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Scully KJ, Marks BE, Putman MS. Advances in diabetes technology to improve the lives of people with cystic fibrosis. Diabetologia 2024:10.1007/s00125-024-06223-3. [PMID: 38995399 DOI: 10.1007/s00125-024-06223-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 05/17/2024] [Indexed: 07/13/2024]
Abstract
People with cystic fibrosis (CF) are at risk for dysglycaemia caused by progressive beta cell dysfunction and destruction due to pancreatic exocrine disease and fibrosis. CF-related diabetes (CFRD) is a unique form of diabetes that has distinctive features from both type 1 and type 2 diabetes. Recent advances in diabetes technology may be of particular benefit in this population given the complex, multi-system organ involvement and challenging health issues that people with CFRD often face. This review summarises how diabetes technologies, such as continuous glucose monitors (CGMs) and insulin delivery devices: (1) have improved our understanding of CFRD, including how hyperglycaemia affects clinical outcomes in people with CF; (2) may be helpful in the screening and diagnosis of CFRD; and (3) offer promise for improving the management of CFRD and easing the burden that this diagnosis can add to an already medically complicated patient population.
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Affiliation(s)
- Kevin J Scully
- Hasbro Children's Hospital, Warren Alpert School of Medicine, Providence, RI, USA
| | - Brynn E Marks
- Children's Hospital of Philadelphia, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Melissa S Putman
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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2
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Schoelwer MJ, DeBoer MD, Breton MD. Use of diabetes technology in children. Diabetologia 2024:10.1007/s00125-024-06218-0. [PMID: 38995398 DOI: 10.1007/s00125-024-06218-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Accepted: 05/23/2024] [Indexed: 07/13/2024]
Abstract
Children with type 1 diabetes and their caregivers face numerous challenges navigating the unpredictability of this complex disease. Although the burden of managing diabetes remains significant, new technology has eased some of the load and allowed children with type 1 diabetes to achieve tighter glycaemic management without fear of excess hypoglycaemia. Continuous glucose monitor use alone improves outcomes and is considered standard of care for paediatric type 1 diabetes management. Similarly, automated insulin delivery (AID) systems have proven to be safe and effective for children as young as 2 years of age. AID use improves not only blood glucose levels but also quality of life for children with type 1 diabetes and their caregivers and should be strongly considered for all youth with type 1 diabetes if available and affordable. Here, we review key data on the use of diabetes technology in the paediatric population and discuss management issues unique to children and adolescents.
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Affiliation(s)
| | - Mark D DeBoer
- Department of Pediatrics, University of Virginia, Charlottesville, VA, USA
| | - Marc D Breton
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.
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Blanchard J, Ahmed S, Clark B, Sanchez Cotto L, Rangasamy S, Thompson B. Design and Testing of a Smartphone Application for Real-Time Tracking of CSII and CGM Site Rotation Compliance in Patients With Type 1 Diabetes. J Diabetes Sci Technol 2024; 18:937-945. [PMID: 36539997 DOI: 10.1177/19322968221145178] [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: 12/24/2022]
Abstract
INTRODUCTION Glycemic control in patients with type 1 diabetes can be difficult to achieve. One critical aspect of insulin delivery is site rotation, which is necessary to reduce dermatologic complications of repeated insulin infusion. No current application is designed to help patients track sites and instruct on overused sites. OBJECTIVE The objectives of this study were to (1) design a smartphone app, Insulin Site Guide, to gather real-time information on continuous subcutaneous insulin infusion (CSII) and continuous glucose monitor (CGM) site location and rotation compliance and instruct subjects on the use of an overused site; (2) conduct a usability study to measure site rotation compliance; and (3) report subject satisfaction with the app. DESIGN The app is installed on the subject's smartphone. Subjects use the app to record CSII and CGM placement in real-time. Data are sent to the study team at the end of the study. Subjects complete a questionnaire concerning the app. RESULTS We report site rotation compliance data for eight subjects and survey responses for 10 subjects. Initial data from eight subjects indicate a high site rotation compliance of 84% for insulin pumps. In general, the majority of users indicate high satisfaction with the app. CONCLUSIONS Insulin Site Guide is a mobile app that uses a novel algorithm to better guide site rotation. Use of the app has the potential to improve site rotation and decrease dermatologic complications of diabetes with long-term use.
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Affiliation(s)
- John Blanchard
- Translational Genomics Research Institute, Phoenix, AZ, USA
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4
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Galindo RJ, Aleppo G, Parkin CG, Baidal DA, Carlson AL, Cengiz E, Forlenza GP, Kruger DF, Levy C, McGill JB, Umpierrez GE. Increase Access, Reduce Disparities: Recommendations for Modifying Medicaid CGM Coverage Eligibility Criteria. J Diabetes Sci Technol 2024; 18:974-987. [PMID: 36524477 DOI: 10.1177/19322968221144052] [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: 12/23/2022]
Abstract
Numerous studies have demonstrated the clinical value of continuous glucose monitoring (CGM) in type 1 diabetes (T1D) and type 2 diabetes (T2D) populations. However, the eligibility criteria for CGM coverage required by the Centers for Medicare & Medicaid Services (CMS) ignore the conclusive evidence that supports CGM use in various diabetes populations that are currently deemed ineligible. In an earlier article, we discussed the limitations and inconsistencies of the agency's CGM eligibility criteria relative to current scientific evidence and proposed practice solutions to address this issue and improve the safety and care of Medicare beneficiaries with diabetes. Although Medicaid is administered through CMS, there is no consistent Medicaid policy for CGM coverage in the United States. This article presents a rationale for modifying and standardizing Medicaid CGM coverage eligibility across the United States.
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Affiliation(s)
- Rodolfo J Galindo
- Emory University School of Medicine, Atlanta, GA, USA
- Center for Diabetes Metabolism Research, Emory University Hospital Midtown, Atlanta, GA, USA
- Hospital Diabetes Taskforce, Emory Healthcare System, Atlanta, GA, USA
| | - Grazia Aleppo
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | - David A Baidal
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Anders L Carlson
- International Diabetes Center, Minneapolis, MN, USA
- Regions Hospital & HealthPartners Clinics, St. Paul, MN, USA
- Diabetes Education Programs, HealthPartners and Stillwater Medical Group, Stillwater, MN, USA
- University of Minnesota Medical School, Minneapolis, MN, USA
| | - Eda Cengiz
- Pediatric Diabetes Program, Division of Pediatric Endocrinology, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Gregory P Forlenza
- Barbara Davis Center, Division of Pediatric Endocrinology, Department of Pediatrics, University of Colorado Denver, Denver, CO, USA
| | - Davida F Kruger
- Division of Endocrinology, Diabetes, Bone & Mineral, Henry Ford Health System, Detroit, MI, USA
| | - Carol Levy
- Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mount Sinai Diabetes Center and T1D Clinical Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Janet B McGill
- Division of Endocrinology, Metabolism & Lipid Research, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Guillermo E Umpierrez
- Division of Endocrinology, Metabolism, Emory University School of Medicine, Atlanta, GA, USA
- Diabetes and Endocrinology, Grady Memorial Hospital, Atlanta, GA, USA
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5
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Nanayakkara N, Sharifi A, Burren D, Elghattis Y, Jayarathna DK, Cohen N. Hybrid Closed Loop Using a Do-It-Yourself Artificial Pancreas System in Adults With Type 1 Diabetes. J Diabetes Sci Technol 2024; 18:889-896. [PMID: 36788715 DOI: 10.1177/19322968231153882] [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: 02/16/2023]
Abstract
OBJECTIVE There is increasing use of open-source artificial pancreas systems (APS) in the management of Type 1 diabetes. Our aim was to assess the safety and efficacy of the automated insulin delivery system AndroidAPS (AAPS), compared with stand-alone pump therapy in people with type 1 diabetes. The primary outcome was the difference in the percentage of time in range (TIR, 70-180 mg/dL). Secondary aims included mean sensor glucose value and percent continuous glucose monitor (CGM) time below range (TBR, <70 mg/dL). RESEARCH DESIGN AND METHODS This open-label single-center randomized crossover study (ANZCTR, Australian New Zealand clinical trial registry, ANZCTR-ACTRN12620001191987) comprised 20 participants with type 1 diabetes on established pump therapy, assigned to either stand-alone insulin pump therapy or the open-source AAPS hybrid closed-loop system for four weeks, with crossover to the alternate arm for the following four weeks. The CGM outcome parameters were measured by seven-day CGM at baseline and the final week of each four-week study arm. RESULTS Twenty participants were recruited (60% women), aged 45.8 ± 15.9 years, with mean diabetes duration of 23.9 ± 13.2 years, baseline glycated hemoglobin (HbA1c) 7.5% ± 0.5% (58 ± 6 mmol/mol) and mean TIR 62.3% ± 12.9%. The change in TIR from baseline for AAPS compared with stand-alone pump therapy was 18.6% (11.4-25.9), (P < .001), TIR 76.6% ± 11.7%, 58.0% ± 15.6%, for AAPS and stand-alone pump, respectively. Time glucose <54 mg/dL was not increased (mean = -2.0%, P = .191). No serious adverse events or episodes of severe hypoglycemia were recorded. CONCLUSIONS This clinical trial of the open-source AAPS hybrid closed-loop system performed in an at-home setting demonstrated comparable safety to stand-alone pump therapy. The glycemic outcomes of AAPS were superior with improved TIR, and there was no significant difference in TBR compared with stand-alone pump therapy.
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Affiliation(s)
- Natalie Nanayakkara
- Department of Diabetes Clinical Research, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Amin Sharifi
- Department of Diabetes Clinical Research, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Department of Endocrinology and Diabetes, Eastern Health, Box Hill, VIC, Australia
| | - David Burren
- Department of Diabetes Clinical Research, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Yasser Elghattis
- Department of Diabetes Clinical Research, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Dulari K Jayarathna
- Department of Diabetes Clinical Research, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Neale Cohen
- Department of Diabetes Clinical Research, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
- School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
- School of Pharmacy, The University of Queensland, Brisbane, QLD, Australia
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de Jong LA, Li X, Emamipour S, van der Werf S, Postma MJ, van Dijk PR, Feenstra TL. Evaluating the Cost-Utility of Continuous Glucose Monitoring in Individuals with Type 1 Diabetes: A Systematic Review of the Methods and Quality of Studies Using Decision Models or Empirical Data. PHARMACOECONOMICS 2024:10.1007/s40273-024-01388-6. [PMID: 38904911 DOI: 10.1007/s40273-024-01388-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 04/22/2024] [Indexed: 06/22/2024]
Abstract
INTRODUCTION This review presents a critical appraisal of differences in the methodologies and quality of model-based and empirical data-based cost-utility studies on continuous glucose monitoring (CGM) in type 1 diabetes (T1D) populations. It identifies key limitations and challenges in health economic evaluations on CGM and opportunities for their improvement. METHODS The review and its documentation adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for systematic reviews. Searches for articles published between January 2000 and January 2023 were conducted using the MEDLINE, Embase, Web of Science, Cochrane Library, and Econlit databases. Published studies using models and empirical data to evaluate the cost utility of all CGM devices used by T1D patients were included in the search. Two authors independently extracted data on interventions, populations, model settings (e.g., perspectives and time horizons), model types and structures, clinical outcomes used to populate the model, validation, and uncertainty analyses. They subsequently met to confirm consensus. Quality was assessed using the Philips checklist for model-based studies and the Consensus Health Economic Criteria (CHEC) checklist for empirical studies. Model validation was assessed using the Assessment of the Validation Status of Health-Economic decision models (AdViSHE) checklist. The extracted data were used to generate summary tables and figures. The study protocol is registered with PROSPERO (CRD42023391284). RESULTS In total, 34 studies satisfied the selection criteria, two of which only used empirical data. The remaining 32 studies applied 10 different models, with a substantial majority adopting the CORE Diabetes Model. Model-based studies often lacked transparency, as their assumptions regarding the extrapolation of treatment effects beyond available evidence from clinical studies and the selection and processing of the input data were not explicitly stated. Initial scores for disagreements concerning checklists were relatively high, especially for the Philips checklist. Following their resolution, overall quality scores were moderate at 56%, whereas model validation scores were mixed. Strikingly, costing approaches differed widely across studies, resulting in little consistency in the elements included in intervention costs. DISCUSSION AND CONCLUSION The overall quality of studies evaluating CGM was moderate. Potential areas of improvement include developing systematic approaches for data selection, improving uncertainty analyses, clearer reporting, and explaining choices for particular modeling approaches. Few studies provided the assurance that all relevant and feasible options had been compared, which is required by decision makers, especially for rapidly evolving technologies such as CGM and insulin administration. High scores for disagreements indicated that several checklists contained questions that were difficult to interpret consistently for quality assessment. Therefore, simpler but comprehensive quality checklists may be needed for model-based health economic evaluation studies.
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Affiliation(s)
- Lisa A de Jong
- Department of Health Sciences, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Xinyu Li
- Groningen Research Institute of Pharmacy (GRIP), Faculty of Science and Engineering, University of Groningen, Groningen, The Netherlands
| | - Sajad Emamipour
- Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Sjoukje van der Werf
- Central Medical Library, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Maarten J Postma
- Department of Health Sciences, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Economics, Econometrics and Finance, Faculty of Economics and Business, University of Groningen, Groningen, The Netherlands
- Center of Excellence for Pharmaceutical Care Innovation, Universitas Padjadjaran, Bandung, Indonesia
- Department of Pharmacology and Therapy, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia
| | - Peter R van Dijk
- Department of Endocrinology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Internal Medicine, Diabetes Center, Isala, Zwolle, The Netherlands
| | - Talitha L Feenstra
- Groningen Research Institute of Pharmacy (GRIP), Faculty of Science and Engineering, University of Groningen, Groningen, The Netherlands.
- National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.
