harry B. Helmsley Charitable Trust, the Pediatric Endocrine Society, and the T1D Exchange. Diabetes Care 2017; 40:1622-1630. [PMID: 29162582 PMCID: PMC5864122 DOI: 10.2337/dc17-1624] [Citation(s) in RCA: 258] [Impact Index Per Article: 36.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To identify and define clinically meaningful type 1 diabetes outcomes beyond hemoglobin A1c (HbA1c) based upon a review of the evidence, consensus from clinical experts, and input from researchers, people with type 1 diabetes, and industry. Priority outcomes include hypoglycemia, hyperglycemia, time in range, diabetic ketoacidosis (DKA), and patient-reported outcomes (PROs). While priority outcomes for type 1 and type 2 diabetes may overlap, type 1 diabetes was the focus of this work. RESEARCH AND METHODS A Steering Committee-comprising representatives from the American Association of Clinical Endocrinologists, the American Association of Diabetes Educators, the American Diabetes Association, the Endocrine Society, JDRF International, The Leona M. and Harry B. Helmsley Charitable Trust, the Pediatric Endocrine Society, and the T1D Exchange-was the decision-making body for the Type 1 Diabetes Outcomes Program. Their work was informed by input from researchers, industry, and people with diabetes through Advisory Committees representing each stakeholder group. Stakeholder surveys were used to identify priority outcomes. The outcomes prioritized in the surveys were hypoglycemia, hyperglycemia, time in range, DKA, and PROs. To develop consensus on the definitions of these outcomes, the Steering Committee relied on published evidence, their clinical expertise, and feedback from the Advisory Committees. RESULTS The Steering Committee developed definitions for hypoglycemia, hyperglycemia, time in range, and DKA in type 1 diabetes. The definitions reflect their assessment of the outcome's short- and long-term clinical impact on people with type 1 diabetes. Knowledge gaps to be addressed by future research were identified. The Steering Committee discussed PROs and concluded that further type 1 diabetes-specific development is needed. CONCLUSIONS The Steering Committee recommends use of the defined clinically meaningful outcomes beyond HbA1c in the research, development, and evaluation of type 1 diabetes therapies.
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Affiliation(s)
| | | | | | - Lawrence Blonde
- American Association of Clinical Endocrinologists, Jacksonville, FL
| | | | | | | | - Paul Madden
- American Diabetes Association, Arlington, VA
| | | | | | | | - Sripriya Raman
- American Association of Clinical Endocrinologists, Jacksonville, FL
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Dassau E, Renard E, Place J, Farret A, Pelletier MJ, Lee J, Huyett LM, Chakrabarty A, Doyle FJ, Zisser HC. Intraperitoneal insulin delivery provides superior glycaemic regulation to subcutaneous insulin delivery in model predictive control-based fully-automated artificial pancreas in patients with type 1 diabetes: a pilot study. Diabetes Obes Metab 2017; 19:1698-1705. [PMID: 28474383 PMCID: PMC5742859 DOI: 10.1111/dom.12999] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Revised: 04/27/2017] [Accepted: 04/27/2017] [Indexed: 01/15/2023]
Abstract
AIMS To compare intraperitoneal (IP) to subcutaneous (SC) insulin delivery in an artificial pancreas (AP). RESEARCH DESIGN AND METHODS Ten adults with type 1 diabetes participated in a non-randomized, non-blinded sequential AP study using the same SC glucose sensing and Zone Model Predictive Control (ZMPC) algorithm adjusted for insulin clearance. On first admission, subjects underwent closed-loop control with SC delivery of a fast-acting insulin analogue for 24 hours. Following implantation of a DiaPort IP insulin delivery system, the identical 24-hour trial was performed with IP regular insulin delivery. The clinical protocol included 3 unannounced meals with 70, 40 and 70 g carbohydrate, respectively. Primary endpoint was time spent with blood glucose (BG) in the range of 80 to 140 mg/dL (4.4-7.7 mmol/L). RESULTS Percent of time spent within the 80 to 140 mg/dL range was significantly higher for IP delivery than for SC delivery: 39.8 ± 7.6 vs 25.6 ± 13.1 ( P = .03). Mean BG (mg/dL) and percent of time spent within the broader 70 to 180 mg/dL range were also significantly better for IP insulin: 151.0 ± 11.0 vs 190.0 ± 31.0 ( P = .004) and 65.7 ± 9.2 vs 43.9 ± 14.7 ( P = .001), respectively. Superiority of glucose control with IP insulin came from the reduced time spent in hyperglycaemia (>180 mg/dL: 32.4 ± 8.9 vs 53.5 ± 17.4, P = .014; >250 mg/dL: 5.9 ± 5.6 vs 23.0 ± 11.3, P = .0004). Higher daily doses of insulin (IU) were delivered with the IP route (43.7 ± 0.1 vs 32.3 ± 0.1, P < .001) with no increased percent time spent <70 mg/dL (IP: 2.5 ± 2.9 vs SC: 4.1 ± 5.3, P = .42). CONCLUSIONS Glycaemic regulation with fully-automated AP delivering IP insulin was superior to that with SC insulin delivery. This pilot study provides proof-of-concept for an AP system combining a ZMPC algorithm with IP insulin delivery.
