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Rizzi A, Tartaglione L, Lucaccini Paoli L, Leo ML, Popolla V, Viti L, Barberio A, Di Leo M, Pontecorvi A, Pitocco D. Evaluation of time in tight range and the glycaemia risk index in adults with type 1 diabetes using an advanced hybrid closed loop system: A 1-year real-world assessment. Diabetes Obes Metab 2024; 26:4078-4086. [PMID: 39010292 DOI: 10.1111/dom.15766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2024] [Revised: 06/13/2024] [Accepted: 06/22/2024] [Indexed: 07/17/2024]
Abstract
AIM To assess the long-term glycaemic outcomes, with additional metrics, in adults with type 1 diabetes (T1D) using the Tandem t:slim X2 with Control-IQ technology advanced hybrid closed-loop (AHCL) system. METHODS This was a single-centre, retrospective study involving 56 T1D patients who transitioned to the Tandem t:slim X2 with Control-IQ system. The primary and secondary endpoints consisted of variations in time in tight range (TiTR; 70-140 mg/dL) and the glycaemia risk index (GRI), respectively. Additional standardized continuous glucose monitoring (CGM) metrics, mean sensor glucose, coefficient of variation, the glucose management indicator (GMI), HbA1c and insulin daily dose, were also evaluated. Variables were measured at baseline and at 15 days, 3 months, 6 months and 1 year after Tandem t:slim X2 Control-IQ initiation. Glucose outcomes are expressed as mean (standard deviation). RESULTS Use of Tandem t:slim X2 with Control-IQ over 1 year was associated with an increase in mean TiTR, from 38.11% (17.05%) to 43.10% (13.20%) (P = .059), and with a decline in the GRI, from 41.03 (25.48) to 28.55 (16.27) (P = .008). CGM metrics, including time in range and time above range, showed consistent improvements. Mean sensor glucose, the GMI and HbA1c decreased significantly over time. After an initial increase, insulin daily dose remained stable throughout the 12 months. CONCLUSIONS The results highlight the sustained effectiveness of Tandem t:slim X2 with Control-IQ in improving glycaemic outcomes over 1 year and support the use of this technology for the management of T1D.
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Affiliation(s)
- Alessandro Rizzi
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Linda Tartaglione
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Lorenzo Lucaccini Paoli
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Maria Laura Leo
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Valentina Popolla
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Luca Viti
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Annarita Barberio
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Mauro Di Leo
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Alfredo Pontecorvi
- Department of Endocrinology, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Dario Pitocco
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
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Forlenza GP, DeSalvo DJ, Aleppo G, Wilmot EG, Berget C, Huyett LM, Hadjiyianni I, Méndez JJ, Conroy LR, Ly TT, Sherr JL. Real-World Evidence of Omnipod ® 5 Automated Insulin Delivery System Use in 69,902 People with Type 1 Diabetes. Diabetes Technol Ther 2024; 26:514-525. [PMID: 38375861 DOI: 10.1089/dia.2023.0578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Background: The Omnipod® 5 Automated Insulin Delivery System was associated with favorable glycemic outcomes for people with type 1 diabetes (T1D) in two pivotal clinical trials. Real-world evidence is needed to explore effectiveness in nonstudy conditions. Methods: A retrospective analysis of the United States Omnipod 5 System users (aged ≥2 years) with T1D and sufficient data (≥90 days of data; ≥75% of days with ≥220 continuous glucose monitor readings/day) available in Insulet Corporation's device and person-reported datasets as of July 2023 was performed. Target glucose setting usage (i.e., 110-150 mg/dL in 10 mg/dL increments) was summarized and glycemic outcomes were examined. Subgroup analyses of those using the lowest average glucose target (110 mg/dL) and stratification by baseline characteristics (e.g., age, prior therapy, health insurance coverage) were conducted. Results: In total, 69,902 users were included. Multiple and higher glucose targets were more commonly used in younger age groups. Median percentage of time in range (TIR; 70-180 mg/dL) was 68.8%, 61.3%, and 53.6% for users with average glucose targets of 110, 120, and 130-150 mg/dL, respectively, with minimal time <70 mg/dL (all median <1.13%). Among those with an average glucose target of 110 mg/dL (n = 37,640), median TIR was 65.0% in children and adolescents (2-17 years) and 69.9% in adults (≥18 years). Subgroup analyses of users transitioning from Omnipod DASH or multiple daily injections and of Medicaid/Medicare users demonstrated favorable glycemic outcomes among these groups. Conclusion: These glycemic outcomes from a large and diverse sample of nearly 70,000 children and adults demonstrate effective use of the Omnipod 5 System under real-world conditions.
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Affiliation(s)
- Gregory P Forlenza
- Department of Pediatrics, Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Daniel J DeSalvo
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
| | - Grazia Aleppo
- Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Emma G Wilmot
- Translational Medical Sciences, University of Nottingham, School of Medicine, Royal Derby Hospital, Derby, United Kingdom
| | - Cari Berget
- Department of Pediatrics, Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | | | | | | | | | - Trang T Ly
- Insulet Corporation, Acton, Massachusetts, USA
| | - Jennifer L Sherr
- Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut, USA
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Mameli C, Smylie GM, Marigliano M, Zagaroli L, Mancioppi V, Maffeis C, Salpietro V, Zuccotti G, Delvecchio M. Safety and Psychological Outcomes of Tandem t:Slim X2 Insulin Pump with Control-IQ Technology in Children, Adolescents, and Young Adults with Type 1 Diabetes: A Systematic Review. Diabetes Ther 2024:10.1007/s13300-024-01618-2. [PMID: 39008237 DOI: 10.1007/s13300-024-01618-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Accepted: 06/26/2024] [Indexed: 07/16/2024] Open
Abstract
The Tandem t:slim X2 insulin pump is a second-generation automated insulin delivery system with Control-IQ technology. It consists of an X2 insulin pump, an integrated Dexcom sensor, and an embedded 'Control-IQ' algorithm, which predicts glucose levels 30 min in the future, adapting the programmed basal insulin rates to get glucose levels between 112.5 and 160 mg/dl (8.9 mmol/l). The system delivers automatic correction boluses of insulin when glucose levels are predicted to rise > 180 mg/dl (10 mmol/l). It has been commercially available since 2016. We reviewed the current evidence about the psychological, safety, and exercise-related outcomes of this device in children, adolescents, and young adults living with type 1 diabetes. We screened 552 papers, but only 21 manuscripts were included in this review. Fear of hypoglycemia is significantly reduced in young people with diabetes and their parents. Interestingly, diabetes-related distress is decreased; thus, the system is well accepted by the users. The sleeping quality of subjects living with diabetes and their caregivers is improved to a lesser extent as well. Despite the small number of data, this system is associated with a low rate of exercise-related hypoglycemia. Finally, evidence from the literature shows that this system is safe and effective in improving psychological personal outcomes. Even if further steps toward the fully closed loop are still mandatory, this second-generation automated insulin delivery system reduces the burden of diabetes. It properly addresses most psychological issues in children, adolescents, and young adults with type 1 diabetes mellitus; thus, it appears to be well accepted.
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Affiliation(s)
- Chiara Mameli
- Department of Pediatrics, Buzzi Children's Hospital, Milan, Italy
- Department of Biomedical and Clinical Science, Università Di Milano, Milan, Italy
| | | | - Marco Marigliano
- Department of Surgery, Dentistry, Pediatrics, and Gynecology, Section of Pediatric Diabetes and Metabolism, University and Azienda Ospedaliera, Universitaria Integrata of Verona, Verona, Italy
| | - Luca Zagaroli
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Valentina Mancioppi
- Department of Surgery, Dentistry, Pediatrics, and Gynecology, Section of Pediatric Diabetes and Metabolism, University and Azienda Ospedaliera, Universitaria Integrata of Verona, Verona, Italy
| | - Claudio Maffeis
- Department of Surgery, Dentistry, Pediatrics, and Gynecology, Section of Pediatric Diabetes and Metabolism, University and Azienda Ospedaliera, Universitaria Integrata of Verona, Verona, Italy
| | - Vincenzo Salpietro
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Gianvincenzo Zuccotti
- Department of Pediatrics, Buzzi Children's Hospital, Milan, Italy
- Department of Biomedical and Clinical Science, Università Di Milano, Milan, Italy
| | - Maurizio Delvecchio
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
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Rimon MTI, Hasan MW, Hassan MF, Cesmeci S. Advancements in Insulin Pumps: A Comprehensive Exploration of Insulin Pump Systems, Technologies, and Future Directions. Pharmaceutics 2024; 16:944. [PMID: 39065641 PMCID: PMC11279469 DOI: 10.3390/pharmaceutics16070944] [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: 05/19/2024] [Revised: 06/25/2024] [Accepted: 06/27/2024] [Indexed: 07/28/2024] Open
Abstract
Insulin pumps have transformed the way diabetes is managed by providing a more accurate and individualized method of delivering insulin, in contrast to conventional injection routines. This research explores the progression of insulin pumps, following their advancement from initial ideas to advanced contemporary systems. The report proceeds to categorize insulin pumps according to their delivery systems, specifically differentiating between conventional, patch, and implantable pumps. Every category is thoroughly examined, emphasizing its unique characteristics and capabilities. A comparative examination of commercially available pumps is provided to enhance informed decision making. This section provides a thorough analysis of important specifications among various brands and models. Considered factors include basal rate and bolus dosage capabilities, reservoir size, user interface, and compatibility with other diabetes care tools, such as continuous glucose monitoring (CGM) devices and so on. This review seeks to empower healthcare professionals and patients with the essential information to improve diabetes treatment via individualized pump therapy options. It provides a complete assessment of the development, categorization, and full specification comparisons of insulin pumps.
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Affiliation(s)
| | | | | | - Sevki Cesmeci
- Department of Mechanical Engineering, Georgia Southern University, Statesboro, GA 30458, USA
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5
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Ahmad S, Beneyto A, Zhu T, Contreras I, Georgiou P, Vehi J. An automatic deep reinforcement learning bolus calculator for automated insulin delivery systems. Sci Rep 2024; 14:15245. [PMID: 38956183 PMCID: PMC11219905 DOI: 10.1038/s41598-024-62912-4] [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: 11/10/2023] [Accepted: 05/22/2024] [Indexed: 07/04/2024] Open
Abstract
In hybrid automatic insulin delivery (HAID) systems, meal disturbance is compensated by feedforward control, which requires the announcement of the meal by the patient with type 1 diabetes (DM1) to achieve the desired glycemic control performance. The calculation of insulin bolus in the HAID system is based on the amount of carbohydrates (CHO) in the meal and patient-specific parameters, i.e. carbohydrate-to-insulin ratio (CR) and insulin sensitivity-related correction factor (CF). The estimation of CHO in a meal is prone to errors and is burdensome for patients. This study proposes a fully automatic insulin delivery (FAID) system that eliminates patient intervention by compensating for unannounced meals. This study exploits the deep reinforcement learning (DRL) algorithm to calculate insulin bolus for unannounced meals without utilizing the information on CHO content. The DRL bolus calculator is integrated with a closed-loop controller and a meal detector (both previously developed by our group) to implement the FAID system. An adult cohort of 68 virtual patients based on the modified UVa/Padova simulator was used for in-silico trials. The percentage of the overall duration spent in the target range of 70-180 mg/dL was 71.2 % and 76.2 % , < 70 mg/dL was 0.9 % and 0.1 % , and > 180 mg/dL was 26.7 % and 21.1 % , respectively, for the FAID system and HAID system utilizing a standard bolus calculator (SBC) including CHO misestimation. The proposed algorithm can be exploited to realize FAID systems in the future.
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Affiliation(s)
- Sayyar Ahmad
- Modeling and Intelligent Control Engineering Laboratory, Institute of Informatics and Applications, University of Girona, 17003, Girona, Spain
| | - Aleix Beneyto
- Modeling and Intelligent Control Engineering Laboratory, Institute of Informatics and Applications, University of Girona, 17003, Girona, Spain
| | - Taiyu Zhu
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, UK
| | - Ivan Contreras
- Modeling and Intelligent Control Engineering Laboratory, Institute of Informatics and Applications, University of Girona, 17003, Girona, Spain
| | - Pantelis Georgiou
- Centre for Bio-Inspired Technology, Department of Electrical and Electronic Engineering, Imperial College London, London, UK
| | - Josep Vehi
- Modeling and Intelligent Control Engineering Laboratory, Institute of Informatics and Applications, University of Girona, 17003, Girona, Spain.
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), 28001, Madrid, Spain.
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Ware J, Wilinska ME, Ruan Y, Allen JM, Boughton CK, Hartnell S, Bally L, de Beaufort C, Besser REJ, Campbell FM, Draxlbauer K, Elleri D, Evans ML, Fröhlich-Reiterer E, Ghatak A, Hofer SE, Kapellen TM, Leelarathna L, Mader JK, Mubita WM, Narendran P, Poettler T, Rami-Merhar B, Tauschmann M, Randell T, Thabit H, Thankamony A, Trevelyan N, Hovorka R. Safety of User-Initiated Intensification of Insulin Delivery Using Cambridge Hybrid Closed-Loop Algorithm. J Diabetes Sci Technol 2024; 18:882-888. [PMID: 36475908 PMCID: PMC11307210 DOI: 10.1177/19322968221141924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [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
OBJECTIVE Many hybrid closed-loop (HCL) systems struggle to manage unusually high glucose levels as experienced with intercurrent illness or pre-menstrually. Manual correction boluses may be needed, increasing hypoglycemia risk with overcorrection. The Cambridge HCL system includes a user-initiated algorithm intensification mode ("Boost"), activation of which increases automated insulin delivery by approximately 35%, while remaining glucose-responsive. In this analysis, we assessed the safety of "Boost" mode. METHODS We retrospectively analyzed data from closed-loop studies involving young children (1-7 years, n = 24), children and adolescents (10-17 years, n = 19), adults (≥24 years, n = 13), and older adults (≥60 years, n = 20) with type 1 diabetes. Outcomes were calculated per participant for days with ≥30 minutes of "Boost" use versus days with no "Boost" use. Participants with <10 "Boost" days were excluded. The main outcome was time spent in hypoglycemia <70 and <54 mg/dL. RESULTS Eight weeks of data for 76 participants were analyzed. There was no difference in time spent <70 and <54 mg/dL between "Boost" days and "non-Boost" days; mean difference: -0.10% (95% confidence interval [CI] -0.28 to 0.07; P = .249) time <70 mg/dL, and 0.03 (-0.04 to 0.09; P = .416) time < 54 mg/dL. Time in significant hyperglycemia >300 mg/dL was 1.39 percentage points (1.01 to 1.77; P < .001) higher on "Boost" days, with higher mean glucose and lower time in target range (P < .001). CONCLUSIONS Use of an algorithm intensification mode in HCL therapy is safe across all age groups with type 1 diabetes. The higher time in hyperglycemia observed on "Boost" days suggests that users are more likely to use algorithm intensification on days with extreme hyperglycemic excursions.