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Annicchiarico A, Barile B, Buccoliero C, Nicchia GP, Brunetti G. Alternative therapeutic strategies in diabetes management. World J Diabetes 2024; 15:1142-1161. [PMID: 38983831 PMCID: PMC11229975 DOI: 10.4239/wjd.v15.i6.1142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 02/17/2024] [Accepted: 04/12/2024] [Indexed: 06/11/2024] Open
Abstract
Diabetes is a heterogeneous metabolic disease characterized by elevated blood glucose levels resulting from the destruction or malfunction of pancreatic β cells, insulin resistance in peripheral tissues, or both, and results in a non-sufficient production of insulin. To adjust blood glucose levels, diabetic patients need exogenous insulin administration together with medical nutrition therapy and physical activity. With the aim of improving insulin availability in diabetic patients as well as ameliorating diabetes comorbidities, different strategies have been investigated. The first approaches included enhancing endogenous β cell activity or transplanting new islets. The protocol for this kind of intervention has recently been optimized, leading to standardized procedures. It is indicated for diabetic patients with severe hypoglycemia, complicated by impaired hypoglycemia awareness or exacerbated glycemic lability. Transplantation has been associated with improvement in all comorbidities associated with diabetes, quality of life, and survival. However, different trials are ongoing to further improve the beneficial effects of transplantation. Furthermore, to overcome some limitations associated with the availability of islets/pancreas, alternative therapeutic strategies are under evaluation, such as the use of mesenchymal stem cells (MSCs) or induced pluripotent stem cells for transplantation. The cotransplantation of MSCs with islets has been successful, thus providing protection against proinflammatory cytokines and hypoxia through different mechanisms, including exosome release. The use of induced pluripotent stem cells is recent and requires further investigation. The advantages of MSC implantation have also included the improvement of diabetes-related comorbidities, such as wound healing. Despite the number of advantages of the direct injection of MSCs, new strategies involving biomaterials and scaffolds have been developed to improve the efficacy of mesenchymal cell delivery with promising results. In conclusion, this paper offered an overview of new alternative strategies for diabetes management while highlighting some limitations that will need to be overcome by future approaches.
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Affiliation(s)
- Alessia Annicchiarico
- Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari 70125, Italy
| | - Barbara Barile
- Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari 70125, Italy
| | - Cinzia Buccoliero
- Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari 70125, Italy
| | - Grazia Paola Nicchia
- Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari 70125, Italy
| | - Giacomina Brunetti
- Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari 70125, Italy
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Scidà G, Corrado A, Abuqwider J, Lupoli R, Rainone C, Della Pepa G, Masulli M, Annuzzi G, Bozzetto L. Postprandial Glucose Control With Different Hybrid Closed-Loop Systems According to Type of Meal in Adults With Type 1 Diabetes. J Diabetes Sci Technol 2024:19322968241256475. [PMID: 38840523 DOI: 10.1177/19322968241256475] [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: 06/07/2024]
Abstract
BACKGROUND Hybrid Closed-Loop Systems (HCLs) may not perform optimally on postprandial glucose control. We evaluated how first-generation and advanced HCLs manage meals varying in carbohydrates, fat, and protein. METHOD According to a cross-sectional design, seven-day food records and HCLs reports from 120 adults with type 1 diabetes (MiniMed670G: n = 40, MiniMed780G: n = 49, Control-IQ [C-IQ]: n = 31) were analyzed. Breakfasts (n = 570), lunches (n = 658), and dinners (n = 619) were divided according to the median of their carbohydrate (g)/fat (g) plus protein (g) ratio (C/FP). After breakfast (4-hour), lunch (6-hour), and dinner (6-hour), continuous glucose monitoring (CGM) metrics and early and late glucose incremental area under the curves (iAUCs) and delivered insulin doses were evaluated. The association of C/FP and HCLs with postprandial glucose and insulin patterns was analyzed by univariate analysis of variance (ANOVA) with a two-factor design. RESULTS Postprandial glucose time-in-range 70 to 180 mg/dL was optimal after breakfast (78.3 ± 26.9%), lunch (72.7 ± 26.1%), and dinner (70.8 ± 27.3%), with no significant differences between HCLs. Independent of C/FP, late glucose-iAUC after lunch was significantly lower in C-IQ users than 670G and 780G (P < .05), with no significant differences at breakfast and dinner. Postprandial insulin pattern (Ins3-6h minus Ins0-3h) differed by type of HCLs at lunch (P = .026) and dinner (P < .001), being the early insulin dose (Ins0-3h) higher than the late dose (Ins3-6h) in 670G and 780G users with an opposite pattern in C-IQ users. CONCLUSIONS Independent of different proportions of dietary carbohydrates, fat, and protein, postprandial glucose response was similar in users of different HCLs, although obtained through different automatic insulin delivery patterns.
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Affiliation(s)
- Giuseppe Scidà
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Alessandra Corrado
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Jumana Abuqwider
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Roberta Lupoli
- Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy
| | - Carmen Rainone
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Giuseppe Della Pepa
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Maria Masulli
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Giovanni Annuzzi
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Lutgarda Bozzetto
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
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Forlenza GP, Tabatabai I, Lewis DM. Point-Counterpoint: The Need for Do-It-Yourself (DIY) Open Source (OS) AID Systems in Type 1 Diabetes Management. Diabetes Technol Ther 2024. [PMID: 38669472 DOI: 10.1089/dia.2024.0073] [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: 04/28/2024]
Abstract
In the last decade, technology developed by people with diabetes and their loved ones has added to the options for diabetes management. One such example is that of automated insulin delivery (AID) algorithms, which were created and shared as open source by people living with type 1 diabetes (T1D) years before commercial systems were first available. Now, numerous options for commercial systems exist in some countries, yet tens of thousands of people with diabetes are still choosing Open-Source AID (OS-AID), previously called "do-it-yourself" (DIY) systems, which are noncommercial versions of these open-source AID systems. In this article, we provide point and counterpoint perspectives regarding (1) safety and efficacy, (2) regulation and support, (3) user choice and flexibility, (4) access and affordability, and (5) patient and provider education, for open source and commercial AID systems. The perspectives reflected here include that of a person living with T1D who uses and has developed OS-AID systems, a physician-researcher based in the United States who conducts clinical trials to support development of commercial AID systems and supports people with diabetes using all types of AID, and an endocrinologist with T1D who uses both systems and treats people with diabetes using all types of AID.
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Affiliation(s)
- Gregory P Forlenza
- Barbara Davis Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Ideen Tabatabai
- Barbara Davis Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
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10
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Ng SM, Wright NP, Yardley D, Campbell F, Randell T, Trevelyan N, Ghatak A, Hindmarsh PC. Long-term assessment of the NHS hybrid closed-loop real-world study on glycaemic outcomes, time-in-range, and quality of life in children and young people with type 1 diabetes. BMC Med 2024; 22:175. [PMID: 38659016 PMCID: PMC11044460 DOI: 10.1186/s12916-024-03396-x] [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: 12/07/2023] [Accepted: 04/17/2024] [Indexed: 04/26/2024] Open
Abstract
Hybrid closed-loop (HCL) systems seamlessly interface continuous glucose monitoring (CGM) with insulin pumps, employing specialised algorithms and user-initiated automated insulin delivery. This study aimed to assess the efficacy of HCLs at 12 months post-initiation on glycated haemoglobin (HbA1c), time-in-range (TIR), hypoglycaemia frequency, and quality of life measures among children and young people (CYP) with type 1 diabetes mellitus (T1DM) and their caregivers in a real-world setting. Conducted between August 1, 2021, and December 10, 2022, the prospective recruitment took place in eight paediatric diabetes centres across England under the National Health Service England's (NHSE) HCL pilot real-world study. A cohort of 251 CYP (58% males, mean age 12.3 years) with T1DM participated (89% white, 3% Asian, 4% black, 3% mixed ethnicity, and 1% other). The study utilised three HCL systems: (1) Tandem Control-IQ AP system, which uses the Tandem t:slim X2 insulin pump (Tandem Diabetes Care, San Diego, CA, USA) with the Dexcom G6® CGM (Dexcom, San Diego, CA, USA) sensor; (2) Medtronic MiniMed™ 780G with the Guardian 4 sensor (Medtronic, Northridge, CA, USA); and (3) the CamAPS FX (CamDiab, Cambridge, UK) with the Ypsomed insulin pump (Ypsomed Ltd, Escrick, UK) and Dexcom G6® CGM.All systems were fully funded by the NHS. Results demonstrated significant improvements in HbA1c (average reduction at 12 months 7 mmol/mol; P < 0.001), time-in-range (TIR) (average increase 13.4%; P < 0.001), hypoglycaemia frequency (50% reduction), hypoglycaemia fear, and quality of sleep (P < 0.001) among CYP over a 12-month period of HCL usage. Additionally, parents and carers experienced improvements in hypoglycaemia fear and quality of sleep after 6 and 12 months of use. In addition to the improvements in glycaemic management, these findings underscore the positive impact of HCL systems on both the well-being of CYP with T1DM and the individuals caring for them.
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Affiliation(s)
- Sze May Ng
- Faculty of Health, Social Care and Medicine, Edge Hill University, Ormskirk, UK.
- Department of Women's and Children's Health, University of Liverpool, Liverpool, UK.
- Paediatric Department, Mersey and West Lancashire Teaching Hospitals, Ormskirk, L39 2AZ, 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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11
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Forlenza GP, Dai Z, Niu F, Shin JJ. Reducing Diabetes Burden in Medtronic's Automated Insulin Delivery Systems. Diabetes Technol Ther 2024; 26:7-16. [PMID: 38377321 DOI: 10.1089/dia.2023.0459] [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: 02/22/2024]
Abstract
Background: The MiniMed™ 780G advanced hybrid closed-loop system (MM780G) builds on the basal automation and low-glucose protection features of the MiniMed™ 670G and 770G systems. While previous publications have focused on glycemic control improvements with MM780G, burden reduction has not been fully described. Methods: Data from two 3-month pivotal trials for the MM670G with Guardian™ Sensor 3 (GS3) (104 adults; 125 children) and MM780G with Guardian™ 4 Sensor (G4S) (67 adults;109 children) were compared. Real-world data (RWD) from United States users (N = 3851) transitioning from MM770G+GS3 to MM780G+G4S were also analyzed. Analyses included a new metric for diabetes management burden (i.e., pentagon composite metric), glycemic outcomes and system burden (e.g., closed-loop exits and fingersticks per day). Results: Diabetes burden metric (-22.8% and -28.5%), time in range (+3.1% [*P = 0.035] and +6.4% [P < 0.001]) and time below range (-1.8% [*P < 0.001] and -0.7% [*P < 0.001]) significantly improved, compared to MM670G for adult and pediatric participants, respectively. The pediatric mean sensor glucose (SG) reduced by -8.6 mg/dL (*P < 0.001), while the adults' saw no change. Closed-loop use significantly increased for both cohorts (+17.1% [*P < 0.001] and +20.5% [*P < 0.001]). Closed-loop exits were significantly reduced to about 1 per week (-0.5 [*P < 0.001] and -0.7 [*P < 0.001]); fingerstick tests were also reduced (-6.2 [*P < 0.001] and -6.9 [*P < 0.001]). Similar outcomes were observed from U.S. RWD. Conclusions: MiniMed™ 780G with G4S use was associated with significant reduction in diabetes management burden with fewer closed-loop exits, fingersticks and other interactions, and improvements in glycemic control when compared to the MiniMed™ 670G with GS3.
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Affiliation(s)
- Gregory P Forlenza
- Barbara Davis Center, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Zheng Dai
- Medtronic Diabetes, Northridge, California, USA
| | - Fang Niu
- Medtronic Diabetes, Northridge, California, USA
| | - John J Shin
- Medtronic Diabetes, Northridge, California, USA
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12
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Considine EG, Sherr JL. Real-World Evidence of Automated Insulin Delivery System Use. Diabetes Technol Ther 2024; 26:53-65. [PMID: 38377315 PMCID: PMC10890954 DOI: 10.1089/dia.2023.0442] [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: 02/22/2024]
Abstract
Objective: Pivotal trials of automated insulin delivery (AID) closed-loop systems have demonstrated a consistent picture of glycemic benefit, supporting approval of multiple systems by the Food and Drug Administration or Conformité Européenne mark receipt. To assess how pivotal trial findings translate to commercial AID use, a systematic review of retrospective real-world studies was conducted. Methods: PubMed and EMBASE were searched for articles published after 2018 with more than five nonpregnant individuals with type 1 diabetes (T1D). Data were screened/extracted in duplicate for sample size, AID system, glycemic outcomes, and time in automation. Results: Of 80 studies identified, 20 met inclusion criteria representing 171,209 individuals. Time in target range 70-180 mg/dL (3.9-10.0 mmol/L) was the primary outcome in 65% of studies, with the majority of reports (71%) demonstrating a >10% change with AID use. Change in hemoglobin A1c (HbA1c) was reported in nine studies (range 0.1%-0.9%), whereas four reported changes in glucose management indicator (GMI) with a 0.1%-0.4% reduction noted. A decrease in HbA1c or GMI of >0.2% was achieved in two-thirds of the studies describing change in HbA1c and 80% of articles where GMI was described. Time below range <70 mg/dL (<3.9 mmol/L) was reported in 16 studies, with all but 1 study showing stable or reduced levels. Most systems had >90% time in automation. Conclusion: With larger and more diverse populations, and follow-up periods of longer duration (∼9 months vs. 3-6 months for pivotal trials), real-world retrospective analyses confirm pivotal trial findings. Given the glycemic benefits demonstrated, AID is rapidly becoming the standard of care for all people living with T1D. Individuals should be informed of these systems and differences between them, have access to and coverage for these technologies, and receive support as they integrate this mode of insulin delivery into their lives.