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MESH Headings
- Adult
- Algorithms
- Blood Glucose/analysis
- Diabetes Mellitus, Type 1/blood
- Diabetes Mellitus, Type 1/therapy
- Female
- France
- Glycated Hemoglobin/analysis
- Humans
- Hyperglycemia/prevention & control
- Hypoglycemia/chemically induced
- Hypoglycemia/prevention & control
- Hypoglycemic Agents/administration & dosage
- Hypoglycemic Agents/adverse effects
- Hypoglycemic Agents/therapeutic use
- Infusions, Parenteral
- Infusions, Subcutaneous
- Insulin Infusion Systems/adverse effects
- Insulin Lispro/administration & dosage
- Insulin Lispro/adverse effects
- Insulin Lispro/therapeutic use
- Insulin, Regular, Human/administration & dosage
- Insulin, Regular, Human/adverse effects
- Insulin, Regular, Human/therapeutic use
- Male
- Middle Aged
- Pancreas, Artificial/adverse effects
- Pilot Projects
- Proof of Concept Study
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Affiliation(s)
- Eyal Dassau
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
| | - Eric Renard
- Department of Endocrinology, Diabetes, Nutrition and INSERM Clinical Investigation Center 1411, University Hospital of Montpellier, Montpellier, France
- Department of Psychology, Institute of Functional Genomics, CNRS UMR5203, INSERM U1191, University of Montpellier, Montpellier, France
| | - Jérôme Place
- Department of Psychology, Institute of Functional Genomics, CNRS UMR5203, INSERM U1191, University of Montpellier, Montpellier, France
| | - Anne Farret
- Department of Endocrinology, Diabetes, Nutrition and INSERM Clinical Investigation Center 1411, University Hospital of Montpellier, Montpellier, France
- Department of Psychology, Institute of Functional Genomics, CNRS UMR5203, INSERM U1191, University of Montpellier, Montpellier, France
| | - Marie-José Pelletier
- Department of Endocrinology, Diabetes, Nutrition and INSERM Clinical Investigation Center 1411, University Hospital of Montpellier, Montpellier, France
| | - Justin Lee
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
| | - Lauren M. Huyett
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
| | - Ankush Chakrabarty
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
| | - Francis J. Doyle
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
| | - Howard C. Zisser
- Department of Chemical Engineering, University of California Santa Barbara, Santa Barbara, California
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Tauschmann M, Hovorka R. Insulin delivery and nocturnal glucose control in children and adolescents with type 1 diabetes. Expert Opin Drug Deliv 2017; 14:1367-1377. [PMID: 28819992 PMCID: PMC5942151 DOI: 10.1080/17425247.2017.1360866] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Introduction: Nocturnal glucose control remains challenging in children and adolescents with type 1 diabetes due to highly variable overnight insulin requirements. The issue may be addressed by glucose responsive insulin delivery based on real-time continuous glucose measurements. Areas covered: This review outlines recent developments of glucose responsive insulin delivery systems from a paediatric perspective. We cover threshold-based suspend application, predictive low glucose suspend, and more advanced single hormone and dual-hormone closed-loop systems. Approaches are evaluated in relation to nocturnal glucose control particularly during outpatient randomised controlled trials. Expert opinion: Significant progress translating research from controlled clinical centre settings to free-living unsupervised home studies have been achieved over the past decade. Nocturnal glycaemic control can be improved whilst reducing the risk of hypoglycaemia with closed-loop systems. Following the US regulatory approval of the first hybrid closed-loop system in non-paediatric population, large multinational closed-loop clinical trials and pivotal studies including paediatric populations are underway or in preparation to facilitate the use of closed-loop systems in clinical practice.
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Affiliation(s)
- Martin Tauschmann
- a Wellcome Trust-MRC Institute of Metabolic Science , University of Cambridge , Cambridge , UK.,b Department of Paediatrics , University of Cambridge , Cambridge , UK
| | - Roman Hovorka
- a Wellcome Trust-MRC Institute of Metabolic Science , University of Cambridge , Cambridge , UK.,b Department of Paediatrics , University of Cambridge , Cambridge , UK
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Abstract
PURPOSE OF REVIEW The review summarizes the current state of the artificial pancreas (AP) systems and introduces various new modules that should be included in future AP systems. RECENT FINDINGS A fully automated AP must be able to detect and mitigate the effects of meals, exercise, stress and sleep on blood glucose concentrations. This can only be achieved by using a multivariable approach that leverages information from wearable devices that provide real-time streaming data about various physiological variables that indicate imminent changes in blood glucose concentrations caused by meals, exercise, stress and sleep. The development of a fully automated AP will necessitate the design of multivariable and adaptive systems that use information from wearable devices in addition to glucose sensors and modify the models used in their model-predictive alarm and control systems to adapt to the changes in the metabolic state of the user. These AP systems will also integrate modules for controller performance assessment, fault detection and diagnosis, machine learning and classification to interpret various signals and achieve fault-tolerant control. Advances in wearable devices, computational power, and safe and secure communications are enabling the development of fully automated multivariable AP systems.