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Affiliation(s)
- Julia Ware
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Malgorzata E. Wilinska
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Yue Ruan
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Janet M. Allen
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Charlotte K. Boughton
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Diabetes and Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Sara Hartnell
- Department of Diabetes and Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Lia Bally
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Carine de Beaufort
- Diabetes & Endocrine Care Clinique Pediatrique, Centre Hospitalier de Luxembourg, Luxembourg City, Luxembourg
- Department of Paediatric Endocrinology, UZ-VUB, Brussels, Belgium
| | - Rachel E. J. Besser
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Fiona M. Campbell
- Department of Paediatric Diabetes, Leeds Children’s Hospital, Leeds, UK
| | | | - Daniela Elleri
- Department of Diabetes, Royal Hospital for Sick Children, Edinburgh, UK
| | - Mark L. Evans
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Diabetes and Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Elke Fröhlich-Reiterer
- Department of Pediatric and Adolescent Medicine, Medical University of Graz, Graz, Austria
| | - Atrayee Ghatak
- Department of Diabetes, Alder Hey Children’s NHS Foundation Trust, Liverpool, UK
| | - Sabine E. Hofer
- Department of Pediatrics I, Medical University of Innsbruck, Innsbruck, Austria
| | - Thomas M. Kapellen
- Hospital for Children and Adolescents, Leipzig University, Leipzig, Germany
| | - Lalantha Leelarathna
- Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Division of Diabetes, Endocrinology & Gastroenterology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Julia K. Mader
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Womba M. Mubita
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK
| | - Parth Narendran
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK
| | - Tina Poettler
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Birgit Rami-Merhar
- Department of Paediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Martin Tauschmann
- Department of Paediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Tabitha Randell
- Department of Paediatric Diabetes and Endocrinology, Nottingham Children’s Hospital, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Hood Thabit
- Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Division of Diabetes, Endocrinology & Gastroenterology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Ajay Thankamony
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Nicola Trevelyan
- Department of Paediatric Endocrinology and Diabetes, Southampton Children’s Hospital, Southampton General Hospital, Southampton, UK
| | - Roman Hovorka
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
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7
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Benhalima K, Beunen K, Van Wilder N, Ballaux D, Vanhaverbeke G, Taes Y, Aers XP, Nobels F, Marlier J, Lee D, Cuypers J, Preumont V, Siegelaar SE, Painter RC, Laenen A, Gillard P, Mathieu C. Comparing advanced hybrid closed loop therapy and standard insulin therapy in pregnant women with type 1 diabetes (CRISTAL): a parallel-group, open-label, randomised controlled trial. Lancet Diabetes Endocrinol 2024; 12:390-403. [PMID: 38697182 DOI: 10.1016/s2213-8587(24)00089-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 03/11/2024] [Accepted: 03/11/2024] [Indexed: 05/04/2024]
Abstract
BACKGROUND Advanced hybrid closed loop (AHCL) therapy can improve glycaemic control in pregnant women with type 1 diabetes. However, data are needed on the efficacy and safety of AHCL systems as these systems, such as the MiniMed 780G, are not currently approved for use in pregnant women. We aimed to investigate whether the MiniMed 780G can improve glycaemic control with less hypoglycaemia in pregnant women with type 1 diabetes. METHODS CRISTAL was a double-arm, parallel-group, open-label, randomised controlled trial conducted in secondary and tertiary care specialist endocrinology centres at 12 hospitals (11 in Belgium and one in the Netherlands). Pregnant women aged 18-45 years with type 1 diabetes were randomly assigned (1:1) to AHCL therapy (MiniMed 780G) or standard insulin therapy (standard of care) at a median of 10·1 (IQR 8·6-11·6) weeks of gestation. Randomisation was done centrally with minimisation dependent on baseline HbA1c, insulin administration method, and centre. Participants and study teams were not masked to group allocation. The primary outcome was proportion of time spent in the pregnancy-specific target glucose range (3·5-7·8 mmol/L), measured by continuous glucose monitoring (CGM) at 14-17 weeks, 20-23 weeks, 26-29 weeks, and 33-36 weeks. Key secondary outcomes were overnight time in target range, and time below glucose range (<3·5 mmol/L) overall and overnight. Analyses were conducted on an intention-to-treat basis. This trial is registered with ClinicalTrials.gov (NCT04520971). FINDINGS Between Jan 15, 2021 and Sept 30, 2022, 101 participants were screened, and 95 were randomly assigned to AHCL therapy (n=46) or standard insulin therapy (n=49). 43 patients assigned to AHCL therapy and 46 assigned to standard insulin therapy completed the study. At baseline, 91 (95·8%) participants used insulin pumps, and the mean HbA1c was 6·5% (SD 0·6). The mean proportion of time spent in the target range (averaged over four time periods) was 66·5% (SD 10·0) in the AHCL therapy group compared with 63·2% (12·4) in the standard insulin therapy group (adjusted mean difference 1·88 percentage points [95% CI -0·82 to 4·58], p=0·17). Overnight time in the target range was higher (adjusted mean difference 6·58 percentage points [95% CI 2·31 to 10·85], p=0·0026), and time below range overall (adjusted mean difference -1·34 percentage points [95% CI, -2·19 to -0·49], p=0·0020) and overnight (adjusted mean difference -1·86 percentage points [95% CI -2·90 to -0·81], p=0·0005) were lower with AHCL therapy than with standard insulin therapy. Participants assigned to AHCL therapy reported higher treatment satisfaction. No unanticipated safety events occurred with AHCL therapy. INTERPRETATION In pregnant women starting with tighter glycaemic control, AHCL therapy did not improve overall time in target range but improved overnight time in target range, reduced time below range, and improved treatment satisfaction. These data suggest that the MiniMed 780G can be safely used in pregnancy and provides some additional benefits compared with standard insulin therapy; however, it will be important to refine the algorithm to better align with pregnancy requirements. FUNDING Diabetes Liga Research Fund and Medtronic.
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Affiliation(s)
- Katrien Benhalima
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium; Department of Endocrinology, UZ Leuven, Leuven, Belgium.
| | - Kaat Beunen
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium
| | - Nancy Van Wilder
- Department of Endocrinology, University Hospital Brussels, Jette, Belgium
| | - Dominique Ballaux
- Department of Endocrinology, Vitaz Campus Sint-Niklaas Moerland, Sint-Niklaas, Belgium
| | - Gerd Vanhaverbeke
- Department of Endocrinology, General Hospital Groeninge Kortrijk, Kortrijk, Belgium
| | - Youri Taes
- Department of Endocrinology, General Hospital Sint-Jan Brugge, Brugge, Belgium
| | - Xavier-Philippe Aers
- Department of Endocrinology, General Hospital Delta Campus Rumbeke, Roeselare, Belgium
| | - Frank Nobels
- Department of Endocrinology, OLV Hospital Aalst, Aalst, Belgium
| | - Joke Marlier
- Department of Endocrinology, Ghent University Hospital, Gent, Belgium
| | - Dahae Lee
- Department of Endocrinology, Imelda Hospital Bonheiden, Bonheiden, Belgium
| | - Joke Cuypers
- Department of Endocrinology, General Hospital Turnhout Campus Sint-Jozef, Turnhout, Belgium
| | - Vanessa Preumont
- Department of Endocrinology, University Hospital Saint-Luc, Brussel, Belgium
| | - Sarah E Siegelaar
- Department of Endocrinologyand Metabolism, Amsterdam UMC location University of Amsterdam, Amsterdam, Netherlands; Amsterdam Gastroenterology Endocrinology and Metabolism, Amsterdam University Medical Centres, Amsterdam, Netherlands
| | - Rebecca C Painter
- Department of Obstetrics & Gynecology, Amsterdam University Medical Centres, Amsterdam, Netherlands; Amsterdam Reproduction and Development, Amsterdam University Medical Centres, Amsterdam, Netherlands
| | - Annouschka Laenen
- Center of Biostatics and Statistical bioinformatics, KU Leuven, Leuven, Belgium
| | - Pieter Gillard
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium; Department of Endocrinology, UZ Leuven, Leuven, Belgium
| | - Chantal Mathieu
- Clinical and Experimental Endocrinology, Department of Chronic Diseases and Metabolism, KU Leuven, Leuven, Belgium; Department of Endocrinology, UZ Leuven, Leuven, Belgium
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8
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Lablanche S, Delagenière J, Jalbert M, Sonnet E, Benichou M, Arnold N, Spiteri A, Le Berre JP, Renard E, Chevalier N, Borot S, Bonnemaison E, Coffin C, Teissier MP, Benhamou PY, Borel JC, Penfornis A, Joubert M, Kessler L. 12-Month Real-Life Efficacy of the MiniMed 780G Advanced Closed-Loop System in Patients Living with Type 1 Diabetes: A French Observational, Retrospective, Multicentric Study. Diabetes Technol Ther 2024; 26:426-432. [PMID: 38236643 DOI: 10.1089/dia.2023.0414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/10/2024]
Abstract
Aim: To evaluate the evolution of glycemic outcomes in patients living with type 1 diabetes (T1D) after 1 year of use of the MiniMed 780G advanced hybrid closed-loop (AHCL) system. Methods: We conducted an observational, retrospective, multicentric study in 20 centers in France. The primary objective was to evaluate the improvement in glycemic control after 1-year use of AHCL. The primary endpoint was the variation of time in range (TIR) between pre-AHCL and after 1-year use of AHCL. Secondary objectives were to analyze the glycemic outcomes after 3, 6, and 12 months of AHCL use, the safety, and the long-term observance of AHCL. Results: Two hundred twenty patients were included, and 200 were analyzed for the primary endpoint. 92.7% of patients continued to use AHCL. After 1 year of use of AHCL, TIR was 72.5% ± 10.6% (+9.1%; 95% confidence interval [CI] [7.6-10.5] compared to pre-AHCL initiation, P < 0.001), HbA1c 7.1% ± 0.7% (-0.5%; 95% CI [-0.6 to -0.4]; P < 0.001), time below range 2.0% [1.0; 3.0] (0.0% [-2.0; 0.0], P < 0.001), and time above range 24.8% ± 10.9% (-7.3%; 95% CI [-8.8 to -5.7]; P < 0.001). More patients achieved the glycemic treatment goals of HbA1c <7.0% (45.1% vs. 18.1%, P < 0.001) and TIR >70% (59.0% vs. 29.5% P < 0.001) when compared with pre-AHCL. Five patients experienced severe hypoglycemia events and two patients experienced ketoacidosis. Conclusion: After 1 year of use of AHCL, people living with T1D safely improved their glucose control and a higher proportion of them achieved optimal glycemic control.
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Affiliation(s)
- Sandrine Lablanche
- Grenoble Alpes Univeristy, Grenoble Alpes University Hospital, Endocrinology-Diabetology-Nutrition Department, University, Saint-Martind'Heres, France
| | - Johanna Delagenière
- Grenoble Alpes Univeristy, Grenoble Alpes University Hospital, Endocrinology-Diabetology-Nutrition Department, University, Saint-Martind'Heres, France
| | - Manon Jalbert
- Grenoble Alpes Univeristy, Grenoble Alpes University Hospital, Endocrinology-Diabetology-Nutrition Department, University, Saint-Martind'Heres, France
| | - Emmanuel Sonnet
- Endocrinology-Diabetology Department, Brest University Hospital, Brest, France
| | - Muriel Benichou
- Endocrinology-Diabetology Department, Perpignan Hospital, Perpignan, France
| | | | - Anne Spiteri
- Pediatric Department, Grenoble Alpes University Hospital, Saint-Martin-d'Heres, France
| | | | - Eric Renard
- Endocrinology-Diabetology Department, Montpellier University Hospital, Montpellier, France
| | - Nicolas Chevalier
- Endocrinology-Diabetology Department, Nice University Hospital, Nice, France
| | - Sophie Borot
- Endocrinology-Diabetology Department, Jean-Minjoz University Hospital, Besançon, France
| | | | - Christine Coffin
- Endocrinology-Diabetology Department, Périgueux Hospital, Périgueux, France
| | | | - Pierre Yves Benhamou
- Grenoble Alpes Univeristy, Grenoble Alpes University Hospital, Endocrinology-Diabetology-Nutrition Department, University, Saint-Martind'Heres, France
| | | | - Alfred Penfornis
- Endocrinology-Diabetology Department, Centre Hospitalier Sud Francilien, Corbeil-Essonnes, France
| | - Michael Joubert
- Diabetes Care Unit, Caen University Hospital, UNICAEN, Caen, France
| | - Laurence Kessler
- Endocrinology-Diabetology Department, Strasbourg University Hospital, Strasbourg, France
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9
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Giraudot C, Alazard-Dany N, Lambert V. [Closed-loop synthetic gene circuits for cell-based therapies]. Med Sci (Paris) 2024; 40:437-444. [PMID: 38819279 DOI: 10.1051/medsci/2024054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/01/2024] Open
Abstract
Recent advances in synthetic biology have paved the way for new cellular therapies, using cells capable of autonomously treating chronic diseases. These cells integrate a set of genes functioning in a closed-loop synthetic circuit, delivering a therapeutic effector in response to a specific pathological signal. While promising in mice, these therapies face clinical challenges related to safety and feasibility of in vivo implementation. The latest generations of synthetic circuits aim to address these issues through advanced bioengineering strategies outlined in this article.
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Affiliation(s)
- Clélia Giraudot
- École normale supérieure de Lyon, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France - Université de Lyon, VetAgro Sup, Marcy-l'Étoile, France
| | - Nathalie Alazard-Dany
- École normale supérieure de Lyon, Université Claude Bernard Lyon 1, Université de Lyon, Lyon, France
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10
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Castorani V, Rigamonti A, Frontino G, Morotti E, Sandullo F, Scialabba F, Arrigoni F, Dionisi B, Foglino R, Morosini C, Olivieri G, Bonfanti R. Turning the tides: achieving rapid and safe glucose control in adolescents with suboptimally controlled type 1 diabetes using advanced hybrid closed loop systems. Front Endocrinol (Lausanne) 2024; 15:1243565. [PMID: 38628580 PMCID: PMC11019566 DOI: 10.3389/fendo.2024.1243565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 01/04/2024] [Indexed: 04/19/2024] Open
Abstract
Aim Many adolescents with T1D experience a decline in metabolic control due to erratic eating habits and subpar adherence to treatment regimens. The objective of our retrospective observational study was to assess the effect of the Tandem Control IQ (CIQ) advanced hybrid closed-loop (AHCL) system on a cohort of adolescents with suboptimal glucose control. Methods We retrospectively evaluated 20 non-adherent patients with T1D, who were inconsistently using Multiple Daily Injections (MDIs) and flash glucose monitoring and were subsequently started and on CIQ. Glucometrics and the Glucose Risk Index were assessed at baseline and after 2 weeks, 1 month, and 6 months of CIQ use. Results The study included 20 adolescents with T1D (HbA1c: 10.0% ± 1.7). Time in range (TIR) increased from 27.1% ± 13.7 at baseline to 68.6% ± 14.2 at 2 weeks, 66.6% ± 10.7 at 1 month, and 60.4% ± 13.3 at 6 months of CIQ use. Time above range (TAR) >250 mg/dL decreased from 46.1% ± 23.8 to 9.9% ± 9.5 at 2 weeks, 10.8% ± 6.1 at 1 month, and 15.5% ± 10.5 at 6 months of AHCL use. Mean glucose levels improved from 251 mg/dL ± 68.9 to 175mg/dL ± 25.5 after 6 months of CIQ use. The Glucose Risk Index (GRI) also significantly reduced from 102 to 48 at 6 months of CIQ. HbA1c also improved from 10.0% ± 1.7 at baseline to 7.0% ± 0.7 after 6 months. Two patients experienced a single episode of mild diabetic ketoacidosis (DKA). Conclusions AHCL systems provide a significant, rapid, and safe improvement in glucose control. This marks a pivotal advancement in technology that primarily benefited those who were already compliant.
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Affiliation(s)
- Valeria Castorani
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Andrea Rigamonti
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Giulio Frontino
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Elisa Morotti
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Federica Sandullo
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Francesco Scialabba
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Francesca Arrigoni
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Benedetta Dionisi
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Riccardo Foglino
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Camilla Morosini
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Gabriele Olivieri
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Riccardo Bonfanti
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
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11
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Propper-Lewinsohn T, Elran-Barak R, Gillon-Keren M, Yackobovitch-Gavan M, Liberman A, Phillip M, Shalitin S. Disordered Eating Behaviors Among Adolescents and Young Adults with Type 1 Diabetes Treated with Insulin Pumps and Hybrid Closed-Loop Systems. Diabetes Technol Ther 2024; 26:229-237. [PMID: 38090768 DOI: 10.1089/dia.2023.0500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2024]
Abstract
Background and Aims: Disordered eating behaviors (DEB) are more common among individuals with type 1 diabetes (T1D) compared to those without, and for insulin pump users may be associated with higher hemoglobin A1c (HbA1c). We investigated DEB risk factors among insulin pump-treated individuals with T1D and clinical characteristics of hybrid closed-loop (HCL) systems' users by DEB level. Methods: An observational, cross-sectional study of 167 insulin pump-treated individuals with T1D, 13-21 years of age. Data were obtained from patients' medical charts with additional self-reported questionnaires, including assessment of DEB. Results: DEB were found in 71 (42.5%) individuals, and positively associated with female sex (β = 2.98 [standard error (SE) = 1.31], P = 0.025), body mass index (BMI)-Z-score (β = 2.12 [SE = 0.64], P = 0.001), HbA1c (β = 1.40 [SE = 0.45], P = 0.02), and higher rate of pump discontinuation (β = 4.48 [SE = 1.99], P = 0.026). The use of HCL systems compared to insulin pumps was associated with higher BMI-Z-score (odds ratio [OR]: 3.46 [95% confidence interval, CI: 1.52-7.87], P = 0.003) and tendency to lower HbA1c level (OR: 0.44 [95% CI: 0.18-1.09], P = 0.078) among individuals without DEB, and with lower HbA1c level (OR: 0.29 [95% CI: 0.10-0.83], P = 0.022) and higher socioeconomic status (OR: 1.73 [95% CI: 1.09-2.74], P = 0.020) among individuals with DEB. Conclusions: DEB are common among individuals with T1D treated with insulin pumps and are associated with higher HbA1c levels. Among T1D individuals with DEB, HCL system use is associated with lower HbA1c compared to insulin pump treatment. Our findings highlight the importance of regular screening for DEB and its risk factors to improve pump treatment and diabetes management. Moreover, individuals with DEB using HCL systems may benefit from reduced HbA1c levels.