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Affiliation(s)
| | - Jennifer L. Sherr
- Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut, USA
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13
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Reddy M, Oliver N. The role of real-time continuous glucose monitoring in diabetes management and how it should link to integrated personalized diabetes management. Diabetes Obes Metab 2024; 26 Suppl 1:46-56. [PMID: 38441367 DOI: 10.1111/dom.15504] [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: 12/23/2023] [Revised: 01/31/2024] [Accepted: 02/04/2024] [Indexed: 03/07/2024]
Abstract
Diabetes is a complex metabolic condition that demands tailored, individualized approaches for effective management. Real-time continuous glucose monitoring (rtCGM) systems have improved in terms of design, usability and accuracy over the years and play a pivotal role in the delivery of integrated personalized diabetes management (iPDM). iPDM is a comprehensive multidisciplinary approach that combines individualized care strategies utilizing technologies and interventions and encourages the active involvement of the person with diabetes in the care provided. The use of stand-alone rtCGM and its integration with other diabetes technologies, such as hybrid automated insulin delivery, have enabled improved glycaemic and quality of life outcomes for people with diabetes. As the uptake of rtCGM and associated technologies is increasing and becoming the standard of care for people with diabetes, it is important that efforts are focused on associated goals such as reducing health inequalities in terms of access, aligning structured education with rtCGM usage, choosing the right technology based on needs and preferences, and minimizing burden while aiming for optimal glucose outcomes. Utilizing rtCGM in other settings than outpatients and in diabetes cohorts beyond type 1 and type 2 diabetes needs further exploration. This review aims to provide an overview of the role of rtCGM and how best to link rtCGM to iPDM, highlighting its role in enhancing personalized treatment strategies.
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Affiliation(s)
- Monika Reddy
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Nick Oliver
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
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14
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Steenkamp DW, Fantasia KL, Wolpert HA. Optimizing Glycemic Outcomes for Minoritized and Medically Underserved Adults Living with Type 1 Diabetes. Endocrinol Metab Clin North Am 2024; 53:67-80. [PMID: 38272599 DOI: 10.1016/j.ecl.2023.07.001] [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] [Indexed: 01/27/2024]
Abstract
Individuals living with type 1 diabetes (T1D) from medically underserved communities have poorer health outcomes. Efforts to improve outcomes include a focus on team-based care, activation of behavior change, and enhancing self-management skills and practices. Advanced diabetes technologies are part of the standard of care for adults with T1D. However, health care providers often carry implicit biases and may be uncomfortable with recommending technologies to patients who have traditionally been excluded from efficacy trials or have limited real-world exposure to devices. We review the literature on this topic and provide an approach to address these issues in clinical practice.
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Affiliation(s)
- Devin W Steenkamp
- Section of Endocrinology, Diabetes and Nutrition, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, 72 East Concord Street, C3, Boston, MA 02118, USA.
| | - Kathryn L Fantasia
- Section of Endocrinology, Diabetes and Nutrition, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, 72 East Concord Street, C3, Boston, MA 02118, USA; Department of Medicine, Evans Center for Implementation and Improvement Sciences (CIIS), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Howard A Wolpert
- Section of Endocrinology, Diabetes and Nutrition, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine and Boston Medical Center, 72 East Concord Street, C3, Boston, MA 02118, USA
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15
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Maahs DM, Prahalad P, Schweiger DS, Shalitin S. Diabetes Technology and Therapy in the Pediatric Age Group. Diabetes Technol Ther 2024; 26:S117-S140. [PMID: 38441448 DOI: 10.1089/dia.2024.2508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/07/2024]
Affiliation(s)
- David M Maahs
- Department of Pediatrics, Division of Endocrinology and Diabetes, Stanford University, Stanford, CA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA
- Department of Health Research and Policy (Epidemiology), Stanford University, Stanford, CA
| | - Priya Prahalad
- Department of Pediatrics, Division of Endocrinology and Diabetes, Stanford University, Stanford, CA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA
| | - Darja Smigoc Schweiger
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, University Children's Hospital, University Medical Centre Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Shlomit Shalitin
- Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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16
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Garg SK, McVean JJ. Development and Future of Automated Insulin Delivery (AID) Systems. Diabetes Technol Ther 2024; 26:1-6. [PMID: 38377322 DOI: 10.1089/dia.2023.0467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Affiliation(s)
- Satish K Garg
- Department of Medicine and Pediatrics, Barbara Davis Center for Diabetes, University of Colorado Denver, Anschutz Medical Campus, Aurora, Colorado, USA
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17
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Schütz A, Rami-Merhar B, Schütz-Fuhrmann I, Blauensteiner N, Baumann P, Pöttler T, Mader JK. Retrospective Comparison of Commercially Available Automated Insulin Delivery With Open-Source Automated Insulin Delivery Systems in Type 1 Diabetes. J Diabetes Sci Technol 2024:19322968241230106. [PMID: 38366626 DOI: 10.1177/19322968241230106] [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: 02/18/2024]
Abstract
BACKGROUND Automated insulin delivery (AID) systems have shown to improve glycemic control in a range of populations and settings. At the start of this study, only one commercial AID system had entered the Austrian market (MiniMed 670G, Medtronic). However, there is an ever-growing community of people living with type 1 diabetes (PWT1D) using open-source (OS) AID systems. MATERIALS AND METHODS A total of 144 PWT1D who used either the MiniMed 670G (670G) or OS-AID systems routinely for a period of at least three to a maximum of six months, between February 18, 2020 and January 15, 2023, were retrospectively analyzed (116 670G aged from 2.6 to 71.8 years and 28 OS-AID aged from 3.4 to 53.5 years). The goal is to evaluate and compare the quality of glycemic control of commercially available AID and OS-AID systems and to present all data by an in-depth descriptive analysis of the population. No statistical tests were performed. RESULTS The PWT1D using OS-AID systems spent more time in range (TIR)70-180 mg/dL (81.7% vs 73.9%), less time above range (TAR)181-250 mg/dL (11.1% vs 19.6%), less TAR>250 mg/dL (2.5% vs 4.3%), and more time below range (TBR)54-69 mg/dL (2.2% vs 1.7%) than PWT1D using the 670G system. The TBR<54 mg/dL was comparable in both groups (0.3% vs 0.4%). In the OS-AID group, median glucose level and glycated hemoglobin (HbA1c) were lower than in the 670G system group (130 vs 150 mg/dL; 6.2% vs 7.0%). CONCLUSION In conclusion, both groups were able to achieve satisfactory glycemic outcomes independent of age, gender, and diabetes duration. However, the PWT1D using OS-AID systems attained an even better glycemic control with no clinical safety concerns.
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Affiliation(s)
- Anna Schütz
- Department of Pediatric and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Birgit Rami-Merhar
- Department of Pediatric and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Ingrid Schütz-Fuhrmann
- Karl Landsteiner Institute, Endocrinology and Nephrology, Vienna, Austria
- Department of Endocrinology and Nephrology, Clinic Hietzing, Vienna Health Care Group, Vienna, Austria
| | - Nicole Blauensteiner
- Department of Pediatric and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Petra Baumann
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Tina Pöttler
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Julia K Mader
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
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18
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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. [PMID: 38375861 DOI: 10.1089/dia.2023.0578] [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: 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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19
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Jacobs PG, Herrero P, Facchinetti A, Vehi J, Kovatchev B, Breton MD, Cinar A, Nikita KS, Doyle FJ, Bondia J, Battelino T, Castle JR, Zarkogianni K, Narayan R, Mosquera-Lopez C. Artificial Intelligence and Machine Learning for Improving Glycemic Control in Diabetes: Best Practices, Pitfalls, and Opportunities. IEEE Rev Biomed Eng 2024; 17:19-41. [PMID: 37943654 DOI: 10.1109/rbme.2023.3331297] [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: 11/12/2023]
Abstract
OBJECTIVE Artificial intelligence and machine learning are transforming many fields including medicine. In diabetes, robust biosensing technologies and automated insulin delivery therapies have created a substantial opportunity to improve health. While the number of manuscripts addressing the topic of applying machine learning to diabetes has grown in recent years, there has been a lack of consistency in the methods, metrics, and data used to train and evaluate these algorithms. This manuscript provides consensus guidelines for machine learning practitioners in the field of diabetes, including best practice recommended approaches and warnings about pitfalls to avoid. METHODS Algorithmic approaches are reviewed and benefits of different algorithms are discussed including importance of clinical accuracy, explainability, interpretability, and personalization. We review the most common features used in machine learning applications in diabetes glucose control and provide an open-source library of functions for calculating features, as well as a framework for specifying data sets using data sheets. A review of current data sets available for training algorithms is provided as well as an online repository of data sources. SIGNIFICANCE These consensus guidelines are designed to improve performance and translatability of new machine learning algorithms developed in the field of diabetes for engineers and data scientists.
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20
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ElSayed NA, Aleppo G, Bannuru RR, Bruemmer D, Collins BS, Ekhlaspour L, Hilliard ME, Johnson EL, Khunti K, Lingvay I, Matfin G, McCoy RG, Perry ML, Pilla SJ, Polsky S, Prahalad P, Pratley RE, Segal AR, Seley JJ, Stanton RC, Gabbay RA. 7. Diabetes Technology: Standards of Care in Diabetes-2024. Diabetes Care 2024; 47:S126-S144. [PMID: 38078575 PMCID: PMC10725813 DOI: 10.2337/dc24-s007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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21
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ElSayed NA, Aleppo G, Bannuru RR, Bruemmer D, Collins BS, Ekhlaspour L, Hilliard ME, Johnson EL, Khunti K, Lingvay I, Matfin G, McCoy RG, Perry ML, Pilla SJ, Polsky S, Prahalad P, Pratley RE, Segal AR, Seley JJ, Stanton RC, Gabbay RA. 14. Children and Adolescents: Standards of Care in Diabetes-2024. Diabetes Care 2024; 47:S258-S281. [PMID: 38078582 PMCID: PMC10725814 DOI: 10.2337/dc24-s014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.
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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: 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: 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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23
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Kaur RJ, Mujtahedi SS, Fridell JA, Benavides X, Smith B, Larson TS, Rizvi SR, Kukla A, Dean P, Kudva YC, Odorico J, Stegall M. Impact of pancreas transplantation alone on kidney function: A multicenter clinical cohort study. Clin Transplant 2024; 38:e15212. [PMID: 38041451 DOI: 10.1111/ctr.15212] [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: 07/31/2023] [Revised: 11/07/2023] [Accepted: 11/20/2023] [Indexed: 12/03/2023]
Abstract
Pancreas transplantation alone (PTA) is a β cell replacement option for selected patients with type 1 diabetes mellitus; concerns have been raised regarding deterioration in kidney function (KF) after PTA. This retrospective multicenter study assessed actual impact of transplantation and immunosuppression on KF in PTA recipients at three Transplant Centers. The primary composite endpoint 10 years after PTA was >50% eGFR decline, eGFR < 30 mL/min/1.73 m2 , and/or receiving a kidney transplant (KT). Overall, 822 PTA recipients met eligibility. Median baseline and 10-year eGFR (mL/min/1.73 m2 ) were 76.3 (58.1-100.8) and 51.3 (35.3-65.9), respectively. Primary composite endpoint occurred in 98 patients (53.5%) with 45 experiencing a >50% decrease in eGFR by 10 years post-transplant, 38 eGFR < 30 mL/min/1.73 m2 and 49 requiring KT. KF declined most significantly within 6 months post-PTA, more often in females and patients with better preserved GFR up to 5 years with 11.6% kidney failure at 10 years. Patient survival and death-censored graft survival were both 68% at 10 years with overall graft thrombosis rate 8%. KF declined initially after PTA but stabilized with further slow progression. In conclusion, prospective intervention studies are needed to test renal sparing interventions while gathering more granular data.
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Affiliation(s)
- Ravinder Jeet Kaur
- Division of Endocrinology, Diabetes, Metabolism, & Nutrition, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Syed Saad Mujtahedi
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota, USA
| | - Jonathan A Fridell
- Department of Surgery, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Xiomara Benavides
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota, USA
| | - Byron Smith
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Timothy S Larson
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA
| | - Shafaq R Rizvi
- Division of Endocrinology, Diabetes, Metabolism, & Nutrition, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Aleksandra Kukla
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, Minnesota, USA
| | - Patrick Dean
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota, USA
| | - Yogish C Kudva
- Division of Endocrinology, Diabetes, Metabolism, & Nutrition, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Jon Odorico
- Division of Transplantation, Department of Surgery, University of Wisconsin School of Medicine and Public Health, UWHealth Transplant Center, Madison, Wisconsin, USA
| | - Mark Stegall
- Department of Surgery and Immunology, Mayo Clinic, Rochester, Minnesota, USA
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Aiello EM, Laffel LM, Patti ME, Doyle FJ. Ketone-Based Alert System for Insulin Pump Failures. J Diabetes Sci Technol 2023:19322968231209339. [PMID: 37946403 DOI: 10.1177/19322968231209339] [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: 11/12/2023]
Abstract
BACKGROUND An increasing number of individuals with type 1 diabetes (T1D) manage glycemia with insulin pumps containing short-acting insulin. If insulin delivery is interrupted for even a few hours due to pump or infusion site malfunction, the resulting insulin deficiency can rapidly initiate ketogenesis and diabetic ketoacidosis (DKA). METHODS To detect an event of accidental cessation of insulin delivery, we propose the design of ketone-based alert system (K-AS). This system relies on an extended Kalman filter based on plasma 3-beta-hydroxybutyrate (BOHB) measurements to estimate the disturbance acting on the insulin infusion/injection input. The alert system is based on a novel physiological model capable of simulating the ketone body turnover in response to a change in plasma insulin levels. Simulated plasma BOHB levels were compared with plasma BOHB levels available in the literature. We evaluated the performance of the K-AS on 10 in silico subjects using the S2014 UVA/Padova simulator for two different scenarios. RESULTS The K-AS achieves an average detection time of 84 and 55.5 minutes in fasting and postprandial conditions, respectively, which compares favorably and improves against a detection time of 193 and 120 minutes, respectively, based on the current guidelines. CONCLUSIONS The K-AS leverages the rapid rate of increase of plasma BOHB to achieve short detection time in order to prevent BOHB levels from rising to dangerous levels, without any false-positive alarms. Moreover, the proposed novel insulin-BOHB model will allow us to understand the efficacy of treatment without compromising patient safety.