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Affiliation(s)
- Ali Cinar
- Department of Chemical and Biological Engineering and Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA.
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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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Ly TT, Weinzimer SA, Maahs DM, Sherr JL, Roy A, Grosman B, Cantwell M, Kurtz N, Carria L, Messer L, von Eyben R, Buckingham BA. Automated hybrid closed-loop control with a proportional-integral-derivative based system in adolescents and adults with type 1 diabetes: individualizing settings for optimal performance. Pediatr Diabetes 2017; 18:348-355. [PMID: 27191182 DOI: 10.1111/pedi.12399] [Citation(s) in RCA: 44] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2016] [Revised: 04/06/2016] [Accepted: 04/22/2016] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Automated insulin delivery systems, utilizing a control algorithm to dose insulin based upon subcutaneous continuous glucose sensor values and insulin pump therapy, will soon be available for commercial use. The objective of this study was to determine the preliminary safety and efficacy of initialization parameters with the Medtronic hybrid closed-loop controller by comparing percentage of time in range, 70-180 mg/dL (3.9-10 mmol/L), mean glucose values, as well as percentage of time above and below target range between sensor-augmented pump therapy and hybrid closed-loop, in adults and adolescents with type 1 diabetes. METHODS We studied an initial cohort of 9 adults followed by a second cohort of 15 adolescents, using the Medtronic hybrid closed-loop system with the proportional-integral-derivative with insulin feed-back (PID-IFB) algorithm. Hybrid closed-loop was tested in supervised hotel-based studies over 4-5 days. RESULTS The overall mean percentage of time in range (70-180 mg/dL, 3.9-10 mmol/L) during hybrid closed-loop was 71.8% in the adult cohort and 69.8% in the adolescent cohort. The overall percentage of time spent under 70 mg/dL (3.9 mmol/L) was 2.0% in the adult cohort and 2.5% in the adolescent cohort. Mean glucose values were 152 mg/dL (8.4 mmol/L) in the adult cohort and 153 mg/dL (8.5 mmol/L) in the adolescent cohort. CONCLUSIONS Closed-loop control using the Medtronic hybrid closed-loop system enables adaptive, real-time basal rate modulation. Initializing hybrid closed-loop in clinical practice will involve individualizing initiation parameters to optimize overall glucose control.
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Affiliation(s)
- Trang T Ly
- Department of Pediatrics, Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, CA, USA.,School of Paediatrics and Child Health, The University of Western Australia, Perth, Western Australia, Australia
| | - Stuart A Weinzimer
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT, USA
| | - David M Maahs
- Barbara Davis Center for Childhood Diabetes, University of Colorado Denver, Aurora, CO, USA
| | - Jennifer L Sherr
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT, USA
| | | | | | | | | | - Lori Carria
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT, USA
| | - Laurel Messer
- Barbara Davis Center for Childhood Diabetes, University of Colorado Denver, Aurora, CO, USA
| | - Rie von Eyben
- Department of Pediatrics, Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, CA, USA
| | - Bruce A Buckingham
- Department of Pediatrics, Division of Pediatric Endocrinology and Diabetes, Stanford University School of Medicine, Stanford, CA, USA
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Abstract
PURPOSE OF REVIEW The complexity of modern insulin-based therapy for type I and type II diabetes mellitus and the risks associated with excursions in blood-glucose concentration (hyperglycemia and hypoglycemia) have motivated the development of 'smart insulin' technologies (glucose-responsive insulin, GRI). Such analogs or delivery systems are entities that provide insulin activity proportional to the glycemic state of the patient without external monitoring by the patient or healthcare provider. The present review describes the relevant historical background to modern GRI technologies and highlights three distinct approaches: coupling of continuous glucose monitoring (CGM) to deliver devices (algorithm-based 'closed-loop' systems), glucose-responsive polymer encapsulation of insulin, and molecular modification of insulin itself. RECENT FINDINGS Recent advances in GRI research utilizing each of the three approaches are illustrated; these include newly developed algorithms for CGM-based insulin delivery systems, glucose-sensitive modifications of existing clinical analogs, newly developed hypoxia-sensitive polymer matrices, and polymer-encapsulated, stem-cell-derived pancreatic β cells. SUMMARY Although GRI technologies have yet to be perfected, the recent advances across several scientific disciplines that are described in this review have provided a path towards their clinical implementation.
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Affiliation(s)
- Nischay K. Rege
- Department of Biochemistry and Medical Scientist Training Program, Case Western Reserve University
| | | | - Michael A. Weiss
- Chairman of Institute for Therapeutic Protein Design, Departments of Biomedical Engineering, Biochemistry, and Medicine
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