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Affiliation(s)
- Tamar Propper-Lewinsohn
- The Institute of Endocrinology and Diabetes, Schneider Children's Medical Center, Petah Tikva, Israel
- School of Public Health, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel
| | - Roni Elran-Barak
- School of Public Health, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel
| | - Michal Gillon-Keren
- The Institute of Endocrinology and Diabetes, Schneider Children's Medical Center, Petah Tikva, Israel
- Faculty of Sciences, Kibbutzim College of Education Technology and the Arts, Tel Aviv, Israel
| | - Michal Yackobovitch-Gavan
- The Institute of Endocrinology and Diabetes, Schneider Children's Medical Center, Petah Tikva, Israel
- Department of Epidemiology and Preventive Medicine, School of Public Health, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Alon Liberman
- The Institute of Endocrinology and Diabetes, Schneider Children's Medical Center, Petah Tikva, Israel
| | - Moshe Phillip
- The Institute of Endocrinology and Diabetes, Schneider Children's Medical Center, Petah Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Shlomit Shalitin
- The Institute of Endocrinology and Diabetes, Schneider Children's Medical Center, Petah Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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12
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Fox DS, Ware J, Boughton CK, Allen JM, Wilinska ME, Tauschmann M, Denvir L, Thankamony A, Campbell F, Wadwa RP, Buckingham BA, Davis N, DiMeglio LA, Mauras N, Besser REJ, Ghatak A, Weinzimer SA, Kanapka L, Kollman C, Sibayan J, Beck RW, Hood KK, Hovorka R. Cost-Effectiveness of Closed-Loop Automated Insulin Delivery Using the Cambridge Hybrid Algorithm in Children and Adolescents with Type 1 Diabetes: Results from a Multicenter 6-Month Randomized Trial. J Diabetes Sci Technol 2024:19322968241231950. [PMID: 38494876 DOI: 10.1177/19322968241231950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
BACKGROUND/OBJECTIVE The main objective of this study is to evaluate the incremental cost-effectiveness (ICER) of the Cambridge hybrid closed-loop automated insulin delivery (AID) algorithm versus usual care for children and adolescents with type 1 diabetes (T1D). METHODS This multicenter, binational, parallel-controlled trial randomized 133 insulin pump using participants aged 6 to 18 years to either AID (n = 65) or usual care (n = 68) for 6 months. Both within-trial and lifetime cost-effectiveness were analyzed. Analysis focused on the treatment subgroup (n = 21) who received the much more reliable CamAPS FX hardware iteration and their contemporaneous control group (n = 24). Lifetime complications and costs were simulated via an updated Sheffield T1D policy model. RESULTS Within-trial, both groups had indistinguishable and statistically unchanged health-related quality of life, and statistically similar hypoglycemia, severe hypoglycemia, and diabetic ketoacidosis (DKA) event rates. Total health care utilization was higher in the treatment group. Both the overall treatment group and CamAPS FX subgroup exhibited improved HbA1C (-0.32%, 95% CI: -0.59 to -0.04; P = .02, and -1.05%, 95% CI: -1.43 to -0.67; P < .001, respectively). Modeling projected increased expected lifespan of 5.36 years and discounted quality-adjusted life years (QALYs) of 1.16 (U.K. tariffs) and 1.52 (U.S. tariffs) in the CamAPS FX subgroup. Estimated ICERs for the subgroup were £19 324/QALY (United Kingdom) and -$3917/QALY (United States). For subgroup patients already using continuous glucose monitors (CGM), ICERs were £10 096/QALY (United Kingdom) and -$33 616/QALY (United States). Probabilistic sensitivity analysis generated mean ICERs of £19 342/QALY (95% CI: £15 903/QALY to £22 929/QALY) (United Kingdom) and -$28 283/QALY (95% CI: -$59 607/QALY to $1858/QALY) (United States). CONCLUSIONS For children and adolescents with T1D on insulin pump therapy, AID using the Cambridge algorithm appears cost-effective below a £20 000/QALY threshold (United Kingdom) and cost saving (United States).
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Affiliation(s)
- D Steven Fox
- Department of Pharmaceutical and Health Economics, Mann School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - Julia Ware
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Charlotte K Boughton
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Diabetes & Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Janet M Allen
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Malgorzata E Wilinska
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Martin Tauschmann
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Louise Denvir
- Department of Paediatric Diabetes and Endocrinology, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Ajay Thankamony
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Fiona Campbell
- Department of Paediatric Diabetes, Leeds Children's Hospital, Leeds, UK
| | - R Paul Wadwa
- Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Bruce A Buckingham
- Stanford University School of Medicine, Stanford Diabetes Research Center, Stanford, CA, USA
| | - Nikki Davis
- Department of Paediatric Endocrinology and Diabetes, Southampton Children's Hospital, Southampton General Hospital, Southampton, UK
| | - Linda A DiMeglio
- Division of Pediatric Endocrinology and Diabetology, Department of Pediatrics, Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Nelly Mauras
- Nemours Children's Health, Jacksonville, FL, USA
| | - Rachel E J Besser
- Oxford University Hospitals NHS Foundation Trust, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Department of Paediatrics, University of Oxford, Oxford, UK
| | | | | | | | | | - Judy Sibayan
- The Jaeb Center for Health Research, Tampa, FL, USA
| | - Roy W Beck
- The Jaeb Center for Health Research, Tampa, FL, USA
| | - Korey K Hood
- Stanford University School of Medicine, Stanford Diabetes Research Center, Stanford, CA, USA
| | - Roman Hovorka
- Department of Pharmaceutical and Health Economics, Mann School of Pharmacy, University of Southern California, Los Angeles, CA, USA
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
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13
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Mazzotta FA, Lucaccini Paoli L, Rizzi A, Tartaglione L, Leo ML, Cristallo F, Popolla V, DI Leo M, Pontecorvi A, Pitocco D. The development and evolution of insulin pumps: from early beginnings to future prospects. Minerva Endocrinol (Torino) 2024; 49:85-99. [PMID: 37227318 DOI: 10.23736/s2724-6507.23.04030-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
Diabetes technology has proliferated extensively over the past few decades with vast ameliorations in glucose monitoring and in insulin delivery systems. From a treatment based on daily insulin injections, we have moved to increasingly advanced technologies. Despite such advancements which have allowed better glycemic control, decreased diabetes-related complications, and improved the quality of life among diabetic patients, it has left many individuals unsatisfied with the current rate of commercial artificial pancreas development, stemming the need for further research into novel technologies. Accordingly, the Juvenile Diabetes Research Foundation has marked three generations for the development of an artificial pancreas comprising historical landmarks and future prospects which aim to produce an advanced technological system that attempts to mimic the endogenous pancreas, eliminating the need for user input. This review presents a synopsis of the development and evolution of insulin pumps, starting with the earliest technologies available such as continuous subcutaneous insulin infusion and continuous glucose monitoring as separate components, to currently available integrated advanced closed-loop hybrid systems and possible future technologies. The aim of the review is to provide insight of the advantages and limitations of past and currently available insulin pumps with the hope of driving research into novel technologies that attempt to mimic endogenous pancreatic function as closely as possible.
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Affiliation(s)
- Francesco A Mazzotta
- Department of Endocrinology, Catholic University of the Sacred Heart, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Lorenzo Lucaccini Paoli
- Department of Endocrinology, Catholic University of the Sacred Heart, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy -
| | - Alessandro Rizzi
- Diabetes Care Unit, Catholic University of the Sacred Heart, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Linda Tartaglione
- Diabetes Care Unit, Catholic University of the Sacred Heart, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Maria L Leo
- Department of Endocrinology, Catholic University of the Sacred Heart, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Federica Cristallo
- Diabetes Care Unit, Catholic University of the Sacred Heart, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Valentina Popolla
- Diabetes Care Unit, Catholic University of the Sacred Heart, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Mauro DI Leo
- Diabetes Care Unit, Catholic University of the Sacred Heart, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Alfredo Pontecorvi
- Department of Endocrinology, Catholic University of the Sacred Heart, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Dario Pitocco
- Diabetes Care Unit, Catholic University of the Sacred Heart, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
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14
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Zrubka Z, Kertész G, Gulácsi L, Czere J, Hölgyesi Á, Nezhad HM, Mosavi A, Kovács L, Butte AJ, Péntek M. The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review. J Med Internet Res 2024; 26:e47430. [PMID: 38241075 PMCID: PMC10837761 DOI: 10.2196/47430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 04/29/2023] [Accepted: 11/17/2023] [Indexed: 01/23/2024] Open
Abstract
BACKGROUND Diabetes mellitus (DM) is a major health concern among children with the widespread adoption of advanced technologies. However, concerns are growing about the transparency, replicability, biasedness, and overall validity of artificial intelligence studies in medicine. OBJECTIVE We aimed to systematically review the reporting quality of machine learning (ML) studies of pediatric DM using the Minimum Information About Clinical Artificial Intelligence Modelling (MI-CLAIM) checklist, a general reporting guideline for medical artificial intelligence studies. METHODS We searched the PubMed and Web of Science databases from 2016 to 2020. Studies were included if the use of ML was reported in children with DM aged 2 to 18 years, including studies on complications, screening studies, and in silico samples. In studies following the ML workflow of training, validation, and testing of results, reporting quality was assessed via MI-CLAIM by consensus judgments of independent reviewer pairs. Positive answers to the 17 binary items regarding sufficient reporting were qualitatively summarized and counted as a proxy measure of reporting quality. The synthesis of results included testing the association of reporting quality with publication and data type, participants (human or in silico), research goals, level of code sharing, and the scientific field of publication (medical or engineering), as well as with expert judgments of clinical impact and reproducibility. RESULTS After screening 1043 records, 28 studies were included. The sample size of the training cohort ranged from 5 to 561. Six studies featured only in silico patients. The reporting quality was low, with great variation among the 21 studies assessed using MI-CLAIM. The number of items with sufficient reporting ranged from 4 to 12 (mean 7.43, SD 2.62). The items on research questions and data characterization were reported adequately most often, whereas items on patient characteristics and model examination were reported adequately least often. The representativeness of the training and test cohorts to real-world settings and the adequacy of model performance evaluation were the most difficult to judge. Reporting quality improved over time (r=0.50; P=.02); it was higher than average in prognostic biomarker and risk factor studies (P=.04) and lower in noninvasive hypoglycemia detection studies (P=.006), higher in studies published in medical versus engineering journals (P=.004), and higher in studies sharing any code of the ML pipeline versus not sharing (P=.003). The association between expert judgments and MI-CLAIM ratings was not significant. CONCLUSIONS The reporting quality of ML studies in the pediatric population with DM was generally low. Important details for clinicians, such as patient characteristics; comparison with the state-of-the-art solution; and model examination for valid, unbiased, and robust results, were often the weak points of reporting. To assess their clinical utility, the reporting standards of ML studies must evolve, and algorithms for this challenging population must become more transparent and replicable.
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Affiliation(s)
- Zsombor Zrubka
- HECON Health Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary
| | - Gábor Kertész
- John von Neumann Faculty of Informatics, Óbuda University, Budapest, Hungary
| | - László Gulácsi
- HECON Health Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary
| | - János Czere
- Doctoral School of Innovation Management, Óbuda University, Budapest, Hungary
| | - Áron Hölgyesi
- HECON Health Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary
- Doctoral School of Molecular Medicine, Semmelweis University, Budapest, Hungary
| | - Hossein Motahari Nezhad
- HECON Health Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary
- Doctoral School of Business and Management, Corvinus University of Budapest, Budapest, Hungary
| | - Amir Mosavi
- John von Neumann Faculty of Informatics, Óbuda University, Budapest, Hungary
| | - Levente Kovács
- Physiological Controls Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary
| | - Atul J Butte
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA, United States
| | - Márta Péntek
- HECON Health Economics Research Center, University Research and Innovation Center, Óbuda University, Budapest, Hungary
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15
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Benhalima K, Jendle J, Beunen K, Ringholm L. Automated Insulin Delivery for Pregnant Women With Type 1 Diabetes: Where do we stand? J Diabetes Sci Technol 2024:19322968231223934. [PMID: 38197363 DOI: 10.1177/19322968231223934] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2024]
Abstract
Automated insulin delivery (AID) systems mimic an artificial pancreas via a predictive algorithm integrated with continuous glucose monitoring (CGM) and an insulin pump, thereby providing AID. Outside of pregnancy, AID has led to a paradigm shift in the management of people with type 1 diabetes (T1D), leading to improvements in glycemic control with lower risk for hypoglycemia and improved quality of life. As the use of AID in clinical practice is increasing, the number of women of reproductive age becoming pregnant while using AID is also expected to increase. The requirement for lower glucose targets than outside of pregnancy and for frequent adjustments of insulin doses during pregnancy may impact the effectiveness and safety of AID when using algorithms for non-pregnant populations with T1D. Currently, the CamAPS® FX is the only AID approved for use in pregnancy. A recent randomized controlled trial (RCT) with CamAPS® FX demonstrated a 10% increase in time in range in a pregnant population with T1D and a baseline glycated hemoglobin (HbA1c) ≥ 48 mmol/mol (6.5%). Off-label use of AID not approved for pregnancy are currently also being evaluated in ongoing RCTs. More evidence is needed on the impact of AID on maternal and neonatal outcomes. We review the current evidence on the use of AID in pregnancy and provide an overview of the completed and ongoing RCTs evaluating AID in pregnancy. In addition, we discuss the advantages and challenges of the use of current AID in pregnancy and future directions for research.
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Affiliation(s)
- Katrien Benhalima
- Department of Endocrinology, University Hospital Gasthuisberg, KU Leuven, Leuven, Belgium
| | - Johan Jendle
- Diabetes Endocrinology and Metabolism Research Centre, School of Medicine, Örebro University, Örebro, Sweden
| | - Kaat Beunen
- Department of Endocrinology, University Hospital Gasthuisberg, KU Leuven, Leuven, Belgium
| | - Lene Ringholm
- Center for Pregnant Women with Diabetes, Department of Endocrinology and Metabolism, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
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Seget S, Chobot A, Rusak E, Ochab A, Bielawska A, Polanska J, Jarosz-Chobot P. MiniMed 780GTM in children with type 1 diabetes under seven years of age: Prospective open-label, single-arm, double-center, follow-up study. Technol Health Care 2024; 32:1463-1472. [PMID: 37781828 DOI: 10.3233/thc-230490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
BACKGROUND Given the steadily rising incidence of type 1 diabetes (T1D), particularly among the youngest preschool children, coupled with well-documented challenges of achieving and maintaining optimal metabolic control in this age group, there is a growing need for advanced technological devices. OBJECTIVE To evaluate glycaemic control in children below the age of seven with type 1 diabetes (T1D) and assess the safety of the advanced hybrid closed loop (AHCL) system in comparison to the previous treatment method, a sensor-augmented pump with predictive low-glucose suspend (SAP-PLGS). METHOD Data from 10 children (aged 2.60-6.98 years) with T1D who transitioned to the AHCL system from SAP-PLGS were analysed. SAP-PLGS records from two weeks prior to the initiation of AHCL were compared with records from the initial four weeks post-switch (excluding the training period). These data were examined at two 2-week intervals and compared with records from two weeks post six-month usage of the AHCL. RESULTS A significant decrease in the average nighttime glucose concentration was observed compared to pre-AHCL values (p= 0.001, concordance W = 0.53). The Glucose Management Indicator (GMI) value significantly decreased from 6.88 ± 0.37% to 6.52 ± 0.32% (p= 0.018, rbc = 0.93) immediately following the device switch and stabilized at 6.50 ± 0.28% (p= 0.001, W = 0.53) and 6.55 ± 0.41% (p= 0.001, W = 0.53) at subsequent stages of the study. An improvement was also observed in mean glucose values for time spent < 54 mg/dl, while the proportion of time within this range was maintained, both during the day (p< 0.001, W = 0.58) and at night (p= 0.002, W = 0.83). CONCLUSION The AHCL MiniMed 780GTM system improved glycaemic control in the studied group of children under seven years of age with T1D compared to previous SAP-PLGS therapy. It proved to be safe for delivering insulin in this age group.