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Affiliation(s)
- Eleonora M Aiello
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA, USA
- Sansum Diabetes Research Institute, Santa Barbara, CA, USA
| | - Lori M Laffel
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
| | | | - Francis J Doyle
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Allston, MA, USA
- Sansum Diabetes Research Institute, Santa Barbara, CA, USA
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25
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Nørgaard K, Ranjan AG, Laugesen C, Tidemand KG, Green A, Selmer C, Svensson J, Andersen HU, Vistisen D, Carstensen B. Glucose Monitoring Metrics in Individuals With Type 1 Diabetes Using Different Treatment Modalities: A Real-World Observational Study. Diabetes Care 2023; 46:1958-1964. [PMID: 37610784 DOI: 10.2337/dc23-1137] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 08/04/2023] [Indexed: 08/24/2023]
Abstract
OBJECTIVE This study aimed to investigate the association between continuous glucose monitoring (CGM)-derived glycemic metrics and different insulin treatment modalities using real-world data. RESEARCH DESIGN AND METHODS A cross-sectional study at Steno Diabetes Center Copenhagen, Denmark, included individuals with type 1 diabetes using CGM. Data from September 2021 to August 2022 were analyzed if CGM was used for at least 20% of a 4-week period. Individuals were divided into four groups: multiple daily injection (MDI) therapy, insulin pumps with unintegrated CGM (SUP), sensor-augmented pumps with low glucose management (SAP), and automated insulin delivery (AID). The MDI and SUP groups were further subdivided based on CGM alarm features. The primary outcome was percentage of time in range (TIR: 3.9-10.0 mmol/L) for each treatment group. Secondary outcomes included other glucose metrics and HbA1c. RESULTS Out of 6,314 attendees, 3,184 CGM users were included in the analysis. Among them, 1,622 used MDI, 504 used SUP, 354 used SAP, and 561 used AID. Median TIR was 54.0% for MDI, 54.9% for SUP, 62,9% for SAP, and 72,1% for AID users. The proportion of individuals achieving all recommended glycemic targets (TIR >70%, time above range <25%, and time below range <4%) was significantly higher in SAP (odds ratio [OR] 2.4 [95% CI 1.6-3.5]) and AID (OR 9.4 [95% CI 6.7-13.0]) compared with MDI without alarm features. CONCLUSIONS AID appears superior to other insulin treatment modalities with CGM. Although bias may be present because of indications, AID should be considered the preferred choice for insulin pump therapy.
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Affiliation(s)
- Kirsten Nørgaard
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Ajenthen G Ranjan
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Christian Laugesen
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Katrine G Tidemand
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Allan Green
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Christian Selmer
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Jannet Svensson
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Henrik U Andersen
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Dorte Vistisen
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Bendix Carstensen
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
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26
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Macon EL, Devore MH, Lin YK, Music MB, Wooten M, McMullen CA, Woodcox AM, Marksbury AR, Beckner Z, Patel BV, Schoeder LA, Iles AN, Fisher SJ. Current and future therapies to treat impaired awareness of hypoglycemia. Front Pharmacol 2023; 14:1271814. [PMID: 37942482 PMCID: PMC10628050 DOI: 10.3389/fphar.2023.1271814] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 10/05/2023] [Indexed: 11/10/2023] Open
Abstract
In order to achieve optimal glycemic control, intensive insulin regimes are needed for individuals with Type 1 Diabetes (T1D) and insulin-dependent Type 2 Diabetes (T2D). Unfortunately, intensive glycemic control often results in insulin-induced hypoglycemia. Moreover, recurrent episodes of hypoglycemia result in both the loss of the characteristic warning symptoms associated with hypoglycemia and an attenuated counterregulatory hormone responses. The blunting of warning symptoms is known as impaired awareness of hypoglycemia (IAH). Together, IAH and the loss of the hormonal response is termed hypoglycemia associated autonomic failure (HAAF). IAH is prevalent in up to 25% in people with T1D and up to 10% in people with T2D. IAH and HAAF increase the risk of severe hypoglycemia 6-fold and 25-fold, respectively. To reduce this risk for severe hypoglycemia, multiple different therapeutic approaches are being explored that could improve awareness of hypoglycemia. Current therapies to improve awareness of hypoglycemia include patient education and psychoeducation, the use of novel glycemic control technology, pancreas/islet transplantation, and drug therapy. This review examines both existing therapies and potential therapies that are in pre-clinical testing. Novel treatments that improve awareness of hypoglycemia, via improving the counterregulatory hormone responses or improving hypoglycemic symptom recognition, would also shed light on the possible neurological mechanisms that lead to the development of IAH. To reduce the risk of severe hypoglycemia in people with diabetes, elucidating the mechanism behind IAH, as well as developing targeted therapies is currently an unmet need for those that suffer from IAH.
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Affiliation(s)
- Erica L. Macon
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Micah H. Devore
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Yu Kuei Lin
- Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Megan B. Music
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Mason Wooten
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Colleen A. McMullen
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Andrea M. Woodcox
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Ashlee R. Marksbury
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Zachary Beckner
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Bansi V. Patel
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Lily A. Schoeder
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Ashley N. Iles
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY, United States
| | - Simon J. Fisher
- Division of Endocrinology, Diabetes and Metabolism, Department of Internal Medicine, College of Medicine, University of Kentucky, Lexington, KY, United States
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Pei Y, Ke W, Lu J, Lin Y, Zhang Z, Peng Y, Bi Y, Li Y, Hou J, Zhang X, Chen X, Treminio Y, Lee SW, Shin J, Rhinehart AS, Vigersky RA, Mu Y. Safety Event Outcomes and Glycemic Control with a Hybrid Closed-Loop System Used by Chinese Adolescents and Adults with Type 1 Diabetes Mellitus. Diabetes Technol Ther 2023; 25:718-725. [PMID: 37578804 DOI: 10.1089/dia.2023.0234] [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: 08/15/2023]
Abstract
Background: While evidence supports glycemic control benefits for individuals with type 1 diabetes mellitus (T1DM) using hybrid closed-loop (HCL) systems, HCL automated insulin delivery therapy in China has not been assessed. This study evaluated safety events and effectiveness during HCL system use by Chinese adolescents and adults with T1DM. Methods: Sixty-two participants (n = 12 adolescents with a mean ± standard deviation [SD] of 15.5 ± 1.1 years and n = 50 adults [mean ± SD of 37.6 ± 11.1 years]) with T1DM and baseline A1C of 7.1% ± 1.0% underwent a run-in period (∼2 weeks) using open-loop Manual Mode (sensor-augmented pump) insulin delivery with the MiniMed™ 770G system with the Guardian™ Sensor (3) glucose sensor, followed by a study period (4 weeks) with HCL Auto Mode enabled. Analyses compared continuous glucose monitoring data and insulin delivered during the run-in versus study period (Wilcoxon signed-rank test or t-test). Safety events included rates of severe hypoglycemia and diabetic ketoacidosis (DKA). Results: Compared to baseline run-in, overall Auto Mode use increased time in range (TIR, 70-180 mg/dL) from 75.3% to 80.9% (P < 0.001) and reduced time below range (TBR, <70 mg/dL) from 4.7% to 2.2% (P < 0.001). Subgroup analysis demonstrated that participants (n = 29) with baseline A1C <7.0% had TBR that reduced from 5.6% to 2.0%, while participants (n = 21) with baseline A1C ≥7.5% had time above range (TAR, >180 mg/dL) that reduced from 31.6% to 20.8%. Auto Mode use also increased the percentage achieving combined recommendations for time at sensor glucose ranges (i.e., TIR of >70%, TBR of <4% and TAR of <25%) from 24.2% at baseline to 77.4% at study end. Total daily insulin dose reduced from 42.8 ± 19.8 to 40.7 ± 18.9 U (P = 0.013). There were no severe hypoglycemic, DKA, or serious adverse events. Conclusions: Chinese adolescents and adults, some of whom met target A1C at baseline, safely achieved significantly improved glycemia with 1 month of MiniMed 770G system use when compared to open-loop insulin delivery. ClinicalTrials.gov ID: NCT04663295.
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Affiliation(s)
- Yu Pei
- Chinese PLA General Hospital, Beijing, China
| | - Weijian Ke
- The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jing Lu
- Nanjing Drum Tower Hospital, Nanjing, China
| | - Yi Lin
- Shanghai General Hospital, Shanghai, China
| | | | | | - Yan Bi
- Nanjing Drum Tower Hospital, Nanjing, China
| | - Yanbing Li
- The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | | | | | | | | | | | - John Shin
- Medtronic, Northridge, California, USA
| | | | | | - Yiming Mu
- Chinese PLA General Hospital, Beijing, China
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Garcia-Tirado J, Colmegna P, Villard O, Diaz JL, Esquivel-Zuniga R, Koravi CLK, Barnett CL, Oliveri MC, Fuller M, Brown SA, DeBoer MD, Breton MD. Assessment of Meal Anticipation for Improving Fully Automated Insulin Delivery in Adults With Type 1 Diabetes. Diabetes Care 2023; 46:1652-1658. [PMID: 37478323 PMCID: PMC10465820 DOI: 10.2337/dc23-0119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 06/06/2023] [Indexed: 07/23/2023]
Abstract
OBJECTIVE Meals are a consistent challenge to glycemic control in type 1 diabetes (T1D). Our objective was to assess the glycemic impact of meal anticipation within a fully automated insulin delivery (AID) system among adults with T1D. RESEARCH DESIGN AND METHODS We report the results of a randomized crossover clinical trial comparing three modalities of AID systems: hybrid closed loop (HCL), full closed loop (FCL), and full closed loop with meal anticipation (FCL+). Modalities were tested during three supervised 24-h admissions, where breakfast, lunch, and dinner were consumed per participant's home schedule, at a fixed time, and with a 1.5-h delay, respectively. Primary outcome was the percent time in range 70-180 mg/dL (TIR) during the breakfast postprandial period for FCL+ versus FCL. RESULTS Thirty-five adults with T1D (age 44.5 ± 15.4 years; HbA1c 6.7 ± 0.9%; n = 23 women and n = 12 men) were randomly assigned. TIR for the 5-h period after breakfast was 75 ± 23%, 58 ± 21%, and 63 ± 19% for HCL, FCL, and FCL+, respectively, with no significant difference between FCL+ and FCL. For the 2 h before dinner, time below range (TBR) was similar for FCL and FCL+. For the 5-h period after dinner, TIR was similar for FCL+ and FCL (71 ± 34% vs. 72 ± 29%; P = 1.0), whereas TBR was reduced in FCL+ (median 0% [0-0%] vs. 0% [0-0.8%]; P = 0.03). Overall, 24-h control for HCL, FCL, and FCL+ was 86 ± 10%, 77 ± 11%, and 77 ± 12%, respectively. CONCLUSIONS Although postprandial control remained optimal with hybrid AID, both fully AID solutions offered overall TIR >70% with similar or lower exposure to hypoglycemia. Anticipation did not significantly improve postprandial control in AID systems but also did not increase hypoglycemic risk when meals were delayed.
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Affiliation(s)
- Jose Garcia-Tirado
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
- University Clinic for Diabetes, Endocrinology, Nutritional Medicine, and Metabolism, Inselspital–University Hospital Bern, University of Bern, Bern, Switzerland
| | - Patricio Colmegna
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Orianne Villard
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
- Department of Diabetes Endocrinology and Metabolism, CHU Montpellier, Montpellier, France
| | - Jenny L. Diaz
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | | | | | | | - Mary C. Oliveri
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Morgan Fuller
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Sue A. Brown
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
- Division of Endocrinology and Metabolism, Department of Medicine, University of Virginia, Charlottesville, VA
| | - Mark D. DeBoer
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
- Department of Pediatrics, University of Virginia, Charlottesville, VA
| | - Marc D. Breton
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
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Karakus KE, Akturk HK, Alonso GT, Snell-Bergeon JK, Shah VN. Association Between Diabetes Technology Use and Glycemic Outcomes in Adults With Type 1 Diabetes Over a Decade. Diabetes Care 2023; 46:1646-1651. [PMID: 37458618 DOI: 10.2337/dc23-0495] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 06/06/2023] [Indexed: 08/27/2023]
Abstract
OBJECTIVE To evaluate change in mean clinic HbA1c from 2014 to 2021 with diabetes technology use in adults with type 1 diabetes. RESEARCH DESIGN AND METHODS In this single-center study, we analyzed diabetes technology use and mean clinic HbA1c among unique adults (age ≥18 years) with type 1 diabetes (last visit of the year per patient) between 1 January 2014 and 31 December 2021 from the electronic medical record. Diabetes technology use was defined as the use of continuous glucose monitors (CGMs) without an automated insulin delivery (AID) system or an AID system. Diabetes technology use and HbA1c over time were analyzed using mixed models adjusted for age, sex, and visit year. RESULTS A total of 15,903 clinic visits over 8 years (mean 1,988 patients per year, 4,174 unique patients, 52.7% female, 80.0% Non-Hispanic White) showed significant increases in CGM and AID use (P < 0.001 for both), resulting in an increase of diabetes technology use from 26.9% in 2014 to 82.7% in 2021. These increases were associated with a lower mean clinic HbA1c (7.7-7.5%, P < 0.001) and a higher percentage of adults achieving an HbA1c <7.0% (32.3-41.7%, P < 0.001) from 2014 to 2021. The HbA1c difference between technology users and nonusers increased over time from 0.36% (95% CI 0.26-0.47%, P < 0.001) in 2014 to 0.93% (95% CI 0.80-1.06%, P < 0.001) in 2021. CONCLUSIONS Adopting diabetes technology in adults with type 1 diabetes decreased HbA1c and increased the number of people achieving an HbA1c <7.0%, supporting the current international recommendation to offer AID systems to most individuals with type 1 diabetes.
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Affiliation(s)
- Kagan E Karakus
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
- School of Medicine, Koç University, Istanbul, Turkey
| | - Halis K Akturk
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - G Todd Alonso
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Janet K Snell-Bergeon
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Viral N Shah
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
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30
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Young GM, Jacobs PG, Tyler NS, Nguyen TTP, Castle JR, Wilson LM, Branigan D, Gabo V, Guillot FH, Riddell MC, El Youssef J. Quantifying insulin-mediated and noninsulin-mediated changes in glucose dynamics during resistance exercise in type 1 diabetes. Am J Physiol Endocrinol Metab 2023; 325:E192-E206. [PMID: 37436961 PMCID: PMC10511169 DOI: 10.1152/ajpendo.00298.2022] [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] [Received: 11/10/2022] [Revised: 05/05/2023] [Accepted: 07/04/2023] [Indexed: 07/14/2023]
Abstract
Exercise can cause dangerous fluctuations in blood glucose in people living with type 1 diabetes (T1D). Aerobic exercise, for example, can cause acute hypoglycemia secondary to increased insulin-mediated and noninsulin-mediated glucose utilization. Less is known about how resistance exercise (RE) impacts glucose dynamics. Twenty-five people with T1D underwent three sessions of either moderate or high-intensity RE at three insulin infusion rates during a glucose tracer clamp. We calculated time-varying rates of endogenous glucose production (EGP) and glucose disposal (Rd) across all sessions and used linear regression and extrapolation to estimate insulin- and noninsulin-mediated components of glucose utilization. Blood glucose did not change on average during exercise. The area under the curve (AUC) for EGP increased by 1.04 mM during RE (95% CI: 0.65-1.43, P < 0.001) and decreased proportionally to insulin infusion rate (0.003 mM per percent above basal rate, 95% CI: 0.001-0.006, P = 0.003). The AUC for Rd rose by 1.26 mM during RE (95% CI: 0.41-2.10, P = 0.004) and increased proportionally with insulin infusion rate (0.04 mM per percent above basal rate, CI: 0.03-0.04, P < 0.001). No differences were observed between the moderate and high resistance groups. Noninsulin-mediated glucose utilization rose significantly during exercise before returning to baseline roughly 30-min postexercise. Insulin-mediated glucose utilization remained unchanged during exercise sessions. Circulating catecholamines and lactate rose during exercise despite relatively small changes observed in Rd. Results provide an explanation of why RE may pose a lower overall risk for hypoglycemia.NEW & NOTEWORTHY Aerobic exercise is known to cause decreases in blood glucose secondary to increased glucose utilization in people living with type 1 diabetes (T1D). However, less is known about how resistance-type exercise impacts glucose dynamics. Twenty-five participants with T1D performed in-clinic weight-bearing exercises under a glucose clamp. Mathematical modeling of infused glucose tracer allowed for quantification of the rate of hepatic glucose production as well as rates of insulin-mediated and noninsulin-mediated glucose uptake experienced during resistance exercise.
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Affiliation(s)
- Gavin M Young
- Artificial Intelligence for Medical Systems (AIMS) Laboratory, Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, United States
| | - Peter G Jacobs
- Artificial Intelligence for Medical Systems (AIMS) Laboratory, Department of Biomedical Engineering, Oregon Health & Science University, Portland, Oregon, United States
| | - Nichole S Tyler
- School of Medicine, Oregon Health & Science University, Portland, Oregon, United States
| | - Thanh-Tin P Nguyen
- School of Medicine, Oregon Health & Science University, Portland, Oregon, United States
| | - Jessica R Castle
- Division of Endocrinology, Harold Schnitzer Diabetes Health Center, Oregon Health & Science University, Portland, Oregon, United States
| | - Leah M Wilson
- Division of Endocrinology, Harold Schnitzer Diabetes Health Center, Oregon Health & Science University, Portland, Oregon, United States
| | - Deborah Branigan
- Division of Endocrinology, Harold Schnitzer Diabetes Health Center, Oregon Health & Science University, Portland, Oregon, United States
| | - Virginia Gabo
- School of Medicine, Oregon Health & Science University, Portland, Oregon, United States
| | - Florian H Guillot
- School of Medicine, Oregon Health & Science University, Portland, Oregon, United States
| | - Michael C Riddell
- School of Kinesiology and Health Science, York University, Toronto, Ontario, Canada
| | - Joseph El Youssef
- Division of Endocrinology, Harold Schnitzer Diabetes Health Center, Oregon Health & Science University, Portland, Oregon, United States
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31
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Jacobs PG, Resalat N, Hilts W, Young GM, Leitschuh J, Pinsonault J, El Youssef J, Branigan D, Gabo V, Eom J, Ramsey K, Dodier R, Mosquera-Lopez C, Wilson LM, Castle JR. Integrating metabolic expenditure information from wearable fitness sensors into an AI-augmented automated insulin delivery system: a randomised clinical trial. Lancet Digit Health 2023; 5:e607-e617. [PMID: 37543512 PMCID: PMC10557965 DOI: 10.1016/s2589-7500(23)00112-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 03/21/2023] [Accepted: 06/06/2023] [Indexed: 08/07/2023]
Abstract
BACKGROUND Exercise can rapidly drop glucose in people with type 1 diabetes. Ubiquitous wearable fitness sensors are not integrated into automated insulin delivery (AID) systems. We hypothesised that an AID can automate insulin adjustments using real-time wearable fitness data to reduce hypoglycaemia during exercise and free-living conditions compared with an AID not automating use of fitness data. METHODS Our study population comprised of individuals (aged 21-50 years) with type 1 diabetes from from the Harold Schnitzer Diabetes Health Center clinic at Oregon Health and Science University, OR, USA, who were enrolled into a 76 h single-centre, two-arm randomised (4-block randomisation), non-blinded crossover study to use (1) an AID that detects exercise, prompts the user, and shuts off insulin during exercise using an exercise-aware adaptive proportional derivative (exAPD) algorithm or (2) an AID that automates insulin adjustments using fitness data in real-time through an exercise-aware model predictive control (exMPC) algorithm. Both algorithms ran on iPancreas comprising commercial glucose sensors, insulin pumps, and smartwatches. Participants executed 1 week run-in on usual therapy followed by exAPD or exMPC for one 12 h primary in-clinic session involving meals, exercise, and activities of daily living, and 2 free-living out-patient days. Primary outcome was time below range (<3·9 mmol/L) during the primary in-clinic session. Secondary outcome measures included mean glucose and time in range (3·9-10 mmol/L). This trial is registered with ClinicalTrials.gov, NCT04771403. FINDINGS Between April 13, 2021, and Oct 3, 2022, 27 participants (18 females) were enrolled into the study. There was no significant difference between exMPC (n=24) versus exAPD (n=22) in time below range (mean [SD] 1·3% [2·9] vs 2·5% [7·0]) or time in range (63·2% [23·9] vs 59·4% [23·1]) during the primary in-clinic session. In the 2 h period after start of in-clinic exercise, exMPC had significantly lower mean glucose (7·3 [1·6] vs 8·0 [1·7] mmol/L, p=0·023) and comparable time below range (1·4% [4·2] vs 4·9% [14·4]). Across the 76 h study, both algorithms achieved clinical time in range targets (71·2% [16] and 75·5% [11]) and time below range (1·0% [1·2] and 1·3% [2·2]), significantly lower than run-in period (2·4% [2·4], p=0·0004 vs exMPC; p=0·012 vs exAPD). No adverse events occurred. INTERPRETATION AIDs can integrate exercise data from smartwatches to inform insulin dosing and limit hypoglycaemia while improving glucose outcomes. Future AID systems that integrate exercise metrics from wearable fitness sensors may help people living with type 1 diabetes exercise safely by limiting hypoglycaemia. FUNDING JDRF Foundation and the Leona M and Harry B Helmsley Charitable Trust, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases.
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Affiliation(s)
- Peter G Jacobs
- Artificial Intelligence for Medical Systems Lab, Department of Biomedical Engineering, Center for Health and Healing, Oregon Health and Science University, Portland, OR, USA.
| | - Navid Resalat
- Artificial Intelligence for Medical Systems Lab, Department of Biomedical Engineering, Center for Health and Healing, Oregon Health and Science University, Portland, OR, USA
| | - Wade Hilts
- Artificial Intelligence for Medical Systems Lab, Department of Biomedical Engineering, Center for Health and Healing, Oregon Health and Science University, Portland, OR, USA
| | - Gavin M Young
- Artificial Intelligence for Medical Systems Lab, Department of Biomedical Engineering, Center for Health and Healing, Oregon Health and Science University, Portland, OR, USA
| | - Joseph Leitschuh
- Artificial Intelligence for Medical Systems Lab, Department of Biomedical Engineering, Center for Health and Healing, Oregon Health and Science University, Portland, OR, USA
| | - Joseph Pinsonault
- Artificial Intelligence for Medical Systems Lab, Department of Biomedical Engineering, Center for Health and Healing, Oregon Health and Science University, Portland, OR, USA
| | - Joseph El Youssef
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, OR, USA
| | - Deborah Branigan
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, OR, USA
| | - Virginia Gabo
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, OR, USA
| | - Jae Eom
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, OR, USA
| | - Katrina Ramsey
- Oregon Clinical and Translational Research Institute Biostatistics and Design Program, Oregon Health and Science University, Portland, OR, USA
| | - Robert Dodier
- Artificial Intelligence for Medical Systems Lab, Department of Biomedical Engineering, Center for Health and Healing, Oregon Health and Science University, Portland, OR, USA
| | - Clara Mosquera-Lopez
- Artificial Intelligence for Medical Systems Lab, Department of Biomedical Engineering, Center for Health and Healing, Oregon Health and Science University, Portland, OR, USA
| | - Leah M Wilson
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, OR, USA
| | - Jessica R Castle
- Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland, OR, USA
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Grancini V, Alicandro G, Porcaro LL, Zazzeron L, Gramegna A, Morlacchi LC, Rossetti V, Gaglio A, Resi V, Daccò V, Blasi F, Orsi E. Effects of insulin therapy optimization with sensor augmented pumps on glycemic control and body composition in people with cystic fibrosis-related diabetes. Front Endocrinol (Lausanne) 2023; 14:1228153. [PMID: 37720540 PMCID: PMC10501717 DOI: 10.3389/fendo.2023.1228153] [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: 05/24/2023] [Accepted: 08/11/2023] [Indexed: 09/19/2023] Open
Abstract
Objective Cystic fibrosis (CF)-related diabetes (CFRD) resulting from partial-to-complete insulin deficiency occurs in 40-50% of adults with CF. In people with CFRD, poor glycemic control leads to a catabolic state that may aggravate CF-induced nutritional impairment and loss of muscle mass. Sensor augmented pump (SAP) therapy may improve glycemic control as compared to multiple daily injection (MDI) therapy. Research design and methods This non-randomized clinical trial was aimed at evaluating the effects of insulin therapy optimization with SAP therapy, combined with a structured educational program, on glycemic control and body composition in individuals with insulin-requiring CFRD. Of 46 participants who were offered to switch from MDI to SAP therapy, 20 accepted and 26 continued the MDI therapy. Baseline demographic and clinical characteristics were balanced between groups using a propensity score-based overlap weighting procedure and weighted mixed-effects regression models were used to estimate changes in study outcomes. Results After 24 months changes in HbA1c were: -1.1% (-12.1 mmol/mol) (95% CI: -1.5; -0.8) and -0.1% (-1 mmol/mol) (95% CI: -0.5; 0.3) in the SAP and MDI therapy group, respectively, with a between-group difference of -1.0 (-10 mmol/mol) (-1.5; -0.5). SAP therapy was also associated with a decrease in mean glucose (between group difference: -32 mg/dL; 95% CI: -44; -20) and an increase in TIR (between group difference: 19.3%; 95% CI 13.9; 24.7) and in fat-free mass (between group difference: +5.5 Kg, 95% CI: 3.2; 7.8). Conclusion Therapy optimization with SAP led to a significant improvement in glycemic control, which was associated with an increase in fat-free mass.
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Affiliation(s)
- V. Grancini
- Diabetes Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - G. Alicandro
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
- Pediatrics, Gastroenterology, Hepatology, Pediatric Transplantation and Cystic Fibrosis Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - L. L. Porcaro
- Diabetes Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - L. Zazzeron
- Pediatrics, Gastroenterology, Hepatology, Pediatric Transplantation and Cystic Fibrosis Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - A. Gramegna
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
- Respiratory Unit and Cystic Fibrosis Adult Center, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - L. C. Morlacchi
- Respiratory Unit and Cystic Fibrosis Adult Center, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - V. Rossetti
- Respiratory Unit and Cystic Fibrosis Adult Center, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - A. Gaglio
- Diabetes Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - V. Resi
- Diabetes Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - V. Daccò
- Pediatrics, Gastroenterology, Hepatology, Pediatric Transplantation and Cystic Fibrosis Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - F. Blasi
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
- Respiratory Unit and Cystic Fibrosis Adult Center, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - E. Orsi
- Diabetes Unit, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, Milan, Italy
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Levy CJ, Raghinaru D, Kudva YC, Pandit K, Blevins T, Casaubon L, Desjardins D, Levister CM, O’Malley G, Reid C, Lum J, Kollman C, Beck RW. Beneficial Effects of Control-IQ Automated Insulin Delivery in Basal-Bolus and Basal-Only Insulin Users With Type 2 Diabetes. Clin Diabetes 2023; 42:116-124. [PMID: 38230336 PMCID: PMC10788662 DOI: 10.2337/cd23-0025] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/18/2024]
Abstract
The t:slim X2 insulin pump with Control-IQ technology (Control-IQ) advanced hybrid closed-loop automated insulin delivery system was evaluated in this prospective single-arm trial. Thirty adults with type 2 diabetes using the Control-IQ system showed substantial glycemic improvement with no increase in hypoglycemia. Mean time in range (70-180 mg/dL) improved 15%, representing an increase of 3.6 hours/day, and mean glucose decreased by 22 mg/dL.