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Affiliation(s)
- Sebastian Seget
- Department of Children's Diabetology, Medical University of Silesia, Katowice, Poland
| | - Agata Chobot
- Department of Pediatrics, Institute of Medical Sciences, University of Opole, Opole, Poland
| | - Ewa Rusak
- Department of Children's Diabetology, Medical University of Silesia, Katowice, Poland
| | - Agnieszka Ochab
- Department of Pediatrics, Institute of Medical Sciences, University of Opole, Opole, Poland
| | - Anna Bielawska
- Department of Children's Diabetology, Medical University of Silesia, Katowice, Poland
| | - Joanna Polanska
- Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland
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Criego AB, Carlson AL, Brown SA, Forlenza GP, Bode BW, Levy CJ, Hansen DW, Hirsch IB, Bergenstal RM, Sherr JL, Mehta SN, Laffel LM, Shah VN, Bhargava A, Weinstock RS, MacLeish SA, DeSalvo DJ, Jones TC, Aleppo G, Buckingham BA, Ly TT. Two Years with a Tubeless Automated Insulin Delivery System: A Single-Arm Multicenter Trial in Children, Adolescents, and Adults with Type 1 Diabetes. Diabetes Technol Ther 2024; 26:11-23. [PMID: 37850941 PMCID: PMC10794844 DOI: 10.1089/dia.2023.0364] [Citation(s) in RCA: 2] [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: 10/19/2023]
Abstract
Background: The Omnipod® 5 Automated Insulin Delivery (AID) System was shown to be safe and effective following 3 months of use in people with type 1 diabetes (T1D); however, data on the durability of these results are limited. This study evaluated the long-term safety and effectiveness of Omnipod 5 use in people with T1D during up to 2 years of use. Materials and Methods: After a 3-month single-arm, multicenter, pivotal trial in children (6-13.9 years) and adolescents/adults (14-70 years), participants could continue system use in an extension phase. HbA1c was measured every 3 months for up to 15 months; continuous glucose monitor metrics were collected for up to 2 years. Results: Participants (N = 224) completed median (interquartile range) 22.3 (21.7, 22.7) months of AID. HbA1c was reduced in the pivotal trial from 7.7% ± 0.9% in children and 7.2% ± 0.9% in adolescents/adults to 7.0% ± 0.6% and 6.8% ± 0.7%, respectively, (P < 0.0001), and was maintained at 7.2% ± 0.7% and 6.9% ± 0.6% after 15 months (P < 0.0001 from baseline). Time in target range (70-180 mg/dL) increased from 52.4% ± 15.6% in children and 63.6% ± 16.5% in adolescents/adults at baseline to 67.9% ± 8.0% and 73.8% ± 10.8%, respectively, during the pivotal trial (P < 0.0001) and was maintained at 65.9% ± 8.9% and 72.9% ± 11.3% during the extension (P < 0.0001 from baseline). One episode of diabetic ketoacidosis and seven episodes of severe hypoglycemia occurred during the extension. Children and adolescents/adults spent median 96.1% and 96.3% of time in Automated Mode, respectively. Conclusion: Our study supports that long-term use of the Omnipod 5 AID System can safely maintain improvements in glycemic outcomes for up to 2 years of use in people with T1D. Clinical Trials Registration Number: NCT04196140.
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Affiliation(s)
- Amy B. Criego
- Department of Pediatric Endocrinology, International Diabetes Center, Park Nicollet, Minneapolis, Minnesota, USA
| | - Anders L. Carlson
- International Diabetes Center, Park Nicollet, HealthPartners, Minneapolis, Minnesota, USA
| | - Sue A. Brown
- Division of Endocrinology, Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | - Gregory P. Forlenza
- Department of Pediatrics, Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | | | - Carol J. Levy
- Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - David W. Hansen
- Department of Pediatrics, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Irl B. Hirsch
- Department of Medicine, University of Washington, Seattle, Washington, USA
| | - Richard M. Bergenstal
- International Diabetes Center, Park Nicollet, HealthPartners, Minneapolis, Minnesota, USA
| | - Jennifer L. Sherr
- Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut, USA
| | - Sanjeev N. Mehta
- Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Lori M. Laffel
- Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Viral N. Shah
- Department of Pediatrics, Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | | | - Ruth S. Weinstock
- Department of Medicine, SUNY Upstate Medical University, Syracuse, New York, USA
| | - Sarah A. MacLeish
- Department of Pediatrics, University Hospitals Cleveland Medical Center, Rainbow Babies and Children's Hospital, Cleveland, Ohio, USA
| | - Daniel J. DeSalvo
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
| | - Thomas C. Jones
- Department of Research, East Coast Institute for Research at The Jones Center, Macon, Georgia, USA
| | - Grazia Aleppo
- Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Bruce A. Buckingham
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California, USA
| | - Trang T. Ly
- Insulet Corporation, Acton, Massachusetts, USA
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18
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Gitsi E, Livadas S, Angelopoulos N, Paparodis RD, Raftopoulou M, Argyrakopoulou G. A Nutritional Approach to Optimizing Pump Therapy in Type 1 Diabetes Mellitus. Nutrients 2023; 15:4897. [PMID: 38068755 PMCID: PMC10707799 DOI: 10.3390/nu15234897] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2023] [Revised: 11/14/2023] [Accepted: 11/20/2023] [Indexed: 12/18/2023] Open
Abstract
Achieving optimal glucose control in individuals with type 1 diabetes (T1DM) continues to pose a significant challenge. While continuous insulin infusion systems have shown promise as an alternative to conventional insulin therapy, there remains a crucial need for greater awareness regarding the necessary adaptations for various special circumstances. Nutritional choices play an essential role in the efficacy of diabetes management and overall health status for patients with T1DM. Factors such as effective carbohydrate counting, assessment of the macronutrient composition of meals, and comprehending the concept of the glycemic index of foods are paramount in making informed pre-meal adjustments when utilizing insulin pumps. Furthermore, the ability to handle such situations as physical exercise, illness, pregnancy, and lactation by making appropriate adjustments in nutrition and pump settings should be cultivated within the patient-practitioner relationship. This review aims to provide healthcare practitioners with practical guidance on optimizing care for individuals living with T1DM. It includes recommendations on carbohydrate counting, managing mixed meals and the glycemic index, addressing exercise-related challenges, coping with illness, and managing nutritional needs during pregnancy and lactation. Additionally, considerations relating to closed-loop systems with regard to nutrition are addressed. By implementing these strategies, healthcare providers can better equip themselves to support individuals with T1DM in achieving improved diabetes management and enhanced quality of life.
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Affiliation(s)
- Evdoxia Gitsi
- Diabetes and Obesity Unit, Athens Medical Center, 15125 Athens, Greece; (E.G.); (M.R.)
| | | | | | - Rodis D. Paparodis
- Center for Diabetes and Endocrine Research, College of Medicine and Life Sciences, University of Toledo, Toledo, OH 43614, USA;
| | - Marina Raftopoulou
- Diabetes and Obesity Unit, Athens Medical Center, 15125 Athens, Greece; (E.G.); (M.R.)
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Tejedor M, Hjerde SN, Myhre JN, Godtliebsen F. Evaluating Deep Q-Learning Algorithms for Controlling Blood Glucose in In Silico Type 1 Diabetes. Diagnostics (Basel) 2023; 13:3150. [PMID: 37835893 PMCID: PMC10572616 DOI: 10.3390/diagnostics13193150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 09/22/2023] [Accepted: 09/29/2023] [Indexed: 10/15/2023] Open
Abstract
Patients with type 1 diabetes must continually decide how much insulin to inject before each meal to maintain blood glucose levels within a healthy range. Recent research has worked on a solution for this burden, showing the potential of reinforcement learning as an emerging approach for the task of controlling blood glucose levels. In this paper, we test and evaluate several deep Q-learning algorithms for automated and personalized blood glucose regulation in an in silico type 1 diabetes patient with the goal of estimating and delivering proper insulin doses. The proposed algorithms are model-free approaches with no prior information about the patient. We used the Hovorka model with meal variation and carbohydrate counting errors to simulate the patient included in this work. Our experiments compare different deep Q-learning extensions showing promising results controlling blood glucose levels, with some of the proposed algorithms outperforming standard baseline treatment.
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Affiliation(s)
- Miguel Tejedor
- Norwegian Centre for E-Health Research, P.O. Box 35, N-9038 Tromsø, Norway;
| | - Sigurd Nordtveit Hjerde
- Faculty of Science and Technology, Norwegian University of Life Sciences, Postboks 5003 NMBU, 1432 Ås, Norway;
| | - Jonas Nordhaug Myhre
- NORCE Norwegian Research Centre, Postboks 22, Nygårdstangen, 5838 Bergen, Norway;
| | - Fred Godtliebsen
- Department of Mathematics and Statistics, UiT—The Arctic University of Norway, P.O. Box 6050 Langnes, N-9037 Tromsø, Norway
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Sehgal S, De Bock M, Jones S, Frewen C, Wheeler BJ. User experiences during the transition to calibration-free sensors with remote monitoring while using automated insulin delivery - a qualitative study. Front Endocrinol (Lausanne) 2023; 14:1214975. [PMID: 37693343 PMCID: PMC10484395 DOI: 10.3389/fendo.2023.1214975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 07/31/2023] [Indexed: 09/12/2023] Open
Abstract
Introduction To evaluate the experiences of patients with type 1 diabetes following transition from a calibration-requiring to a calibration-free sensor and remote monitoring in the context of using automated insulin delivery (AID). Research design and methods Fifteen participants aged 7-65 years with type 1 diabetes participating in a longitudinal study used a Medtronic® advanced hybrid closed loop (AHCL) device with initially calibration-requiring then calibration-free sensors. Qualitative interviews were conducted ≥20 weeks following use of the calibration-requiring and ≥4 weeks after use of the calibration-free sensors/remote monitoring. Thematic analysis was used to identify key themes and subthemes. Results At baseline, mean diabetes duration was 14.5 years ( ± 10.9), mean Hba1c 54.8 mmol/mol ( ± 10.2) (7.2 ± 0.9%) and Time in range 75.4% ( ± 11.6). Participants reported a progressive improvement in digital and lifestyle integration, and device trust following transition to calibration-free sensors with remote monitoring potential. They also reported a reduced need for capillary glucose, increased device satisfaction and trust, and reduced burden of diabetes care. Negative aspects reported included periodic early sensor loss, and for some, impaired integration with mobile devices. Conclusion Transitioning to calibration-free sensors with remote monitoring while using AHCL was associated with better user experience, including perceptions of improved quality of life and a reduced burden of diabetes care. Appropriate expectation setting, training, and ongoing support allow for the optimal user experience while using AHCL. Clinical trial registration https://www.anzctr.org.au, identifier ACTRN12621000360819.
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Affiliation(s)
- Shekhar Sehgal
- Department of Women’s and Children’s Health, Dunedin School of Medicine, Otago Medical School, University of Otago, Dunedin, New Zealand
| | - Martin De Bock
- Department of Pediatrics, University of Otago, Christchurch, New Zealand
- Pediatric Endocrinology, Health New Zealand (NZ)-Canterbury, Christchurch, New Zealand
| | - Shirley Jones
- Department of Women’s and Children’s Health, Dunedin School of Medicine, Otago Medical School, University of Otago, Dunedin, New Zealand
| | - Carla Frewen
- Department of Women’s and Children’s Health, Dunedin School of Medicine, Otago Medical School, University of Otago, Dunedin, New Zealand
| | - Benjamin J. Wheeler
- Department of Women’s and Children’s Health, Dunedin School of Medicine, Otago Medical School, University of Otago, Dunedin, New Zealand
- Pediatric Endocrinology, Health New Zealand (NZ)-Southern, Dunedin, New Zealand
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21
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Ng SM. NICE and NHS England leads the way to improve diabetes care with access to continuous glucose monitoring for people with type 1 diabetes. BMC Med 2023; 21:295. [PMID: 37553627 PMCID: PMC10408125 DOI: 10.1186/s12916-023-03014-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 07/28/2023] [Indexed: 08/10/2023] Open
Affiliation(s)
- Sze May Ng
- Paediatric Department, Mersey and West Lancashire Teaching Hospitals NHS Trust, Ormskirk, L39 2AZ, UK.
- Department of Women's and Children's Health, University of Liverpool, Liverpool, UK.
- Faculty of Health, Social Care & Medicine, Edge Hill University, Ormskirk, UK.
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Griffin TP, Gallen G, Hartnell S, Crabtree T, Holloway M, Gibb FW, Lumb A, Wilmot EG, Choudhary P, Hussain S. UK's Association of British Clinical Diabetologist's Diabetes Technology Network (ABCD-DTN): Best practice guide for hybrid closed-loop therapy. Diabet Med 2023; 40:e15078. [PMID: 36932929 DOI: 10.1111/dme.15078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/27/2023] [Accepted: 02/28/2023] [Indexed: 03/19/2023]
Abstract
This best practice guide is written with the aim of providing an overview of current hybrid closed-loop (HCL) systems in use within the United Kingdom's (UK) National Health Service (NHS) and to provide education and advice for their management on both an individual and clinical service level. The environment of diabetes technology, and particularly HCL systems, is rapidly evolving. The past decade has seen unprecedented advances in the development of HCL systems. These systems improve glycaemic outcomes and reduce the burden of treatment for people with type 1 diabetes (pwT1D). It is anticipated that access to these systems will increase in England as a result of updates in National Institute of Health and Care Excellence (NICE) guidance providing broader support for the use of real-time continuous glucose monitoring (CGM) for pwT1D. NICE is currently undertaking multiple-technology appraisal into HCL systems. Based on experience from centres involved in supporting advanced technologies as well as from the recent NHS England HCL pilot, this guide is intended to provide healthcare professionals with UK expert consensus on the best practice for initiation, optimisation and ongoing management of HCL therapy.
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Affiliation(s)
- Tomás P Griffin
- Leicester Diabetes Centre, University Hospitals of Leicester, Leicester, UK
- Diabetes Research Centre, College of Health Sciences, University of Leicester, Leicester, UK
- School of Medicine, University of Limerick, Limerick, Ireland
- Centre for Diabetes and Endocrinology, University Hospital Limerick, Limerick, Ireland
| | - Geraldine Gallen
- Department of Diabetes, School of Cardiovascular, Metabolic Medicine and Sciences, King's College London, London, UK
| | - Sara Hartnell
- Department of Diabetes and Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Thomas Crabtree
- University Hospitals of Derby and Burton NHS Foundation Trust, Derby, UK
- Translational Medical Sciences, University of Nottingham, Nottingham, UK
| | | | - Fraser W Gibb
- Edinburgh Centre for Endocrinology & Diabetes, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - Alistair Lumb
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford, UK
| | - Emma G Wilmot
- University Hospitals of Derby and Burton NHS Foundation Trust, Derby, UK
- Translational Medical Sciences, University of Nottingham, Nottingham, UK
| | - Pratik Choudhary
- Leicester Diabetes Centre, University Hospitals of Leicester, Leicester, UK
- Diabetes Research Centre, College of Health Sciences, University of Leicester, Leicester, UK
| | - Sufyan Hussain
- Department of Diabetes, School of Cardiovascular, Metabolic Medicine and Sciences, King's College London, London, UK
- Department of Diabetes and Endocrinology, Guy's & St Thomas' NHS Foundation Trust, London, UK
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Benhalima K, Beunen K, Siegelaar SE, Painter R, Murphy HR, Feig DS, Donovan LE, Polsky S, Buschur E, Levy CJ, Kudva YC, Battelino T, Ringholm L, Mathiesen ER, Mathieu C. Management of type 1 diabetes in pregnancy: update on lifestyle, pharmacological treatment, and novel technologies for achieving glycaemic targets. Lancet Diabetes Endocrinol 2023; 11:490-508. [PMID: 37290466 DOI: 10.1016/s2213-8587(23)00116-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 04/04/2023] [Accepted: 04/06/2023] [Indexed: 06/10/2023]
Abstract
Glucose concentrations within target, appropriate gestational weight gain, adequate lifestyle, and, if necessary, antihypertensive treatment and low-dose aspirin reduces the risk of pre-eclampsia, preterm delivery, and other adverse pregnancy and neonatal outcomes in pregnancies complicated by type 1 diabetes. Despite the increasing use of diabetes technology (ie, continuous glucose monitoring and insulin pumps), the target of more than 70% time in range in pregnancy (TIRp 3·5-7·8 mmol/L) is often reached only in the final weeks of pregnancy, which is too late for beneficial effects on pregnancy outcomes. Hybrid closed-loop (HCL) insulin delivery systems are emerging as promising treatment options in pregnancy. In this Review, we discuss the latest evidence on pre-pregnancy care, management of diabetes-related complications, lifestyle recommendations, gestational weight gain, antihypertensive treatment, aspirin prophylaxis, and the use of novel technologies for achieving and maintaining glycaemic targets during pregnancy in women with type 1 diabetes. In addition, the importance of effective clinical and psychosocial support for pregnant women with type 1 diabetes is also highlighted. We also discuss the contemporary studies examining HCL systems in type 1 diabetes during pregnancies.
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Affiliation(s)
- Katrien Benhalima
- Endocrinology, University Hospital Gasthuisberg, Katholieke Universiteit Leuven, Leuven, Belgium.
| | - Kaat Beunen
- Endocrinology, University Hospital Gasthuisberg, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Sarah E Siegelaar
- Department of Endocrinology and Metabolism, Amsterdam UMC, University of Amsterdam, Amsterdam, Netherlands; Amsterdam Gastroenterology Endocrinology and Metabolism, Amsterdam, Netherlands
| | - Rebecca Painter
- Department of Gynaecology and Obstetrics, Amsterdam UMC, Vrije Universiteit, Netherlands; Amsterdam Reproduction and Development, Amsterdam, Netherlands
| | - Helen R Murphy
- Diabetes and Antenatal Care, University of East Anglia, Norwich, UK
| | - Denice S Feig
- Department of Medicine, Obstetrics, and Gynecology and Department of Health Policy, Management, and Evaluation, University of Toronto, Diabetes and Endocrinology in Pregnancy Program, Mt Sinai Hospital, Toronto, ON, Canada
| | - Lois E Donovan
- Division of Endocrinology and Metabolism, Department of Medicine, and Department of Obstetrics and Gynaecology, Cumming School Medicine, University of Calgary, Calgary, AB, Canada
| | - Sarit Polsky
- Medicine and Pediatrics, Barbara Davis Center for Diabetes, Adult Clinic, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Elizabeth Buschur
- Internal Medicine, Endocrinology, Diabetes, and Metabolism, The Ohio State University, Wexner Medical Center, Columbus, OH, USA
| | - Carol J Levy
- Department of Medicine, Endocrinology and Obstetrics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Yogish C Kudva
- Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
| | - Tadej Battelino
- Department of Endocrinology, Diabetes and Metabolism, University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia; Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Lene Ringholm
- Center for Pregnant Women with Diabetes, Rigshospitalet, Copenhagen, Denmark
| | | | - Chantal Mathieu
- Endocrinology, University Hospital Gasthuisberg, Katholieke Universiteit Leuven, Leuven, Belgium
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Nwokolo M, Hovorka R. The Artificial Pancreas and Type 1 Diabetes. J Clin Endocrinol Metab 2023; 108:1614-1623. [PMID: 36734145 PMCID: PMC10271231 DOI: 10.1210/clinem/dgad068] [Citation(s) in RCA: 4] [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] [Received: 09/15/2022] [Revised: 01/23/2023] [Accepted: 02/01/2023] [Indexed: 02/04/2023]
Abstract
Diabetes technologies represent a paradigm shift in type 1 diabetes care. Continuous subcutaneous insulin infusion (CSII) pumps and continuous glucose monitors (CGM) improve glycated hemoglobin (HbA1c) levels, enhance time in optimal glycemic range, limit severe hypoglycemia, and reduce diabetes distress. The artificial pancreas or closed-loop system connects these devices via a control algorithm programmed to maintain target glucose, partially relieving the person living with diabetes of this constant responsibility. Automating insulin delivery reduces the input required from those wearing the device, leading to better physiological and psychosocial outcomes. Hybrid closed-loop therapy systems, requiring user-initiated prandial insulin doses, are the most advanced closed-loop systems commercially available. Fully closed-loop systems, requiring no user-initiated insulin boluses, and dual hormone systems have been shown to be safe and efficacious in the research setting. Clinical adoption of closed-loop therapy remains in early stages despite recent technological advances. People living with diabetes, health care professionals, and regulatory agencies continue to navigate the complex path to equitable access. We review the available devices, evidence, clinical implications, and barriers regarding these innovatory technologies.
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Affiliation(s)
- Munachiso Nwokolo
- Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
| | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, Box 289, Addenbrooke's Hospital, Cambridge CB2 0QQ, UK
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25
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Emerson H, Guy M, McConville R. Offline reinforcement learning for safer blood glucose control in people with type 1 diabetes. J Biomed Inform 2023; 142:104376. [PMID: 37149275 DOI: 10.1016/j.jbi.2023.104376] [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: 12/19/2022] [Revised: 03/23/2023] [Accepted: 04/28/2023] [Indexed: 05/08/2023]
Abstract
The widespread adoption of effective hybrid closed loop systems would represent an important milestone of care for people living with type 1 diabetes (T1D). These devices typically utilise simple control algorithms to select the optimal insulin dose for maintaining blood glucose levels within a healthy range. Online reinforcement learning (RL) has been utilised as a method for further enhancing glucose control in these devices. Previous approaches have been shown to reduce patient risk and improve time spent in the target range when compared to classical control algorithms, but are prone to instability in the learning process, often resulting in the selection of unsafe actions. This work presents an evaluation of offline RL for developing effective dosing policies without the need for potentially dangerous patient interaction during training. This paper examines the utility of BCQ, CQL and TD3-BC in managing the blood glucose of the 30 virtual patients available within the FDA-approved UVA/Padova glucose dynamics simulator. When trained on less than a tenth of the total training samples required by online RL to achieve stable performance, this work shows that offline RL can significantly increase time in the healthy blood glucose range from 61.6±0.3% to 65.3±0.5% when compared to the strongest state-of-art baseline (p<0.001). This is achieved without any associated increase in low blood glucose events. Offline RL is also shown to be able to correct for common and challenging control scenarios such as incorrect bolus dosing, irregular meal timings and compression errors. The code for this work is available at: https://github.com/hemerson1/offline-glucose.
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Affiliation(s)
- Harry Emerson
- University of Bristol, 1 Cathedral Square, Bristol, BS1 5TS, United Kingdom.
| | - Matthew Guy
- University Hospital Southampton, Tremona Road, Southampton, SO16 6YD, Hampshire, United Kingdom.
| | - Ryan McConville
- University of Bristol, 1 Cathedral Square, Bristol, BS1 5TS, United Kingdom.
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Chmayssem A, Nadolska M, Tubbs E, Sadowska K, Vadgma P, Shitanda I, Tsujimura S, Lattach Y, Peacock M, Tingry S, Marinesco S, Mailley P, Lablanche S, Benhamou PY, Zebda A. Insight into continuous glucose monitoring: from medical basics to commercialized devices. Mikrochim Acta 2023; 190:177. [PMID: 37022500 DOI: 10.1007/s00604-023-05743-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 03/08/2023] [Indexed: 04/07/2023]
Abstract
According to the latest statistics, more than 537 million people around the world struggle with diabetes and its adverse consequences. As well as acute risks of hypo- or hyper- glycemia, long-term vascular complications may occur, including coronary heart disease or stroke, as well as diabetic nephropathy leading to end-stage disease, neuropathy or retinopathy. Therefore, there is an urgent need to improve diabetes management to reduce the risk of complications but also to improve patient's quality life. The impact of continuous glucose monitoring (CGM) is well recognized, in this regard. The current review aims at introducing the basic principles of glucose sensing, including electrochemical and optical detection, summarizing CGM technology, its requirements, advantages, and disadvantages. The role of CGM systems in the clinical diagnostics/personal testing, difficulties in their utilization, and recommendations are also discussed. In the end, challenges and prospects in future CGM systems are discussed and non-invasive, wearable glucose biosensors are introduced. Though the scope of this review is CGMs and provides information about medical issues and analytical principles, consideration of broader use will be critical in future if the right systems are to be selected for effective diabetes management.
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Affiliation(s)
- Ayman Chmayssem
- UMR 5525, Univ. Grenoble Alpes, CNRS, Grenoble INP, INSERM, TIMC, VetAgro Sup, 38000, Grenoble, France
| | - Małgorzata Nadolska
- Institute of Nanotechnology and Materials Engineering, Faculty of Applied Physics and Mathematics, Gdansk University of Technology, 80-233, Gdansk, Poland
| | - Emily Tubbs
- Univ. Grenoble Alpes, CEA, INSERM, IRIG, 38000, Grenoble, Biomics, France
- Univ. Grenoble Alpes, LBFA and BEeSy, INSERM, U1055, F-38000, Grenoble, France
| | - Kamila Sadowska
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4, 02-109, Warsaw, Poland
| | - Pankaj Vadgma
- School of Engineering and Materials Science, Queen Mary University of London, Mile End, London, E1 4NS, UK
| | - Isao Shitanda
- Department of Pure and Applied Chemistry, Faculty of Science and Technology, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba, 278-8510, Japan
- Research Institute for Science and Technology, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba, 278-8510, Japan
| | - Seiya Tsujimura
- Japanese-French lAaboratory for Semiconductor physics and Technology (J-F AST)-CNRS-Université Grenoble Alpes-Grenoble, INP-University of Tsukuba, 1-1-1 Tennodai, Tsukuba, 305-8573, Japan
- Division of Material Science, Faculty of Pure and Applied Science, University of Tsukuba, 1-1-1, Tennodai, Ibaraki, Tsukuba, 305-5358, Japan
| | | | - Martin Peacock
- Zimmer and Peacock, Nedre Vei 8, Bldg 24, 3187, Horten, Norway
| | - Sophie Tingry
- Institut Européen Des Membranes, UMR 5635, IEM, Université Montpellier, ENSCM, CNRS, Montpellier, France
| | - Stéphane Marinesco
- Plate-Forme Technologique BELIV, Lyon Neuroscience Research Center, UMR5292, Inserm U1028, CNRS, Univ. Claude-Bernard-Lyon I, 69675, Lyon 08, France
| | - Pascal Mailley
- Univ. Grenoble Alpes, CEA, LETI, 38000, Grenoble, DTBS, France
| | - Sandrine Lablanche
- Univ. Grenoble Alpes, LBFA and BEeSy, INSERM, U1055, F-38000, Grenoble, France
- Department of Endocrinology, Grenoble University Hospital, Univ. Grenoble Alpes, Pôle DigiDune, Grenoble, France
| | - Pierre Yves Benhamou
- Department of Endocrinology, Grenoble University Hospital, Univ. Grenoble Alpes, Pôle DigiDune, Grenoble, France
| | - Abdelkader Zebda
- UMR 5525, Univ. Grenoble Alpes, CNRS, Grenoble INP, INSERM, TIMC, VetAgro Sup, 38000, Grenoble, France.
- Japanese-French lAaboratory for Semiconductor physics and Technology (J-F AST)-CNRS-Université Grenoble Alpes-Grenoble, INP-University of Tsukuba, 1-1-1 Tennodai, Tsukuba, 305-8573, Japan.
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Gómez AM, Henao D, Parra D, Kerguelen A, Jaramillo P, Gómez Y, Muñoz OM, Rondón M. Early and sustained increase in time in range 1 year after initiation of hybrid close loop therapy via telemedicine in type 1 diabetes patients. Acta Diabetol 2023; 60:943-949. [PMID: 37010594 PMCID: PMC10068726 DOI: 10.1007/s00592-023-02051-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 02/07/2023] [Indexed: 04/04/2023]
Abstract
BACKGROUND AND AIMS Evidence supports the efficacy and safety of the Hybrid Close loop (HCL) system in patients with type 1 diabetes (T1D). However, limited data are available on the long-term outcomes of patients on HCL with telemedicine follow-up. METHODS A prospective observational cohort study including T1D patients, who were upgrading to HCL system. Virtual training and follow-up were done through telemedicine. CGM data were analyzed to compare the baseline time in range (TIR), time below range (TBR), glycemic variability and auto mode (AM), with measurements performed at 3, 6 and 12 months. RESULTS 134 patients were included with baseline A1c 7.6% ± 1.1. 40.5% had a severe hypoglycemia event in the last year. Baseline TIR, measured two weeks after starting AM was 78.6 ± 9.94%. No changes were evident at three (Mean difference - 0.15;CI-2.47,2.17;p = 0.96), six (MD-1.09;CI-3.42,1.24;p = 0.12) and 12 months (MD-1.30;CI-3.64,1.04;p = 0.08). No significant changes were found in TBR or glycemic variability throughout the follow-up. Use of AM was 85.6 ± 17.5% and percentage of use of sensor was 88.75 ± 9.5% at 12 months. No severe hypoglycemic (SH) events were reported. CONCLUSIONS HCL systems allow to improve TIR, TBR and glycemic variability safely, early and sustained up to 1 year of follow-up in patients with T1D and high risk of hypoglycemia followed through telemedicine.
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Affiliation(s)
- Ana M. Gómez
- Hospital Universitario San Ignacio, Pontificia Universidad Javeriana, Carrera 7 No. 40-62, Bogotá, Colombia
- Hospital Universitario San Ignacio, Endocrinology Unit, Bogotá, Colombia
| | - Diana Henao
- Hospital Universitario San Ignacio, Pontificia Universidad Javeriana, Carrera 7 No. 40-62, Bogotá, Colombia
- Hospital Universitario San Ignacio, Endocrinology Unit, Bogotá, Colombia
| | - Darío Parra
- Hospital Universitario San Ignacio, Pontificia Universidad Javeriana, Carrera 7 No. 40-62, Bogotá, Colombia
- Hospital Universitario San Ignacio, Endocrinology Unit, Bogotá, Colombia
| | - Alfonso Kerguelen
- Hospital Universitario San Ignacio, Pontificia Universidad Javeriana, Carrera 7 No. 40-62, Bogotá, Colombia
- Hospital Universitario San Ignacio, Endocrinology Unit, Bogotá, Colombia
| | - Pablo Jaramillo
- Hospital Universitario San Ignacio, Pontificia Universidad Javeriana, Carrera 7 No. 40-62, Bogotá, Colombia
- Hospital Universitario San Ignacio, Endocrinology Unit, Bogotá, Colombia
| | - Yaline Gómez
- Hospital Universitario San Ignacio, Pontificia Universidad Javeriana, Carrera 7 No. 40-62, Bogotá, Colombia
- Hospital Universitario San Ignacio, Endocrinology Unit, Bogotá, Colombia
| | - Oscar Mauricio Muñoz
- Hospital Universitario San Ignacio, Pontificia Universidad Javeriana, Carrera 7 No. 40-62, Bogotá, Colombia
- Department of Internal Medicine, Hospital Universitario San Ignacio, Bogotá, Colombia
| | - Martin Rondón
- Department of Clinical Epidemiology and Biostatistics, Pontificia Universidad Javeriana, Bogotá, Colombia
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Chico A, Navas de Solís S, Lainez M, Rius F, Cuesta M. Efficacy, Safety, and Satisfaction with the Accu-Chek Insight with Diabeloop Closed-Loop System in Subjects with Type 1 Diabetes: A Multicenter Real-World Study. Diabetes Technol Ther 2023; 25:242-249. [PMID: 36724301 DOI: 10.1089/dia.2022.0449] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Aim: To evaluate the efficacy, safety and satisfaction of the closed-loop system Accu-Chek® Insight with Diabeloop™ (DBLG1™) in adults with type 1 diabetes (T1D) in real-world conditions. Methods: Patients with T1D using DBLG1 for at least 3 months were included. Glucometric parameters were analyzed at baseline, 1, 2, and 3 months after starting DBLG1. HbA1c was measured before and at 3 months. Technical issues and acute complications were recorded and patients completed a satisfaction questionnaire. Results: Sixty-two patients were included (43 women; age 44.2 ± 11 years; diabetes duration 24.6 ± 12 years; 40 used flash and 22 continuous glucose monitoring (CGM); 45 were on insulin pump and 17 on multiple daily injections). A significant improvement was observed in the CGM-derived glucose metrics early in the first month: Time in range (%TIR) 70-180 mg/dL (54.86 ± 17 vs. 72.23 ± 10.11); time above range level 1 (%TAR1) 180-250 mg/dL (26.26 ± 13.3 vs. 19.48 ± 6.78), time above range level 2 (%TAR2) > 250 mg/dL (12.02 ± 13.09 vs. 6.14 ± 5.23), time below range level 1 (%TBR 1) 54-70 mg/dL (5.73 ± 11.5 vs. 1.67 ± 1.3), time below range level 2 (%TBR2) < 54 mg/dL (1.18 ± 1.97 vs.0.44 ± 0.49), %CV (38.66 ± 7.53 vs. 29.63 ± 3.74), median glucose (168.57 ± 36 mg/dL vs. 154.63 ± 17.55 mg/dL), and %GMI (7.37 ± 0.91 vs. 7.02 ± 0.42). Also, HbA1c decreased significantly (7.45% ± 1.05% vs. 6.95% ± 0.7%). No acute complications or serious adverse events occurred. Similar improvement was observed regardless of prior therapy or the glucose monitoring system used. Three patients discontinued DBLG1 and 21 experienced technical issues. Overall, patient satisfaction was high. Adjustments of the settings were modified in general in the direction of greater aggressiveness. Conclusions: A significant improvement in glycemic control without serious adverse events and a high degree of patient satisfaction were observed in this first real-world study evaluating the closed-loop system, Accu-Chek Insight with Diabeloop.