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Affiliation(s)
- Carol J. Levy
- Division of Endocrinology, Icahn School of Medicine at Mount Sinai, New York, NY
| | | | - Yogish C. Kudva
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Keta Pandit
- Texas Diabetes and Endocrinology, Austin, TX
| | | | | | - Donna Desjardins
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Camilla M. Levister
- Division of Endocrinology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Grenye O’Malley
- Division of Endocrinology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Corey Reid
- Division of Endocrinology, Diabetes, Metabolism and Nutrition, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - John Lum
- Jaeb Center for Health Research, Tampa, FL
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Conway RB, Gerard Gonzalez A, Shah VN, Geno Rasmussen C, Akturk HK, Pyle L, Forlenza G, Alonso GT, Snell-Bergeon J. Racial Disparities in Diabetes Technology Adoption and Their Association with HbA1c and Diabetic Ketoacidosis. Diabetes Metab Syndr Obes 2023; 16:2295-2310. [PMID: 37551339 PMCID: PMC10404403 DOI: 10.2147/dmso.s416192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 07/18/2023] [Indexed: 08/09/2023] Open
Abstract
Aim Poorer glycemic control and higher diabetic ketoacidosis (DKA) rates are seen in racial/ethnic minorities with type 1 diabetes (T1D). Use of diabetes technologies such as continuous glucose monitors (CGM), continuous subcutaneous insulin infusion (CSII) and automated insulin delivery (AID) systems has been shown to improve glycemic control and reduce DKA risk. We examined race/ethnicity differences in diabetes technology use and their relationship with HbA1c and DKA. Methods Data from patients aged ≥12 years with T1D for ≥1 year, receiving care from a single diabetes center, were examined. Patients were classified as Non-Hispanic White (n=3945), Non-Hispanic Black (Black, n=161), Hispanic (n=719), and Multiracial/Other (n=714). General linear models and logistic regression were used. Results Black (OR=0.22, 0.15-0.32) and Hispanic (OR=0.37, 0.30-0.45) patients were less likely to use diabetes technology. This disparity was greater in the pediatric population (p-interaction=0.06). Technology use associated with lower HbA1c in each race/ethnic group. Among technology users, AID use associated with lower HbA1c compared to CGM and/or CSII (HbA1c of 8.4% vs 9.2%, respectively), with the greatest difference observed for Black adult AID users. CSII use associated with a lower odds of DKA in the past year (OR=0.73, 0.54-0.99), a relationship that did not vary by race (p-interaction =0.69); this inverse association with DKA was not observed for CGM or AID. Conclusion Disparities in diabetes technology use, DKA, and glycemic control were apparent among Black and Hispanic patients with T1D. Differences in technology use ameliorated but did not fully account for disparities in HbA1c or DKA.
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Affiliation(s)
- Rebecca Baqiyyah Conway
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - Viral N Shah
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - Halis Kaan Akturk
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Laura Pyle
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Gregory Forlenza
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Guy Todd Alonso
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Janet Snell-Bergeon
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
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Veríssimo D, Vinhais J, Ivo C, Martins AC, Nunes E Silva J, Passos D, Lopes L, Jácome de Castro J, Marcelino M. Continuous Glucose Monitoring vs. Capillary Blood Glucose in Hospitalized Type 2 Diabetes Patients. Cureus 2023; 15:e43832. [PMID: 37736430 PMCID: PMC10509631 DOI: 10.7759/cureus.43832] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/20/2023] [Indexed: 09/23/2023] Open
Abstract
INTRODUCTION The emergence of continuous glucose monitoring devices revolutionized the monitoring of diabetes, allowing real-time measurement of interstitial glucose levels. These devices are especially important for people with diabetes treated with insulin therapy and have been extensively studied in outpatient settings. In hospitalized patients, studies using continuous glucose monitoring have focused mainly on evaluating its accuracy and feasibility, but the results were unclear on whether continuous glucose monitoring was superior to capillary blood glucose in improving glycemic control and further research is needed to support the use of these devices in hospitalized patients with diabetes. OBJECTIVE The primary endpoint of this study was to assess the increase in time-in-range (glycemic readings between 100-180 mg/dL) in hospitalized patients with continuous glucose monitoring, compared to capillary blood glucose. The secondary endpoints included the assessment of reductions in hypoglycemia incidence, mean glucose levels, and glucose coefficient of variation. Additionally, we assessed the intervention's impact on reducing the length of hospital stay, mortality rates, and incidence of inpatient infections. RESEARCH DESIGN AND METHODS This was a retrospective, cohort study of 60 hospitalized patients with type 2 diabetes, divided into two groups of 30 individuals each: an intervention group monitored through continuous glucose monitoring and a control group using capillary blood glucose. RESULTS Both groups were comparable in terms of demographic and clinical characteristics. Continuous glucose monitoring users had a higher number of readings per day (six vs. four, p < 0.001), in-range readings (53.5% vs. 35%, p = 0.027), fewer above-range readings (25.5% vs. 56.5%, p = 0.003), particularly above 250 mg/dL (5% vs. 27.5%, p = 0.001), with no difference in the percentage of hypoglycemia occurence (1% vs. 0%, p = 0.107). Lower mean glucose (161.9 mg/dL vs. 206.5 mg/dL, p < 0.001) was also observed in this group. No difference was observed in mortality, length of stay, or in infection rate (p = 1.000, p = 0.455, and p = 0.606, respectively). CONCLUSIONS This retrospective study supports the use of continuous glucose monitoring in optimizing glycemic control in hospitalized patients with type 2 diabetes on intensive insulin therapy. These findings suggest that continuous glucose monitoring can improve time-in-range and prevent hyperglycemia.
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Affiliation(s)
- David Veríssimo
- Department of Endocrinology, Hospital das Forças Armadas, Lisbon, PRT
| | - Joana Vinhais
- Department of Endocrinology, Hospital das Forças Armadas, Lisbon, PRT
| | - Catarina Ivo
- Department of Endocrinology, Hospital das Forças Armadas, Lisbon, PRT
| | | | | | - Dolores Passos
- Department of Endocrinology, Hospital das Forças Armadas, Lisbon, PRT
| | - Luís Lopes
- Department of Endocrinology, Hospital das Forças Armadas, Lisbon, PRT
| | | | - Mafalda Marcelino
- Department of Endocrinology, Hospital das Forças Armadas, Lisbon, PRT
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Huang ES, Sinclair A, Conlin PR, Cukierman-Yaffe T, Hirsch IB, Huisingh-Scheetz M, Kahkoska AR, Laffel L, Lee AK, Lee S, Lipska K, Meneilly G, Pandya N, Peek ME, Peters A, Pratley RE, Sherifali D, Toschi E, Umpierrez G, Weinstock RS, Munshi M. The Growing Role of Technology in the Care of Older Adults With Diabetes. Diabetes Care 2023; 46:1455-1463. [PMID: 37471606 PMCID: PMC10369127 DOI: 10.2337/dci23-0021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 05/24/2023] [Indexed: 07/22/2023]
Abstract
The integration of technologies such as continuous glucose monitors, insulin pumps, and smart pens into diabetes management has the potential to support the transformation of health care services that provide a higher quality of diabetes care, lower costs and administrative burdens, and greater empowerment for people with diabetes and their caregivers. Among people with diabetes, older adults are a distinct subpopulation in terms of their clinical heterogeneity, care priorities, and technology integration. The scientific evidence and clinical experience with these technologies among older adults are growing but are still modest. In this review, we describe the current knowledge regarding the impact of technology in older adults with diabetes, identify major barriers to the use of existing and emerging technologies, describe areas of care that could be optimized by technology, and identify areas for future research to fulfill the potential promise of evidence-based technology integrated into care for this important population.
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Affiliation(s)
| | | | - Paul R. Conlin
- Harvard Medical School, Boston, MA
- Veteran Affairs Boston Healthcare System, Boston, MA
| | - Tali Cukierman-Yaffe
- Division of Endocrinology, Diabetes, and Metabolism, Ramat Gan, Israel
- Sheba Medical Centre, Ramat Gan, Israel
- Epidemiology Department, Sackler Faculty of Medicine, Herczeg Institute on Aging, Tel Aviv University, Tel Aviv, Israel
| | | | | | | | | | | | - Sei Lee
- University of California San Francisco, San Francisco, CA
| | | | - Graydon Meneilly
- University of British Columbia, Vancouver, British Columbia, Canada
| | - Naushira Pandya
- Department of Geriatrics, Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Ft. Lauderdale, FL
| | | | - Anne Peters
- University of Southern California, Los Angeles, CA
| | - Richard E. Pratley
- AdventHealth Diabetes Institute, AdventHealth Translational Research Institute, AdventHealth, Orlando, FL
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37
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Urbano F, Farella I, Brunetti G, Faienza MF. Pediatric Type 1 Diabetes: Mechanisms and Impact of Technologies on Comorbidities and Life Expectancy. Int J Mol Sci 2023; 24:11980. [PMID: 37569354 PMCID: PMC10418611 DOI: 10.3390/ijms241511980] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/20/2023] [Accepted: 07/24/2023] [Indexed: 08/13/2023] Open
Abstract
Type 1 diabetes (T1D) is one of the most common chronic diseases in childhood, with a progressively increasing incidence. T1D management requires lifelong insulin treatment and ongoing health care support. The main goal of treatment is to maintain blood glucose levels as close to the physiological range as possible, particularly to avoid blood glucose fluctuations, which have been linked to morbidity and mortality in patients with T1D. Indeed, the guidelines of the International Society for Pediatric and Adolescent Diabetes (ISPAD) recommend a glycated hemoglobin (HbA1c) level < 53 mmol/mol (<7.0%) for young people with T1D to avoid comorbidities. Moreover, diabetic disease strongly influences the quality of life of young patients who must undergo continuous monitoring of glycemic values and the administration of subcutaneous insulin. In recent decades, the development of automated insulin delivery (AID) systems improved the metabolic control and the quality of life of T1D patients. Continuous subcutaneous insulin infusion (CSII) combined with continuous glucose monitoring (CGM) devices connected to smartphones represent a good therapeutic option, especially in young children. In this literature review, we revised the mechanisms of the currently available technologies for T1D in pediatric age and explored their effect on short- and long-term diabetes-related comorbidities, quality of life, and life expectation.
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Affiliation(s)
- Flavia Urbano
- Giovanni XXIII Pediatric Hospital, 70126 Bari, Italy;
| | - Ilaria Farella
- Clinica Medica “A. Murri”, University of Bari “Aldo Moro”, 70124 Bari, Italy;
| | - Giacomina Brunetti
- Department of Biosciences, Biotechnologies, and Environment, University of Bari “Aldo Moro”, 70125 Bari, Italy
| | - Maria Felicia Faienza
- Department of Precision and Regenerative Medicine and Ionian Area, University of Bari “Aldo Moro”, 70124 Bari, Italy;
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Russell-Jones D, Bawlchhim Z. Discovery of insulin 100 years on. Postgrad Med J 2023; 99:661-668. [PMID: 37389580 DOI: 10.1136/postgradmedj-2022-141651] [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: 03/14/2022] [Accepted: 04/25/2022] [Indexed: 11/04/2022]
Abstract
The discovery of insulin 100 years ago ranks among the greatest medical achievements ever. This sparked a revolution of scientific discovery and therapeutic intervention to treat people suffering with diabetes. A light was shone for other areas of medicine to illuminate what was possible with detailed scientific endeavour. There followed a range of firsts leading to the current time in which we now know more about this peptide hormone than almost any other protein in existence. This has allowed therapeutic advancement from a positon of knowledge leading to stunning innovation. This innovation is likely to lead to more physiological insulin replacement reducing the disease burden to individuals and society as whole.
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Affiliation(s)
- David Russell-Jones
- CEDAR, Royal Surrey County Hospital, Guildford, UK
- Diabetes & Endocrinology, University of Surrey, Guildford, UK
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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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40
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Singh A, Afshan N, Singh A, Singh SK, Yadav S, Kumar M, Sarma DK, Verma V. Recent trends and advances in type 1 diabetes therapeutics: A comprehensive review. Eur J Cell Biol 2023; 102:151329. [PMID: 37295265 DOI: 10.1016/j.ejcb.2023.151329] [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: 04/05/2023] [Revised: 05/12/2023] [Accepted: 06/03/2023] [Indexed: 06/12/2023] Open
Abstract
Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by the destruction of pancreatic β-cells, leading to insulin deficiency. Insulin replacement therapy is the current standard of care for T1D, but it has significant limitations. However, stem cell-based replacement therapy has the potential to restore β-cell function and achieve glycaemic control eradicating the necessity for drugs or injecting insulin externally. While significant progress has been made in preclinical studies, the clinical translation of stem cell therapy for T1D is still in its early stages. In continuation, further research is essentially required to determine the safety and efficacy of stem cell therapies and to develop strategies to prevent immune rejection of stem cell-derived β-cells. The current review highlights the current state of cellular therapies for T1D including, different types of stem cell therapies, gene therapy, immunotherapy, artificial pancreas, and cell encapsulation being investigated, and their potential for clinical translation.
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Affiliation(s)
- Akash Singh
- Stem Cell Research Centre, Department of Haematology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India
| | - Noor Afshan
- Stem Cell Research Centre, Department of Haematology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India
| | - Anshuman Singh
- Stem Cell Research Centre, Department of Haematology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India
| | - Suraj Kumar Singh
- Stem Cell Research Centre, Department of Haematology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India
| | - Sudhanshu Yadav
- Stem Cell Research Centre, Department of Haematology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India
| | - Manoj Kumar
- ICMR-National Institute for Research in Environmental Health, Bhopal, India
| | | | - Vinod Verma
- Stem Cell Research Centre, Department of Haematology, Sanjay Gandhi Post Graduate Institute of Medical Sciences, Lucknow, India.