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Affiliation(s)
- Ana Chico
- Department of Endocrinology and Nutrition, Hospital Santa Creu i Sant Pau, Barcelona, Spain
- CIBER-BBN, Instituto de Salud Carlos III, Madrid, Spain
- Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Sol Navas de Solís
- Department of Endocrinology and Nutrition, Hospital Universitario y Politécnico La Fe, Unidad Mixta de Investigación Endocrinología, Nutrición y Dietoterapia, Instituto de Investigación Sanitaria La Fe, Valencia, Spain
| | - María Lainez
- Departament of Endocrinology and Nutrition, Hospital Universitario Juan Ramón Jiménez, Huelva, Spain
| | - Ferran Rius
- Department of Endocrinology and Nutrition, Hospital Universitario Arnau de Vilanova, Lleida, Spain
| | - Martín Cuesta
- Department of Endocrinology and Nutrition, Hospital Clinico Universitario San Carlos, Madrid, Spain
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Closed-loop insulin delivery in pregnant women with type 1 diabetes (CRISTAL): a multicentre randomized controlled trial - study protocol. BMC Pregnancy Childbirth 2023; 23:180. [PMID: 36927458 PMCID: PMC10018977 DOI: 10.1186/s12884-023-05481-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 03/01/2023] [Indexed: 03/18/2023] Open
Abstract
BACKGROUND Despite increasing use of continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII, insulin pumps) in type 1 diabetes (T1D) in pregnancy, achieving recommended pregnancy glycaemic targets (3.5-7.8 mmol/L or 63-140 mg/dL) remains challenging. Consequently, the risk of adverse pregnancy outcomes remains high. Outside pregnancy, hybrid closed-loop (HCL) insulin delivery systems have led to a paradigm shift in the management of T1D, with 12% higher time in glucose target range (TIR) compared to conventional CSII. However, most commercially available HCL systems are currently not approved for use in pregnancy. This study aims to evaluate the efficacy, safety and cost-effectiveness of the MiniMed™ 780G HCL system (Medtronic) in T1D in pregnancy. METHODS In this international, open-label, randomized controlled trial (RCT), we will compare the MiniMed™ 780G HCL system to standard of care (SoC) in T1D in pregnancy. Women aged 18-45 years with T1D diagnosis of at least one year, HbA1c ≤ 86 mmol/mol (≤ 10%), and confirmed singleton pregnancy up to 11 weeks 6 days will be eligible. After providing written informed consent, all participants will wear a similar CGM system (Guardian™ 3 or Guardian™ 4 CGM) during a 10-day run-in phase. After the run-in phase, participants will be randomised 1:1 to 780G HCL (intervention) or SoC [control, continuation of current T1D treatment with multiple daily injections (MDI) or CSII and any type of CGM] stratified according to centre, baseline HbA1c (< 53 vs. ≥ 53 mmol/mol or < 7 vs. ≥ 7%), and method of insulin delivery (MDI or CSII). The primary outcome will be the time spent within the pregnancy glucose target range, as measured by the CGM at four time points in pregnancy: 14-17, 20-23, 26-29, and 33-36 weeks. Prespecified secondary outcomes will be overnight TIR, time below range (TBR: <3.5 mmol/L or < 63 mg/dL), and overnight TBR. Other outcomes will be exploratory. The planned sample size is 92 participants. The study will end after postpartum discharge from hospital. Analyses will be performed according to intention-to-treat as well as per protocol. DISCUSSION This large RCT will evaluate a widely used commercially available HCL system in T1D in pregnancy. Recruitment began in January 2021 and was completed in October 2022. Study completion is expected in May 2023. TRIAL REGISTRATION ClinicalTrials.gov: NCT04520971. Registration date: August 20, 2020. https://clinicaltrials.gov/ct2/show/NCT04520971.
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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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Steenkamp DW, Piarulli A, Middelbeek RJW, Wolpert HA. Severe hypoglycaemia while using a hybrid closed-loop insulin pump system: A reminder of the continued importance of patient education for pre-emptive hypoglycaemia mitigation. Diabet Med 2023; 40:e14975. [PMID: 36251520 DOI: 10.1111/dme.14975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 09/27/2022] [Accepted: 10/13/2022] [Indexed: 11/30/2022]
Affiliation(s)
- Devin W Steenkamp
- Section of Endocrinology, Diabetes and Nutrition, Boston University School of Medicine/Boston Medical Center, Boston, Massachusetts, USA
| | - Amanda Piarulli
- Section of Endocrinology, Diabetes and Nutrition, Boston University School of Medicine/Boston Medical Center, Boston, Massachusetts, USA
| | - Roeland J W Middelbeek
- Joslin Diabetes Center and Division of Endocrinology, Diabetes and Metabolism, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Howard A Wolpert
- Section of Endocrinology, Diabetes and Nutrition, Boston University School of Medicine/Boston Medical Center, Boston, Massachusetts, USA
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32
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Dover AR, Ritchie SA, Wright RJ, McMurray EM, Strachan MWJ, Stimson RH, Forbes S, Gibb FW. Interest in hybrid closed loop is high across the socioeconomic spectrum despite current inequalities in provision in a large UK diabetes centre. Diabet Med 2023; 40:e15058. [PMID: 36723227 DOI: 10.1111/dme.15058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 01/24/2023] [Accepted: 01/27/2023] [Indexed: 02/02/2023]
Affiliation(s)
- Anna R Dover
- Edinburgh Centre for Endocrinology & Diabetes, NHS Lothian, Edinburgh, UK
| | - Stuart A Ritchie
- Edinburgh Centre for Endocrinology & Diabetes, NHS Lothian, Edinburgh, UK
| | - Rohana J Wright
- Edinburgh Centre for Endocrinology & Diabetes, NHS Lothian, Edinburgh, UK
| | - Emily M McMurray
- Edinburgh Centre for Endocrinology & Diabetes, NHS Lothian, Edinburgh, UK
| | - Mark W J Strachan
- Edinburgh Centre for Endocrinology & Diabetes, NHS Lothian, Edinburgh, UK
| | - Roland H Stimson
- Edinburgh Centre for Endocrinology & Diabetes, NHS Lothian, Edinburgh, UK
| | - Shareen Forbes
- Edinburgh Centre for Endocrinology & Diabetes, NHS Lothian, Edinburgh, UK
| | - Fraser W Gibb
- Edinburgh Centre for Endocrinology & Diabetes, NHS Lothian, Edinburgh, UK
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Ng SM, Wright NP, Yardley D, Campbell F, Randell T, Trevelyan N, Ghatak A, Hindmarsh PC. Real world use of hybrid-closed loop in children and young people with type 1 diabetes mellitus-a National Health Service pilot initiative in England. Diabet Med 2023; 40:e15015. [PMID: 36424877 DOI: 10.1111/dme.15015] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 11/23/2022] [Indexed: 11/26/2022]
Abstract
AIMS Hybrid closed-loop (HCL) systems are characterised by integrating continuous glucose monitoring (CGM) with insulin pumps that automate insulin delivery via specific algorithms and user-initiated insulin delivery. The aim of the study was to evaluate effectiveness of HCLs on HbA1c, time-in-range (TIR), hypoglycaemia frequency and quality of life measures in children and young people (CYP) with T1D, and their carers. METHODS Patients were recruited prospectively into the National Health Service (NHS) England real-world HCL observational study from the 1st of August 2021 to the 10th of December 2022 from eight paediatric diabetes centres in England. RESULTS There were 251 CYP (147 males, 58%) with T1DM recruited with a mean age at recruitment of 12.3 (SD 3.5) (range 2-19) years. Eighty nine per cent of the CYP were of white ethnicity, 3% Asian, 4% black and 3% mixed ethnicity, and 1% were recorded as others. The HCL systems used in the study were: (1) Tandem Control-IQ AP system, which uses the Tandem t:slim X2 insulin pump (Tandem Diabetes Care, San Diego, CA) with the Dexcom G6® CGM (Dexcom, San Diego, CA) sensor; (2) Medtronic MiniMed™ 780G (Medtronic, Northridge, CA) and (3) CamAPS FX (CamDiab, Cambridge, UK.) All systems were fully funded by the national health service. CONCLUSIONS The results of the NHS England Closed Loop Study in Children and Young People showed improvements in glycaemic control, TIR, frequency of hypoglycaemia, hypoglycaemia fear and quality of sleep for children and young people when using HCL for 6 months. Hypoglycaemia fear and quality of sleep were also improved for their parents and carers at 6 months.
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Affiliation(s)
- Sze May Ng
- Department of Women's and Children's Health, University of Liverpool, Liverpool, UK
- Paediatric Department, Southport and Ormskirk NHS Trust, Ormskirk, UK
| | | | - Diana Yardley
- Children's Diabetes Team, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Fiona Campbell
- Children's Diabetes Centre, Leeds Children's Hospital, Leeds, UK
| | - Tabitha Randell
- Department of Paediatric Endocrinology, Nottingham Children's Hospital, Nottingham, UK
| | | | | | - Peter C Hindmarsh
- Children and Young People's Diabetes Service, University College London Hospitals NHS Foundation Trust, London, UK
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Daly AB, Boughton CK, Nwokolo M, Hartnell S, Wilinska ME, Cezar A, Evans ML, Hovorka R. Fully automated closed-loop insulin delivery in adults with type 2 diabetes: an open-label, single-center, randomized crossover trial. Nat Med 2023; 29:203-208. [PMID: 36631592 PMCID: PMC9873557 DOI: 10.1038/s41591-022-02144-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 11/23/2022] [Indexed: 01/13/2023]
Abstract
In adults with type 2 diabetes, the benefits of fully closed-loop insulin delivery, which does not require meal bolusing, are unclear. In an open-label, single-center, randomized crossover study, 26 adults with type 2 diabetes (7 women and 19 men; (mean ± s.d.) age, 59 ± 11 years; baseline glycated hemoglobin (HbA1c), 75 ± 15 mmol mol-1 (9.0% ± 1.4%)) underwent two 8-week periods to compare the CamAPS HX fully closed-loop app with standard insulin therapy and a masked glucose sensor (control) in random order, with a 2-week to 4-week washout between periods. The primary endpoint was proportion of time in target glucose range (3.9-10.0 mmol l-1). Analysis was by intention to treat. Thirty participants were recruited between 16 December 2020 and 24 November 2021, of whom 28 were randomized to two groups (14 to closed-loop therapy first and 14 to control therapy first). Proportion of time in target glucose range (mean ± s.d.) was 66.3% ± 14.9% with closed-loop therapy versus 32.3% ± 24.7% with control therapy (mean difference, 35.3 percentage points; 95% confidence interval (CI), 28.0-42.6 percentage points; P < 0.001). Time > 10.0 mmol l-1 was 33.2% ± 14.8% with closed-loop therapy versus 67.0% ± 25.2% with control therapy (mean difference, -35.2 percentage points; 95% CI, -42.8 to -27.5 percentage points; P < 0.001). Mean glucose was lower during the closed-loop therapy period than during the control therapy period (9.2 ± 1.2 mmol l-1 versus 12.6 ± 3.0 mmol l-1, respectively; mean difference, -3.6 mmol l-1; 95% CI, -4.6 to -2.5 mmol l-1; P < 0.001). HbA1c was lower following closed-loop therapy (57 ± 9 mmol mol-1 (7.3% ± 0.8%)) than following control therapy (72 ± 13 mmol mol-1 (8.7% ± 1.2%); mean difference, -15 mmol mol-1; 95% CI, -11 to -20 mmol l-1 (mean difference, -1.4%; 95% CI, -1.0 to -1.8%); P < 0.001). Time < 3.9 mmol l-1 was similar between treatments (a median of 0.44% (interquartile range, 0.19-0.81%) during the closed-loop therapy period versus a median of 0.08% (interquartile range, 0.00-1.05%) during the control therapy period; P = 0.43). No severe hypoglycemia events occurred in either period. One treatment-related serious adverse event occurred during the closed-loop therapy period. Fully closed-loop insulin delivery improved glucose control without increasing hypoglycemia compared with standard insulin therapy and may represent a safe and efficacious method to improve outcomes in adults with type 2 diabetes. This study is registered with ClinicalTrials.gov (NCT04701424).
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Affiliation(s)
- Aideen B. Daly
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Charlotte K. Boughton
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK ,grid.24029.3d0000 0004 0383 8386Cambridge University Hospitals NHS Foundation Trust, Wolfson Diabetes and Endocrine Clinic, Cambridge, UK
| | - Munachiso Nwokolo
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Sara Hartnell
- grid.24029.3d0000 0004 0383 8386Cambridge University Hospitals NHS Foundation Trust, Wolfson Diabetes and Endocrine Clinic, Cambridge, UK
| | - Malgorzata E. Wilinska
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Alina Cezar
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Mark L. Evans
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK ,grid.24029.3d0000 0004 0383 8386Cambridge University Hospitals NHS Foundation Trust, Wolfson Diabetes and Endocrine Clinic, Cambridge, UK
| | - Roman Hovorka
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
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Bassi M, Patti L, Silvestrini I, Strati MF, Ponzano M, Minuto N, Maggi D. One-year follow-up comparison of two hybrid closed-loop systems in Italian children and adults with type 1 diabetes. Front Endocrinol (Lausanne) 2023; 14:1099024. [PMID: 36777356 PMCID: PMC9909036 DOI: 10.3389/fendo.2023.1099024] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 01/16/2023] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND AND AIMS Tandem Control-IQ and MiniMed 780G are the main Advanced Hybrid Closed Loop (AHCL) systems currently available in pediatric and adult patients with Type 1 Diabetes (T1D). The aim of our study was to evaluate glycemic control after 1-year of follow-up extending our previous study of 1-month comparison between the two systems. METHODS We retrospectively compared clinical and continuous glucose monitoring (CGM) data from the patients included in the previous study which have completed 1-year observation period. The study population consisted of 74 patients, 42 Minimed 780G users and 32 Tandem Control-IQ users. Linear mixed models with random intercept were performed to study the variations over time and the interaction between time and system; Mann-Whitney or T-test were used to compare systems at 1-year. RESULTS Both systems have been shown to be effective in maintaining the glycemic improvement achieved one month after starting AHCL. Significant changes over time were observed for TIR, TAR, TAR>250mg/dl, average glucose levels and SD (p<0.001). At 1-year follow-up Minimed 780G obtained better improvement in TIR (p<0.001), TAR (p=0.002), TAR>250mg/dl (p=0.001), average glucose levels (p<0.001). The comparison of the glycemic parameters at 1-year showed a significant superiority of Minimed 780G in terms of TIR (71% vs 68%; p=0.001), TAR (p=0.001), TAR>250 (p=0.009), average glucose levels(p=0.001) and SD (p=0.031). CONCLUSIONS The use of AHCL systems led to a significant improvement of glycemic control at 1-month, which is maintained at 1-year follow-up. MiniMed is more effective than Tandem in reaching the International recommended glycemic targets. Continuous training and education in the use of technology is essential to get the best out of the most advanced technological tools.