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Vargas E, Nandhakumar P, Ding S, Saha T, Wang J. Insulin detection in diabetes mellitus: challenges and new prospects. Nat Rev Endocrinol 2023:10.1038/s41574-023-00842-3. [PMID: 37217746 DOI: 10.1038/s41574-023-00842-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/19/2023] [Indexed: 05/24/2023]
Abstract
Tremendous progress has been made towards achieving tight glycaemic control in individuals with diabetes mellitus through the use of frequent or continuous glucose measurements. However, in patients who require insulin, accurate dosing must consider multiple factors that affect insulin sensitivity and modulate insulin bolus needs. Accordingly, an urgent need exists for frequent and real-time insulin measurements to closely track the dynamic blood concentration of insulin during insulin therapy and guide optimal insulin dosing. Nevertheless, traditional centralized insulin testing cannot offer timely measurements, which are essential to achieving this goal. This Perspective discusses the advances and challenges in moving insulin assays from traditional laboratory-based assays to frequent and continuous measurements in decentralized (point-of-care and home) settings. Technologies that hold promise for insulin testing using disposable test strips, mobile systems and wearable real-time insulin-sensing devices are discussed. We also consider future prospects for continuous insulin monitoring and for fully integrated multisensor-guided closed-loop artificial pancreas systems.
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Affiliation(s)
- Eva Vargas
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Ponnusamy Nandhakumar
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Shichao Ding
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Tamoghna Saha
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Joseph Wang
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA.
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42
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Beck RW, Kanapka LG, Breton MD, Brown SA, Wadwa RP, Buckingham BA, Kollman C, Kovatchev B. A Meta-Analysis of Randomized Trial Outcomes for the t:slim X2 Insulin Pump with Control-IQ Technology in Youth and Adults from Age 2 to 72. Diabetes Technol Ther 2023; 25:329-342. [PMID: 37067353 PMCID: PMC10171957 DOI: 10.1089/dia.2022.0558] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Objective: To evaluate the effect of hybrid-closed loop Control-IQ technology (Control-IQ) in randomized controlled trials (RCTs) in subgroups based on baseline characteristics such as race/ethnicity, socioeconomic status (SES), prestudy insulin delivery modality (pump or multiple daily injections), and baseline glycemic control. Methods: Data were pooled and analyzed from 3 RCTs comparing Control-IQ to a Control group using continuous glucose monitoring in 369 participants with type 1 diabetes (T1D) from age 2 to 72 years old. Results: Time in range 70-180 mg/dL (TIR) in the Control-IQ group (n = 256) increased from 57% ± 17% at baseline to 70% ± 11% during follow-up, and in the Control group (n = 113) was 56% ± 15% and 57% ± 14%, respectively (adjusted treatment group difference = 11.5%, 95% confidence interval +9.7% to +13.2%, P < 0.001), an increase of 2.8 h/day on average. Significant reductions in mean glucose, hyperglycemia metrics, hypoglycemic metrics, and HbA1c were also observed. A statistically similar beneficial treatment effect on time in range 70-180 mg/dL was observed across the full age range irrespective of race-ethnicity, household income, prestudy continuous glucose monitor use, or prestudy insulin delivery method. Participants with the highest baseline HbA1c levels showed the greatest improvements in TIR and HbA1c. Conclusion: This pooled analysis of Control-IQ RCTs demonstrates the beneficial effect of Control-IQ in T1D across a broad spectrum of participant characteristics, including racial-ethnic minority, lower SES, lack of prestudy insulin pump experience, and high HbA1c levels. The greatest benefit was observed in participants with the worst baseline glycemic control in whom the auto-bolus feature of the Control-IQ algorithm appears to have substantial impact. Since no subgroups were identified that did not benefit from Control-IQ, hybrid-closed loop technology should be strongly considered for all youth and adults with T1D. Clinical Trials Registry: clinicaltrials.gov; NCT03563313, NCT03844789, and NCT04796779.
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Affiliation(s)
- Roy W. Beck
- JAEB Center for Health Research, Tampa, Florida, USA
| | | | - Marc D. Breton
- University of Virginia Center for Diabetes Technology, Charlottesville, Virginia, USA
| | - Sue A. Brown
- University of Virginia Center for Diabetes Technology, Charlottesville, Virginia, USA
| | - R. Paul Wadwa
- Barbara Davis Center for Diabetes, University of Colorado, Anschutz Medical Campus, Aurora, Colorado, USA
| | - Bruce A. Buckingham
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA
| | - Craig Kollman
- JAEB Center for Health Research, Tampa, Florida, USA
| | - Boris Kovatchev
- University of Virginia Center for Diabetes Technology, Charlottesville, Virginia, USA
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Zahid M, Dowlatshahi S, Kansara AH, Sadhu AR. The Evolution of Diabetes Technology - Options Towards Personalized Care. Endocr Pract 2023:S1530-891X(23)00387-7. [PMID: 37100350 DOI: 10.1016/j.eprac.2023.04.007] [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: 10/01/2022] [Revised: 04/12/2023] [Accepted: 04/18/2023] [Indexed: 04/28/2023]
Abstract
Advances in diabetes technology, especially in the last few decades, have transformed our ability to deliver care to persons with diabetes (PWD). Developments in glucose monitoring, especially continuous glucose monitoring systems (CGM), have revolutionized diabetes care and empowered our patients to manage their disease. CGM has also played an integral role in advancing automated insulin delivery systems. Currently available and upcoming advanced hybrid-closed loop systems aim to decrease patient involvement and are approaching the functionality of a fully automated artificial pancreas. Other advances, such as smart insulin pens and daily patch pumps, offer more options for patients and require less complicated and costly technology. Evidence to support the role of diabetes technology is growing, and PWD and clinicians must choose the right type of technology with a personalized strategy to manage diabetes effectively. Here, we review currently available diabetes technologies, summarize their individual features and highlight key patient factors to consider when creating a personalized treatment plan. We also address current challenges and barriers to the adoption of diabetes technologies.
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Affiliation(s)
- Maleeha Zahid
- Fellow, Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, Houston Methodist Hospital, Houston, Texas
| | - Samaneh Dowlatshahi
- Division of Endocrinology, Diabetes & Metabolism, Assistant Clinical Professor, Weill Cornell Medical College, Assistant Professor of Clinical Medicine, Houston Methodist Academic Institute, Houston Methodist Hospital, Houston, Texas
| | - Abhishek H Kansara
- Division of Endocrinology, Diabetes & Metabolism, Assistant Professor of Clinical Medicine, Weill Cornell Medical College, Assistant Professor of Clinical Medicine, Houston Methodist Academic Institute, Adjunct Assistant Professor, Texas A&M University College of Medicine, Houston Methodist Hospital, Houston, Texas
| | - Archana R Sadhu
- System Director, Diabetes Program at Houston Methodist, Medical Director, Pancreas Transplantation and Transplant Endocrinology, Houston Methodist J.C. Walter Jr. Transplant Center, Assistant Clinical Professor, Weill Cornell Medical College, Adjunct Assistant Professor, Texas A&M Health Sciences.
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Almurashi AM, Rodriguez E, Garg SK. Emerging Diabetes Technologies: Continuous Glucose Monitors/Artificial Pancreases. J Indian Inst Sci 2023; 103:1-26. [PMID: 37362851 PMCID: PMC10043869 DOI: 10.1007/s41745-022-00348-3] [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: 10/18/2022] [Accepted: 11/04/2022] [Indexed: 03/30/2023]
Abstract
Over the past decade there have been many advances in diabetes technologies, such as continuous glucose monitors (CGM s), insulin-delivery devices, and hybrid closed loop systems . Now most CGMs (Medtronic-Guardian, Dexcom-G6, and Abbott-Libre-2) have MARD values of < 10%, in contrast to two decades ago when the MARD used to be > 20%. In addition, the majority of the new CGMs do not require calibrations, and the latest CGMs last for 10-14 days. An implantable 6-months CGM by Eversense-3 is now approved in the USA and Europe. Recently, the FDA approved Libre 3 which provides real-time glucose values every minute. Even though it is approved as an iCGM it is not interoperable with automatic-insulin-delivery (AID) systems. The newer CGMs that are likely to be launched in the next few months in the USA include the 10-11 days Dexcom G7 (60% smaller than the existing G6), and the 7-days Medtronic Guardian 4. Most of the newer CGM have several features like automatic initialization, easy insertion, predictive alarms, and alerts. It has also been noticed that an arm insertion site might have better accuracy than abdomen or other sites, like the buttock for kids. Lag time between YSI and different sensors have been reported differently, sometimes it is down to 2-3 min; however, in many instances, it is still 15-20 min, especially when the rate of change of glucose is > 2 mg/min. We believe that in the next decade there will be a significant increase in the number of people who use CGM for their day-to-day diabetes care.
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Affiliation(s)
- Abdulhalim M. Almurashi
- Barbara Davis Center for Diabetes, University of Colorado Denver, 1775 Aurora Ct, Rm 1324, Aurora, CO 80045 USA
- Madinah Health Cluster, Madinah, Saudi Arabia
| | - Erika Rodriguez
- Barbara Davis Center for Diabetes, University of Colorado Denver, 1775 Aurora Ct, Rm 1324, Aurora, CO 80045 USA
| | - Satish K. Garg
- Barbara Davis Center for Diabetes, University of Colorado Denver, 1775 Aurora Ct, Rm 1324, Aurora, CO 80045 USA
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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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Phillip M, Nimri R, Bergenstal RM, Barnard-Kelly K, Danne T, Hovorka R, Kovatchev BP, Messer LH, Parkin CG, Ambler-Osborn L, Amiel SA, Bally L, Beck RW, Biester S, Biester T, Blanchette JE, Bosi E, Boughton CK, Breton MD, Brown SA, Buckingham BA, Cai A, Carlson AL, Castle JR, Choudhary P, Close KL, Cobelli C, Criego AB, Davis E, de Beaufort C, de Bock MI, DeSalvo DJ, DeVries JH, Dovc K, Doyle FJ, Ekhlaspour L, Shvalb NF, Forlenza GP, Gallen G, Garg SK, Gershenoff DC, Gonder-Frederick LA, Haidar A, Hartnell S, Heinemann L, Heller S, Hirsch IB, Hood KK, Isaacs D, Klonoff DC, Kordonouri O, Kowalski A, Laffel L, Lawton J, Lal RA, Leelarathna L, Maahs DM, Murphy HR, Nørgaard K, O’Neal D, Oser S, Oser T, Renard E, Riddell MC, Rodbard D, Russell SJ, Schatz DA, Shah VN, Sherr JL, Simonson GD, Wadwa RP, Ward C, Weinzimer SA, Wilmot EG, Battelino T. Consensus Recommendations for the Use of Automated Insulin Delivery Technologies in Clinical Practice. Endocr Rev 2023; 44:254-280. [PMID: 36066457 PMCID: PMC9985411 DOI: 10.1210/endrev/bnac022] [Citation(s) in RCA: 100] [Impact Index Per Article: 100.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 07/22/2022] [Indexed: 02/06/2023]
Abstract
The significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers, and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past 6 years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage.