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Affiliation(s)
- Marta Bassi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
- Department of Pediatrics, IRCCS Istituto Giannina Gaslini, University of Genoa, Genoa, Italy
| | - Luca Patti
- Department of Internal Medicine and Medical Specialties (DiMI), University of Genoa, Genoa, Italy
| | - Irene Silvestrini
- Department of Internal Medicine and Medical Specialties (DiMI), University of Genoa, Genoa, Italy
| | - Marina Francesca Strati
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
- Department of Pediatrics, IRCCS Istituto Giannina Gaslini, University of Genoa, Genoa, Italy
| | - Marta Ponzano
- Department of Health Science (DiSSAL), University of Genoa, Genoa, Italy
| | - Nicola Minuto
- Department of Pediatrics, IRCCS Istituto Giannina Gaslini, University of Genoa, Genoa, Italy
- *Correspondence: Nicola Minuto,
| | - Davide Maggi
- Department of Internal Medicine and Medical Specialties (DiMI), University of Genoa, Genoa, Italy
- Diabetes Clinic, IRCCS Ospedale Policlinico San Martino Genoa, Genoa, Italy
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Hybrid Closed-Loop Insulin Pump Technology Can Be Safely Used in the Inpatient Setting. Endocr Pract 2023; 29:24-28. [PMID: 36400399 DOI: 10.1016/j.eprac.2022.11.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 11/09/2022] [Accepted: 11/10/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND Hybrid closed-loop (HCL) systems, also known as automated insulin delivery systems, are a rapidly growing technology in diabetes management. Because more patients are using these systems in the outpatient setting, it is important to also assess inpatient safety to determine whether HCL use can be continued when those patients become hospitalized. METHODS The records of patients using HCL technology on admission to our hospital between June 1, 2020, and June 30, 2021, were analyzed. RESULTS The final analysis included 71 patients divided into 3 categories based on their pump use as an inpatient: (1) HCL users; (2) manual pump users; and (3) pump removed. All cohorts were similar in age, sex, race, hemoglobin A1C at admission, and in Medicare Severity Diagnosis Related Group. Pairwise comparisons indicated that patient-stay mean glucose levels, frequency of patient-specific hyperglycemic measurements, and frequency of hypoglycemic events were similar between all groups. No adverse events, particularly occurrences of diabetic ketoacidosis, pump site complications or infection, or equipment malfunction, were reported. CONCLUSION This preliminary case series review indicates that continued use of HCL technology in the hospital is safe. Moreover, glycemic control in HCL users was comparable with that in those using insulin pump with manual settings and those converted to basal-bolus insulin therapy.
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Morrison AE, Senior PA, Bubela T, Farnsworth K, Witteman HO, Lam A. Do-It-Yourself and Commercial Automated Insulin Delivery Systems in Type 1 Diabetes: An Uncertain Area for Canadian Health-care Providers. Can J Diabetes 2022; 46:863-870. [PMID: 35945126 DOI: 10.1016/j.jcjd.2022.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 05/27/2022] [Accepted: 06/13/2022] [Indexed: 01/15/2023]
Abstract
In the past century, since the discovery of insulin, methods of insulin delivery and glucose monitoring have advanced technologically. In particular, the introduction of insulin pumps, providing continuous subcutaneous insulin infusion (CSII), and continuous glucose monitors (CGMs) have been revolutionary for people living with type 1 diabetes. In this review, we have focussed on automated insulin delivery (AID) systems and discuss the implications of both approved and off-label options for the user and health-care providers. By pairing insulin pumps with CGM, AID systems facilitate automated adjustment in insulin delivery based on CGM readings. A subset of these have been developed commercially and were granted regulatory approval. In contrast, unregulated do-it-yourself AID systems, designed and set up by people living with type 1 diabetes and their families, have advanced rapidly and are gaining popularity worldwide. These patient-driven technologies have demonstrated impressive user self-reported improvements in glycemic control and quality of life, but have not been evaluated in any formal randomized controlled trials or by regulators. This presents challenging uncertainty for health-care providers, in addition to ethical and legal implications in supporting people with diabetes who wish to use these technologies. The current knowledge, opinions and practices relating to the use of AID systems across Canada are unknown. Gathering this information will highlight current practice and areas of knowledge gaps and concern and will assist in focussed education. This understanding is crucial to ensure people with type 1 diabetes using these systems have access to optimal, consistent and safe patient-centred care.
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Affiliation(s)
- Amy E Morrison
- Division of Endocrinology and Metabolism, Department of Medicine, Walter C. MacKenzie Health Sciences Centre, University of Alberta, Edmonton, Alberta, Canada.
| | - Peter A Senior
- Division of Endocrinology and Metabolism, Department of Medicine, Walter C. MacKenzie Health Sciences Centre, University of Alberta, Edmonton, Alberta, Canada; Diabetes Action Canada, Toronto, Ontario, Canada
| | - Tania Bubela
- Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada
| | | | - Holly O Witteman
- Department of Family and Emergency Medicine and Office of Education and Professional Development, Université Laval, Québec City, Québec, Canada
| | - Anna Lam
- Division of Endocrinology and Metabolism, Department of Medicine, Walter C. MacKenzie Health Sciences Centre, University of Alberta, Edmonton, Alberta, Canada
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Stefanov BA, Fussenegger M. Biomarker-driven feedback control of synthetic biology systems for next-generation personalized medicine. Front Bioeng Biotechnol 2022; 10:986210. [PMID: 36225597 PMCID: PMC9548536 DOI: 10.3389/fbioe.2022.986210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 09/06/2022] [Indexed: 11/13/2022] Open
Abstract
Many current clinical therapies for chronic diseases involve administration of drugs using dosage and bioavailability parameters estimated for a generalized population. This standard approach carries the risk of under dosing, which may result in ineffective treatment, or overdosing, which may cause undesirable side effects. Consequently, maintaining a drug concentration in the therapeutic window often requires frequent monitoring, adversely affecting the patient’s quality of life. In contrast, endogenous biosystems have evolved finely tuned feedback control loops that govern the physiological functions of the body based on multiple input parameters. To provide personalized treatment for chronic diseases, therefore, we require synthetic systems that can similarly generate a calibrated therapeutic response. Such engineered autonomous closed-loop devices should incorporate a sensor that actively tracks and evaluates the disease severity based on one or more biomarkers, as well as components that utilize these molecular inputs to bio compute and deliver the appropriate level of therapeutic output. Here, we review recent advances in applications of the closed-loop design principle in biomedical implants for treating severe and chronic diseases, highlighting translational studies of cellular therapies. We describe the engineering principles and components of closed-loop therapeutic devices, and discuss their potential to become a key pillar of personalized medicine.
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Affiliation(s)
| | - Martin Fussenegger
- ETH Zürich, Department of Biosystems Science and Engineering, Basel, Switzerland
- Faculty of Life Science, University of Basel, Basel, Switzerland
- *Correspondence: Martin Fussenegger,
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Jones J, James S, Brown F, O'Neal D, I Ekinci E. Dead in bed - A systematic review of overnight deaths in type 1 diabetes. Diabetes Res Clin Pract 2022; 191:110042. [PMID: 36007797 DOI: 10.1016/j.diabres.2022.110042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 05/18/2022] [Accepted: 08/11/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Type 1 diabetes is a significant, life-long condition which affects many people worldwide. One of the most feared causes of type 1 diabetes mortality, overnight mortality, often caused by the dead in bed syndrome, is largely underreported. A systematic literature search was undertaken to understand the frequency, risk factors, causes and impact that diabetes-related technologies have on overnight mortality, in this population. METHODS MEDLINE (Ovid), Embase (Ovid) and Cochrane were searched to June 2021, using defined inclusion and exclusion criteria. Quality appraisal was undertaken. RESULTS Overall, 26 records met the inclusion criteria. Large-scale cohort studies examined data up to 2013, and there were no studies published after 2018. The proportion of deaths attributable to the dead in bed syndrome was between 2 and 5% of deaths in children, adolescents, and young adults, with a slight decrease in proportion of dead in bed syndrome since 1991. CONCLUSION Overnight mortality is occurring for people with type 1 diabetes, reported as recently as in 2018. Living alone, alcohol and illicit substances consistently appear as risk factors, and the impact of technology on overnight mortality is not fully understood, with more recent data, from larger cohort studies being required.
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Affiliation(s)
- Jessica Jones
- Department of Medicine, University of Melbourne, Grattan Street, Parkville, Victoria 3010, Australia; Department of Endocrinology, Austin Health, 145 Studley Road, Heidelberg, Victoria 3084, Australia; Australian Centre of Accelerating Diabetes Innovations (ACADI), University of Melbourne, Grattan Street, Parkville, Victoria 3010, Australia
| | - Steven James
- Department of Medicine, University of Melbourne, Grattan Street, Parkville, Victoria 3010, Australia; Australian Centre of Accelerating Diabetes Innovations (ACADI), University of Melbourne, Grattan Street, Parkville, Victoria 3010, Australia; School of Nursing, Midwifery and Paramedicine, University of the Sunshine Coast, 1 Moreton Parade, Petrie, Queensland 4502, Australia
| | - Fran Brown
- Melbourne Diabetes Education & Support, 76 Edwin St, Heidelberg Heights, Victoria 3081, Australia
| | - David O'Neal
- Department of Medicine, University of Melbourne, Grattan Street, Parkville, Victoria 3010, Australia; Australian Centre of Accelerating Diabetes Innovations (ACADI), University of Melbourne, Grattan Street, Parkville, Victoria 3010, Australia; Department of Endocrinology, St Vincent's Hospital, 41 Victoria Parade, Fitzroy, Victoria 3065, Australia
| | - Elif I Ekinci
- Department of Medicine, University of Melbourne, Grattan Street, Parkville, Victoria 3010, Australia; Department of Endocrinology, Austin Health, 145 Studley Road, Heidelberg, Victoria 3084, Australia; Australian Centre of Accelerating Diabetes Innovations (ACADI), University of Melbourne, Grattan Street, Parkville, Victoria 3010, Australia.
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Lewis DM, Hussain S. Practical Guidance on Open Source and Commercial Automated Insulin Delivery Systems: A Guide for Healthcare Professionals Supporting People with Insulin-Requiring Diabetes. Diabetes Ther 2022; 13:1683-1699. [PMID: 35913655 PMCID: PMC9399331 DOI: 10.1007/s13300-022-01299-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 07/08/2022] [Indexed: 01/15/2023] Open
Abstract
As increasing numbers of people with insulin-managed diabetes use automated insulin delivery (AID) systems or seek such technologies, healthcare providers are faced with a steep learning curve. Healthcare providers need to understand how to support these technologies to help inform shared decision making, discussing available options, implementing them in the clinical setting, and guiding users in special situations. At the same time, there is a growing diversity of commercial and open source automated insulin delivery systems that are evolving at a rapid pace. This practical guide seeks to provide a conversational framework for healthcare providers to first understand and then jointly assess AID system options with users and caregivers. Using this framework will help HCPs in learning how to evaluate potential new commercial or open source AID systems, while also providing a guide for conversations to help HCPs to assess the readiness and understanding of users for AID systems. The choice of an AID system is not as simple as whether the system is open source or commercially developed, and indeed there are multiple criteria to assess when choosing an AID system. Most importantly, the choices and preferences of the person living with diabetes should be at the center of any decision around the ideal automated insulin delivery system or any other diabetes technology. This framework highlights issues with AID use that may lead to burnout or perceived failures or may otherwise cause users to abandon the use of AID. It discusses the troubleshooting of basic AID system operation and discusses more advanced topics regarding how to maximize the time spent on AID systems, including how to optimize settings and behaviors for the best possible outcomes with AID technology for people with insulin-requiring diabetes. This practical approach article demonstrates how healthcare providers will benefit from assessing and better understanding all available AID system options to enable them to best support each individual.
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Affiliation(s)
| | - Sufyan Hussain
- Department of Diabetes and Endocrinology, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
- Department of Diabetes, King’s College London, London, UK
- Institute of Diabetes, Endocrinology and Obesity, King’s Health Partners, London, UK
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Morrison AE, Chong K, Senior PA, Lam A. A scoping review of Do-It-Yourself Automated Insulin Delivery system (DIY AID) use in people with type 1 diabetes. PLoS One 2022; 17:e0271096. [PMID: 35951597 PMCID: PMC9371307 DOI: 10.1371/journal.pone.0271096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 06/23/2022] [Indexed: 11/18/2022] Open
Abstract
Introduction User designed Automated Insulin Delivery systems (AID), termed Do-It-Yourself (DIY) AID include; AndroidAPS, OpenAPS and Loop. These unregulated systems provide challenges for healthcare providers worldwide, with potential legal and ethical barriers to supporting their use. We performed a scoping review of the currently available literature surrounding DIY AID systems, specifically to highlight the evidence available to facilitate healthcare providers to support persons with diabetes who may benefit from DIY AID. Methods Studies relating to DIY AID systems were searched in Embase, Medline, Web of Science, Scopus, Proquest and Cochrane library until 31st December 2021. Publications were screened through title and abstract to identify study type and AID system type described. A thematic synthesis methodology was used for analysis of studies of DIY AID use due to the heterogeneity in study designs (case reports, qualitative, cross-sectional and cohort studies), with similarity in outcome themes. Results Following implementation of the search strategy, 38 relevant full texts were identified; comprising 12 case reports, 9 qualitative studies and 17 cohort studies, and data was also available from 24 relevant conference abstracts. No randomized studies were identified. Common themes were identified in the outcomes across the studies; glycemic variability, safety, quality of life, healthcare provider attitudes and social media. Conclusion There is extensive real-world data, but a lack of randomized control trial evidence supporting DIY AID system use, due to the user-driven, unregulated nature of these systems. Healthcare providers report a lack of understanding surrounding, and confidence in supporting, DIY AID despite impressive observational and user self-reported improvements in glycemic variability, without any reported safety compromises.
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Affiliation(s)
- Amy E. Morrison
- Division of Endocrinology and Metabolism, Department of Medicine, University of Alberta, Edmonton, AB, Canada
- * E-mail:
| | - Kimberley Chong
- Division of Endocrinology and Metabolism, Department of Medicine, University of Alberta, Edmonton, AB, Canada
| | - Peter A. Senior
- Division of Endocrinology and Metabolism, Department of Medicine, University of Alberta, Edmonton, AB, Canada
- Alberta Diabetes Institute, University of Alberta, Edmonton, AB, Canada
| | - Anna Lam
- Division of Endocrinology and Metabolism, Department of Medicine, University of Alberta, Edmonton, AB, Canada
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Bartolome A, Prioleau T. A computational framework for discovering digital biomarkers of glycemic control. NPJ Digit Med 2022; 5:111. [PMID: 35941355 PMCID: PMC9360447 DOI: 10.1038/s41746-022-00656-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Accepted: 07/14/2022] [Indexed: 11/09/2022] Open
Abstract
Digital biomarkers can radically transform the standard of care for chronic conditions that are complex to manage. In this work, we propose a scalable computational framework for discovering digital biomarkers of glycemic control. As a feasibility study, we leveraged over 79,000 days of digital data to define objective features, model the impact of each feature, classify glycemic control, and identify the most impactful digital biomarkers. Our research shows that glycemic control varies by age group, and was worse in the youngest population of subjects between the ages of 2–14. In addition, digital biomarkers like prior-day time above range and prior-day time in range, as well as total daily bolus and total daily basal were most predictive of impending glycemic control. With a combination of the top-ranked digital biomarkers, we achieved an average F1 score of 82.4% and 89.7% for classifying next-day glycemic control across two unique datasets.
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Ng SM, Katkat N, Day H, Hubbard R, Quinn M, Finnigan L. Real-world prospective observational single-centre study: Hybrid closed loop improves HbA1c, time-in-range and quality of life for children, young people and their carers. Diabet Med 2022; 39:e14863. [PMID: 35488481 DOI: 10.1111/dme.14863] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 04/24/2022] [Accepted: 04/27/2022] [Indexed: 11/30/2022]
Abstract
Hybrid closed-loop (HCL) systems are characterised by integrating continuous glucose monitoring (CGM) with insulin pumps which automate insulin delivery via specific algorithms and user-initiated insulin delivery. The aim of the study was to evaluate the effectiveness of HCLs on Hba1c, time-in-range (TIR), time in hypoglycaemia, fear of hypoglycaemia, sleep and quality of life measure in children and young people (CYP) with T1D and their carers. Data on HbA1c, TIR and hypoglycaemia frequency were reviewed at baseline prior to starting HCL and 3 months after commencement. As part of clinical care, all patients and carers were provided with key education on the use of the HCL system by trained diabetes healthcare professionals. CYP aged 12 years and above independently completed the validated Hypoglycaemia Fear Survey (HFS). Parents of patients <12 were asked to complete a modified version of the HFS-Parent (HFS-P) survey. There were 39 CYP (22 men) with T1D included with a mean age of 11.8 ± 4.4 at commencement of HCL. Median duration of diabetes was 3.8 years (interquartile range 1.3-6.0). There were 55% of patients who were prepubertal at the time of HCL commencement. 91% were on the Control-IQ system and 9% on the CamAPS FX system. HCL use demonstrated significant improvements at 3 months in the following: HbA1c in mmol/mol (63.0 vs. 56.6, p = 0.03), TIR (50.5 vs. 67.0, p = 0.001) and time in hypoglycaemia (4.3% vs. 2.8%, p = 0.004). HFS scores showed improved behaviour (34.0 vs. 27.5.9, p = 0.02) and worry (40.2 vs. 31.6, p = 0.03), and HFS-P scores also showed improved behaviour (p < 0.001) and worry (p = 0.01). Our study shows that HCL at 3 months improves glucose control, diabetes management and quality of life measures such as fear and worry of hypoglycaemia for CYP and carers.
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Affiliation(s)
- Sze May Ng
- Department of Women's and Children's Health, University of Liverpool, Liverpool, UK
- Paediatric Department, Southport and Ormskirk NHS Trust, Ormskirk, UK
| | - Nancy Katkat
- Paediatric Department, Southport and Ormskirk NHS Trust, Ormskirk, UK
| | - Helen Day
- Paediatric Department, Southport and Ormskirk NHS Trust, Ormskirk, UK
| | - Rebecca Hubbard
- Paediatric Department, Southport and Ormskirk NHS Trust, Ormskirk, UK
| | - Michelle Quinn
- Paediatric Department, Southport and Ormskirk NHS Trust, Ormskirk, UK
| | - Lynne Finnigan
- Paediatric Department, Southport and Ormskirk NHS Trust, Ormskirk, UK
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Pintaudi B, Gironi I, Nicosia R, Meneghini E, Disoteo O, Mion E, Bertuzzi F. Minimed Medtronic 780G optimizes glucose control in patients with type 1 diabetes mellitus. Nutr Metab Cardiovasc Dis 2022; 32:1719-1724. [PMID: 35599092 DOI: 10.1016/j.numecd.2022.03.031] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 03/26/2022] [Accepted: 03/31/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND AND AIMS The new advanced hybrid closed loop insulin infusion systems have the potential to significantly improve glycaemic control. The aim of this study was to evaluate the effectiveness of the Minimed 780G system in 59 patients with type 1 diabetes. METHODS AND RESULTS Glucose control obtained by using the system in automatic mode at 1-2 months of activation, at 2-4 months, at 4-6 months, and beyond 6 month was compared with those obtained with the system in manual mode. A significant improvement in time-in-range and in time-above-range throughout the follow-up was observed, as well as a significant reduction in time-below-range (<54 mg/dl) after 6 months, a significant reduction of the glucose variability and of HbA1c. After switching the mode, all target percentages lied on the average within the recommended ranges by literature consensus and no severe hypoglycemia nor ketoacidosis episodes were recorded. CONCLUSION The Minimed 780G allowed a rapid and progressive improvement of the overall glucose control.
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Affiliation(s)
- Basilio Pintaudi
- SC Diabetologia, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Ilaria Gironi
- SC Diabetologia, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Riccardo Nicosia
- SC Diabetologia, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Elena Meneghini
- SC Diabetologia, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Olga Disoteo
- SC Diabetologia, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Elena Mion
- SC Diabetologia, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Federico Bertuzzi
- SC Diabetologia, ASST Grande Ospedale Metropolitano Niguarda, Milan, Italy.
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Hettiarachchi C, Malagutti N, Nolan C, Daskalaki E, Suominen H. A Reinforcement Learning Based System for Blood Glucose Control without Carbohydrate Estimation in Type 1 Diabetes: In Silico Validation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:950-956. [PMID: 36086458 DOI: 10.1109/embc48229.2022.9871054] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Type 1 Diabetes (T1D) is a chronic autoimmune disease, which requires the use of exogenous insulin for glucose regulation. In current hybrid closed-loop systems, meal entry is manual which adds cognitive burden to the persons living with T1D. In this study, we proposed a control system based on Proximal Policy Optimisation (PPO) that controls both basal and bolus insulin infusion and only requires meal announcement, thus eliminating the need for carbohydrate estimation. We evaluated the system on a challenging meal scenario, using an open-source simulator based on the UVA/Padova 2008 model and achieved a mean Time in Range value of 65% for the adult subject cohort, while maintaining a moderate hypoglycemic and hyperglycemic risk profile. The approach shows promise and welcomes further research towards the translation to a real-life artificial pancreas. Clinical relevance- This was an in-silico analysis towards the development of an autonomous artificial pancreas system for glucose control. The proposed system show promise in eliminating the need for estimating the carbohydrate content in meals.
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Schiaffini R, Deodati A, Nicoletti MC, Carducci C, Ciampalini P, Lorubbio A, Matteoli MC, Pampanini V, Patera IP, Rapini N, Cianfarani S. Comparison of two advanced hybrid closed loop in a pediatric population with type 1 diabetes: a real-life observational study. Acta Diabetol 2022; 59:959-964. [PMID: 35451679 DOI: 10.1007/s00592-022-01886-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 03/28/2022] [Indexed: 11/01/2022]
Abstract
OBJECTIVE The Advanced Hybrid Closed Loop (AHCL) systems have provided the potential to ameliorate glucose control in children with Type 1 Diabetes. The aim of the present work was to compare metabolic control obtained with 2 AHCL systems (Medtronic 780G system and Tandem Control IQ system) in a pediatric real-life clinical context. RESEARCH DESIGN AND METHODS It is an observational, real-life, monocentric study; thirty one children and adolescents (M:F = 15:16, age range 7.6-18 years, mean age 13.05 ± 2.4 years, Diabetes duration > 1 year) with T1D, previously treated with Predictive Low Glucose Suspend (PLGS) systems and then upgraded to AHCL have been enrolled. CGM data of the last four weeks of "PLGS system" (PRE period) with the first four weeks of AHCL system (POST period) have been compared. RESULTS For both AHCL systems, Medtronic 780G and Tandem Control IQ, respectively TIR at 4 weeks significantly increased, from 65.7 to 70.5% (p < 0.01) and from 64.8 to 70.1% (p < 0.01). (p < 0.01). The comparison between CGM metrics of the 2 evaluated systems doesn't show difference at baseline (last four weeks of PLGS system) and after four weeks of AHCL use. CONCLUSIONS To our knowledge, this study is the first real-life one comparing 2 AHCL systems in a pediatric population with T1D. It shows an improvement in glucose control when upgrading to AHCL. The comparison between the two AHCL systems did not show significant differences in the analyzed CGM metrics, meaning that the algorithms currently available are equally effective in promoting glucose control.
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Affiliation(s)
- R Schiaffini
- Diabetes Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio, 4, 00165, Rome, Italy.
| | - A Deodati
- Diabetes Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio, 4, 00165, Rome, Italy
| | - M C Nicoletti
- Pediatric Department, Siena University, Siena, Italy
| | - C Carducci
- Diabetes Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio, 4, 00165, Rome, Italy
| | - P Ciampalini
- Diabetes Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio, 4, 00165, Rome, Italy
| | - A Lorubbio
- Diabetes Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio, 4, 00165, Rome, Italy
| | - M C Matteoli
- Diabetes Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio, 4, 00165, Rome, Italy
| | - V Pampanini
- Diabetes Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio, 4, 00165, Rome, Italy
| | - I P Patera
- Diabetes Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio, 4, 00165, Rome, Italy
| | - N Rapini
- Diabetes Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio, 4, 00165, Rome, Italy
| | - S Cianfarani
- Diabetes Unit, Bambino Gesù Children's Hospital, Piazza S Onofrio, 4, 00165, Rome, Italy
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
- Department of Public Health and Cell Biology, Rina Balducci Center of Pediatric Endocrinology, Tor Vergata University, Rome, Italy
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Abstract
PURPOSE OF REVIEW Closed-loop insulin pump systems (artificial pancreas) represent the cutting edge of insulin delivery technology. There are only a few systems currently approved for use in the USA: the MiniMed 670G/770G (which share an algorithm), t:slim X2 Control IQ, and the Omnipod 5. We review these systems and look into the future of the technology. RECENT FINDINGS All of the approved closed-loop insulin pump systems have demonstrated in multicenter prospective trials improvements in time in range, hemoglobin A1c, and time spent in hypoglycemia. The newer systems have also improved time spent in automation. Comparisons between the systems with regard to glycemic control are difficult to make due to differences in clinical trial design, but there are notable differences in the user experience between systems. The past few years have been a time of exponential development in the field of closed-loop insulin pump systems. However, more research is needed to provide full automation of these systems without any need for information from the user.
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Affiliation(s)
- Keren Zhou
- Endocrinology and Metabolism Institute, Cleveland Clinic, 9500 Euclid Avenue, F20, Cleveland, OH, 44195, US.
| | - Diana Isaacs
- Endocrinology and Metabolism Institute, Cleveland Clinic, 9500 Euclid Avenue, F20, Cleveland, OH, 44195, US
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Morrison AE, Chong K, Lai V, Farnsworth K, Senior PA, Lam A. Improved Glycemia and Quality of Life Among Loop users – Analysis of Real-World Data from a Single Centre (Preprint). JMIR Diabetes 2022; 7:e40326. [DOI: 10.2196/40326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/17/2022] [Accepted: 09/01/2022] [Indexed: 11/13/2022] Open
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Faccioli S, Sala-Mira I, Díez JL, Facchinetti A, Sparacino G, Del Favero S, Bondia J. Super-twisting-based meal detector for type 1 diabetes management: Improvement and assessment in a real-life scenario. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 219:106736. [PMID: 35338888 DOI: 10.1016/j.cmpb.2022.106736] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 02/24/2022] [Accepted: 03/06/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND AND OBJECTIVE Hybrid automated insulin delivery systems rely on carbohydrate counting to improve postprandial control in type 1 diabetes. However, this is an extra burden on subjects, and it introduces a source of potential errors that could impact control performances. In fact, carbohydrates estimation is challenging, prone to errors, and it is known that subjects sometimes struggle to adhere to this requirement, forgetting to perform this task. A possible solution is the use of automated meal detection algorithms. In this work, we extended a super-twisting-based meal detector suggested in the literature and assessed it on real-life data. METHODS To reduce the false detections in the original meal detector, we implemented an implicit discretization of the super-twisting and replaced the Euler approximation of the glucose derivative with a Kalman filter. The modified meal detector is retrospectively evaluated in a challenging real-life dataset corresponding to a 2-week trial with 30 subjects using sensor-augmented pump control. The assessment includes an analysis of the nature and riskiness of false detections. RESULTS The proposed algorithm achieved a recall of 70 [13] % (median [interquartile range]), a precision of 73 [26] %, and had 1.4 [1.4] false positives-per-day. False positives were related to rising glucose conditions, whereas false negatives occurred after calibrations, missing samples, or hypoglycemia treatments. CONCLUSIONS The proposed algorithm achieves encouraging performance. Although false positives and false negatives were not avoided, they are related to situations with a low risk of hypoglycemia and hyperglycemia, respectively.
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Affiliation(s)
- S Faccioli
- Department of Information Engineering - DEI, University of Padova, 35131, PD, Italy
| | - I Sala-Mira
- Instituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, Valencia, 46022, Spain
| | - J L Díez
- Instituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, Valencia, 46022, Spain; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas - CIBERDEM, Madrid, 28028, Spain
| | - A Facchinetti
- Department of Information Engineering - DEI, University of Padova, 35131, PD, Italy
| | - G Sparacino
- Department of Information Engineering - DEI, University of Padova, 35131, PD, Italy
| | - S Del Favero
- Department of Information Engineering - DEI, University of Padova, 35131, PD, Italy.
| | - J Bondia
- Instituto Universitario de Automática e Informática Industrial, Universitat Politècnica de València, Valencia, 46022, Spain; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas - CIBERDEM, Madrid, 28028, Spain
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50
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Witte H, Nakas CT, Bally L, Leichtle AB. Machine-learning Prediction of Hypo- and Hyperglycemia from Electronic Health Records: Algorithm Development and Validation. JMIR Form Res 2022; 6:e36176. [PMID: 35526139 PMCID: PMC9345028 DOI: 10.2196/36176] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 04/25/2022] [Accepted: 05/08/2022] [Indexed: 01/16/2023] Open
Abstract
Background Acute blood glucose (BG) decompensations (hypoglycemia and hyperglycemia) represent a frequent and significant risk for inpatients and adversely affect patient outcomes and safety. The increasing need for BG management in inpatients poses a high demand on clinical staff and health care systems in addition. Objective This study aimed to generate a broadly applicable multiclass classification model for predicting BG decompensation events from patients’ electronic health records to indicate where adjustments in patient monitoring and therapeutic interventions are required. This should allow for taking proactive measures before BG levels are derailed. Methods A retrospective cohort study was conducted on patients who were hospitalized at a tertiary hospital in Bern, Switzerland. Using patient details and routine data from electronic health records, a multiclass prediction model for BG decompensation events (<3.9 mmol/L [hypoglycemia] or >10, >13.9, or >16.7 mmol/L [representing different degrees of hyperglycemia]) was generated based on a second-level ensemble of gradient-boosted binary trees. Results A total of 63,579 hospital admissions of 38,250 patients were included in this study. The multiclass prediction model reached specificities of 93.7%, 98.9%, and 93.9% and sensitivities of 67.1%, 59%, and 63.6% for the main categories of interest, which were nondecompensated cases, hypoglycemia, or hyperglycemia, respectively. The median prediction horizon was 7 hours and 4 hours for hypoglycemia and hyperglycemia, respectively. Conclusions Electronic health records have the potential to reliably predict all types of BG decompensation. Readily available patient details and routine laboratory data can support the decisions for proactive interventions and thus help to reduce the detrimental health effects of hypoglycemia and hyperglycemia.
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Affiliation(s)
- Harald Witte
- University Institute of Clinical Chemistry, Inselspital - Bern University Hospital and University of Bern, Freiburgstrasse 10, Bern, CH
| | - Christos Theodoros Nakas
- University Institute of Clinical Chemistry, Inselspital - Bern University Hospital and University of Bern, Freiburgstrasse 10, Bern, CH.,Laboratory of Biometry, University of Thessaly, Volos, GR
| | - Lia Bally
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital - Bern University Hospital and University of Bern, Bern, CH
| | - Alexander Benedikt Leichtle
- University Institute of Clinical Chemistry, Inselspital - Bern University Hospital and University of Bern, Freiburgstrasse 10, Bern, CH.,Center of Artificial Intelligence in Medicine (CAIM), University of Bern, Bern, CH
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