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Affiliation(s)
- Moshe Phillip
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children’s Medical Center of Israel, 49202 Petah Tikva, Israel
- Sacker Faculty of Medicine, Tel-Aviv University, 39040 Tel-Aviv, Israel
| | - Revital Nimri
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children’s Medical Center of Israel, 49202 Petah Tikva, Israel
- Sacker Faculty of Medicine, Tel-Aviv University, 39040 Tel-Aviv, Israel
| | - Richard M Bergenstal
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | | | - Thomas Danne
- AUF DER BULT, Diabetes-Center for Children and Adolescents, Endocrinology and General Paediatrics, Hannover, Germany
| | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Boris P Kovatchev
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
| | - Laurel H Messer
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | | | | | | | - Lia Bally
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Roy W Beck
- Jaeb Center for Health Research Foundation, Inc., Tampa, FL 33647, USA
| | - Sarah Biester
- AUF DER BULT, Diabetes-Center for Children and Adolescents, Endocrinology and General Paediatrics, Hannover, Germany
| | - Torben Biester
- AUF DER BULT, Diabetes-Center for Children and Adolescents, Endocrinology and General Paediatrics, Hannover, Germany
| | - Julia E Blanchette
- College of Nursing, University of Utah, Salt Lake City, UT 84112, USA
- Center for Diabetes and Obesity, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA
| | - Emanuele Bosi
- Diabetes Research Institute, IRCCS San Raffaele Hospital and San Raffaele Vita Salute University, Milan, Italy
| | - Charlotte K Boughton
- Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, University of Cambridge Metabolic Research Laboratories, Cambridge, UK
| | - Marc D Breton
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
| | - Sue A Brown
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
- Division of Endocrinology, University of Virginia, Charlottesville, VA 22903, USA
| | - Bruce A Buckingham
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, CA 94304, USA
| | - Albert Cai
- The diaTribe Foundation/Close Concerns, San Diego, CA 94117, USA
| | - Anders L Carlson
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | - Jessica R Castle
- Harold Schnitzer Diabetes Health Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Pratik Choudhary
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Kelly L Close
- The diaTribe Foundation/Close Concerns, San Diego, CA 94117, USA
| | - Claudio Cobelli
- Department of Woman and Child’s Health, University of Padova, Padova, Italy
| | - Amy B Criego
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | - Elizabeth Davis
- Telethon Kids Institute, University of Western Australia, Perth Children’s Hospital, Perth, Australia
| | - Carine de Beaufort
- Diabetes & Endocrine Care Clinique Pédiatrique DECCP/Centre Hospitalier Luxembourg, and Faculty of Sciences, Technology and Medicine, University of Luxembourg, Esch sur Alzette, GD Luxembourg/Department of Paediatrics, UZ-VUB, Brussels, Belgium
| | - Martin I de Bock
- Department of Paediatrics, University of Otago, Christchurch, New Zealand
| | - Daniel J DeSalvo
- Division of Pediatric Diabetes and Endocrinology, Baylor College of Medicine, Texas Children’s Hospital, Houston, TX 77598, USA
| | - J Hans DeVries
- Amsterdam UMC, University of Amsterdam, Internal Medicine, Amsterdam, The Netherlands
| | - Klemen Dovc
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children’s Hospital, Ljubljana, Slovenia, and Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Francis J Doyle
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Laya Ekhlaspour
- Lucile Packard Children’s Hospital—Pediatric Endocrinology, Stanford University School of Medicine, Palo Alto, CA 94304, USA
| | - Naama Fisch Shvalb
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children’s Medical Center of Israel, 49202 Petah Tikva, Israel
| | - Gregory P Forlenza
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | | | - Satish K Garg
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Dana C Gershenoff
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | - Linda A Gonder-Frederick
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
| | - Ahmad Haidar
- Department of Biomedical Engineering, McGill University, Montreal, Canada
| | - Sara Hartnell
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | | | - Simon Heller
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK
| | - Irl B Hirsch
- Department of Medicine, University of Washington Diabetes Institute, University of Washington, Seattle, WA, USA
| | - Korey K Hood
- Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Diana Isaacs
- Cleveland Clinic, Endocrinology and Metabolism Institute, Cleveland, OH 44106, USA
| | - David C Klonoff
- Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, CA 94010, USA
| | - Olga Kordonouri
- AUF DER BULT, Diabetes-Center for Children and Adolescents, Endocrinology and General Paediatrics, Hannover, Germany
| | | | - Lori Laffel
- Joslin Diabetes Center, Harvard Medical School, Boston, MA 02215, USA
| | - Julia Lawton
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Rayhan A Lal
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Lalantha Leelarathna
- Manchester University Hospitals NHS Foundation Trust/University of Manchester, Manchester, UK
| | - David M Maahs
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, CA 94304, USA
| | - Helen R Murphy
- Norwich Medical School, University of East Anglia, Norwich, UK
| | - Kirsten Nørgaard
- Steno Diabetes Center Copenhagen and Department of Clinical Medicine, University of Copenhagen, Gentofte, Denmark
| | - David O’Neal
- Department of Medicine and Department of Endocrinology, St Vincent’s Hospital Melbourne, University of Melbourne, Melbourne, Australia
| | - Sean Oser
- Department of Family Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Tamara Oser
- Department of Family Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Eric Renard
- Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital, and Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Michael C Riddell
- School of Kinesiology & Health Science, Muscle Health Research Centre, York University, Toronto, Canada
| | - David Rodbard
- Biomedical Informatics Consultants LLC, Potomac, MD, USA
| | - Steven J Russell
- Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Desmond A Schatz
- Department of Pediatrics, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL 02114, USA
| | - Viral N Shah
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Jennifer L Sherr
- Department of Pediatrics, Yale University School of Medicine, Pediatric Endocrinology, New Haven, CT 06511, USA
| | - Gregg D Simonson
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | - R Paul Wadwa
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Candice Ward
- Institute of Metabolic Science, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Stuart A Weinzimer
- Department of Pediatrics, Yale University School of Medicine, Pediatric Endocrinology, New Haven, CT 06511, USA
| | - Emma G Wilmot
- Department of Diabetes & Endocrinology, University Hospitals of Derby and Burton NHS Trust, Derby, UK
- Division of Medical Sciences and Graduate Entry Medicine, University of Nottingham, Nottingham, England, UK
| | - Tadej Battelino
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children’s Hospital, Ljubljana, Slovenia, and Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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Karol AB, O'Malley G, Fallurin R, Levy CJ. Automated Insulin Delivery Systems as a Treatment for Type 2 Diabetes Mellitus: A Review. Endocr Pract 2023; 29:214-220. [PMID: 36241017 DOI: 10.1016/j.eprac.2022.10.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 09/29/2022] [Accepted: 10/03/2022] [Indexed: 12/13/2022]
Abstract
OBJECTIVE Approximately 6.3% of the worldwide population has type 2 diabetes mellitus (T2DM), and the number of people requiring insulin is increasing. Automated insulin delivery (AID) systems integrate continuous subcutaneous insulin infusion and continuous glucose monitoring with a predictive control algorithm to provide more physiologic glycemic control. Personalized glycemic targets are recommended in T2DM owing to the heterogeneity of the disease. Based on the success of hybrid closed-loop systems in improving glycemic control and safety in type 1 diabetes mellitus, there has been further interest in the use of these systems in people with T2DM. METHODS We performed a review of AID systems with a focus on the T2DM population. RESULTS In 5 randomized controlled trials, AID systems improve time in range and reduce glycemic variability, without increasing insulin requirements or the risk of hypoglycemia. CONCLUSION AID systems in T2DM are safe and effective in hospitalized and closely monitored settings. Home studies of longer duration are required to assess for long-term benefit and identify target populations of benefit.
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Affiliation(s)
- Alexander B Karol
- Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Grenye O'Malley
- Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Reshmitha Fallurin
- Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Carol J Levy
- Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai, New York, New York.
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Palmer BA, Soltys K, Zimmerman MB, Norris AW, Tsalikian E, Tansey MJ, Pinnaro CT. Diabetes Device Downloading: Benefits and Barriers Among Youth With Type 1 Diabetes. J Diabetes Sci Technol 2023; 17:381-389. [PMID: 34809477 PMCID: PMC10012364 DOI: 10.1177/19322968211059537] [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: 11/15/2022]
Abstract
BACKGROUND The majority of youth with type 1 diabetes (T1D) fail to meet glycemic targets despite increasing continuous glucose monitoring (CGM) use. We therefore aimed to determine the proportion of caregivers who review recent glycemic trends ("retrospective review") and make ensuant insulin adjustments based on this data ("retroactive insulin adjustments"). We additionally considered that fear of hypoglycemia and frequency of severe hypoglycemia would be associated with performing retrospective review. METHODS We conducted a cross-sectional survey of caregivers of youth with T1D, collecting demographics, diabetes technology usage, patterns of glucose data review/insulin dose self-adjustment, and Hypoglycemia Fear Survey (HFS). RESULTS Nineteen percent of eligible caregivers (191/1003) responded. Performing retrospective review was associated with younger child age (12.2 versus 15.4, P = .0001) and CGM use (92% versus 73%, P = .004), but was not associated with a significant improvement in child's HbA1c (7.89 versus 8.04, P = .65). Retrospective reviewers had significantly higher HFS-behavior scores (31.9 versus 27.7, P = .0002), which remained significantly higher when adjusted for child's age and CGM use (P = .005). Linear regression identified a significant negative association between HbA1c (%) and number of retroactive insulin adjustments (0.24 percent lower mean HbA1c per additional adjustment made, P = .02). CONCLUSIONS Retrospective glucose data review is associated with improved HbA1c when coupled with data-driven retroactive insulin adjustments. Barriers to data downloading existed even in this cohort of predominantly CGM-using T1D families.
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Affiliation(s)
- Benjamin A. Palmer
- Division of Endocrinology and Diabetes,
Stead Family Department of Pediatrics, The University of Iowa, Iowa City, IA,
USA
| | - Karissa Soltys
- Division of Endocrinology and Diabetes,
Stead Family Department of Pediatrics, The University of Iowa, Iowa City, IA,
USA
| | | | - Andrew W. Norris
- Division of Endocrinology and Diabetes,
Stead Family Department of Pediatrics, The University of Iowa, Iowa City, IA,
USA
- Fraternal Order of Eagles Diabetes
Research Center, The University of Iowa, Iowa City, IA, USA
| | - Eva Tsalikian
- Division of Endocrinology and Diabetes,
Stead Family Department of Pediatrics, The University of Iowa, Iowa City, IA,
USA
| | - Michael J. Tansey
- Division of Endocrinology and Diabetes,
Stead Family Department of Pediatrics, The University of Iowa, Iowa City, IA,
USA
- Fraternal Order of Eagles Diabetes
Research Center, The University of Iowa, Iowa City, IA, USA
| | - Catherina T. Pinnaro
- Division of Endocrinology and Diabetes,
Stead Family Department of Pediatrics, The University of Iowa, Iowa City, IA,
USA
- Fraternal Order of Eagles Diabetes
Research Center, The University of Iowa, Iowa City, IA, USA
- Catherina T. Pinnaro, MD, MS, Division of
Endocrinology and Diabetes, Stead Family Department of Pediatrics, The
University of Iowa, 216 MRC, 501 Newton Road, Iowa City, IA 52242, USA.
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Mameli C, Smylie GM, Galati A, Rapone B, Cardona-Hernandez R, Zuccotti G, Delvecchio M. Safety, metabolic and psychological outcomes of Medtronic MiniMed 670G in children, adolescents and young adults: a systematic review. Eur J Pediatr 2023; 182:1949-1963. [PMID: 36809498 PMCID: PMC9942055 DOI: 10.1007/s00431-023-04833-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/18/2023] [Accepted: 01/20/2023] [Indexed: 02/23/2023]
Abstract
Hybrid closed loop (HCL) systems are the combination of a pump for insulin delivery and a glucose sensor for continuous glucose monitoring. These systems are managed by an algorithm, which delivers insulin on the basis of the interstitial glucose levels. The MiniMed™ 670G system was the first HCL system available for clinical purpose. In this paper, we reviewed the literature about metabolic and psychological outcomes in children, adolescents and young adults with type 1 diabetes treated with MiniMed™ 670G. Only 30 papers responded to the inclusion criteria and thus were considered. All the papers show that the system is safe and effective in managing glucose control. Metabolic outcomes are available up to 12 months of follow-up; longer study period are lacking. This HCL system may improve HbA1c up to 7.1% and time in range up to 73%. The time spent in hypoglycaemia is almost neglectable. Better improvement in blood glucose control is observed in patients with higher HbA1c at HCL system start and larger daily use of auto-mode functionality. Conclusion: The Medtronic MiniMed™ 670G is safe and well accepted, without any increase in the burden for patients. Some papers report an improvement in the psychological outcomes, but other papers do not confirm this finding. So far, it significantly improves the management of diabetes mellitus in children, adolescents and young adults. Proper training and support by the diabetes team are mandatory. Studies for a period longer than 1 year would be appreciated to better understand the potentiality of this system. What is Known: • The Medtronic MiniMedTM 670G is a hybrid closed loop system which combines a continuous glucose monitoring sensor with an insulin pump. • It has been the first hybrid closed loop system available for clinical purpose. Adequate training and patients support play a key role in diabetes management. What is New: • The Medtronic MiniMedTM 670G may improve HbA1c and CGM metrics up to 1-year of follow-up, but the improvement appears lower than advanced hybrid closed loop systems. This system is effective to prevent hypoglycaemia. • The psychosocial effects remain less understood in terms of improvement of psychosocial outcomes. The system has been considered to provide flexibility and independence by the patients and their caregivers. The workload required to use this system is perceived as a burden by the patients who decrease the use of auto-mode functionality over time.
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Affiliation(s)
- Chiara Mameli
- grid.4708.b0000 0004 1757 2822Department of Pediatrics, Buzzi Children’s Hospital, University of Milan, Milan, Italy ,grid.4708.b0000 0004 1757 2822Department of Biomedical and Clinical Science, University of Milan, Milan, Italy
| | - Giulia Marie Smylie
- grid.4708.b0000 0004 1757 2822Department of Pediatrics, Buzzi Children’s Hospital, University of Milan, Milan, Italy
| | - Alessio Galati
- Metabolic Disorders and Diabetes Unit, “Giovanni XXIII” Children’s Hospital, AOU Policlinico-Giovanni XXIII, Bari, Italy
| | - Biagio Rapone
- grid.7644.10000 0001 0120 3326Department of Interdisciplinary Medicine, University of Bari “Aldo Moro, 70121 Bari, Italy
| | - Roque Cardona-Hernandez
- grid.411160.30000 0001 0663 8628Division of Pediatric Endocrinology, Hospital Sant Joan de Déu, Barcelona, Spain
| | - Gianvincenzo Zuccotti
- grid.4708.b0000 0004 1757 2822Department of Pediatrics, Buzzi Children’s Hospital, University of Milan, Milan, Italy ,grid.4708.b0000 0004 1757 2822Department of Biomedical and Clinical Science, University of Milan, Milan, Italy
| | - Maurizio Delvecchio
- Metabolic Disorders and Diabetes Unit, "Giovanni XXIII" Children's Hospital, AOU Policlinico-Giovanni XXIII, Bari, Italy.
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Grassi B, Gómez AM, Calliari LE, Franco D, Raggio M, Riera F, Castro M, McVean J, van den Heuvel T, Arrieta A, Castañeda J, Cohen O. Real-world performance of the MiniMed 780G advanced hybrid closed loop system in Latin America: Substantial improvement in glycaemic control with each technology iteration of the MiniMed automated insulin delivery system. Diabetes Obes Metab 2023; 25:1688-1697. [PMID: 36789699 DOI: 10.1111/dom.15023] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/06/2023] [Accepted: 02/12/2023] [Indexed: 02/16/2023]
Abstract
AIM We studied real-world performance of MiniMed (MM) 780G system users from Argentina, Brazil, Colombia and Chile (geographical analysis), and the effect of each technology iteration of the MM system on glycaemic control (technology iteration analysis). MATERIALS AND METHODS CareLink data from August 2020 to September 2022 were extracted. Endpoints included continuous glucose monitoring metrics. For the geographical analysis, aggregated endpoints for MM780G system users were calculated. For the technology iteration analysis, MM780G system user outcomes were compared with outcomes when the same individuals were still using the MM640G or MM670G system. RESULTS On average, 1025 MM780G system users from the geographical analysis were followed for 136 (SD 135) days, spent 91.5 (14.3)% in advanced hybrid closed loop, showed a glucose management indicator (GMI) of 6.7 (0.3)%, a time in range between 70 and 180 mg/dl (TIR) of 76.5 (9.0)%, and a time below range 70 mg/dl (TBR) of 2.7 (2.1)%. The percentage of users reaching targets of GMI <7%, TIR >70% and TBR <4% was 80.8%, 78.1% and 80.1%, respectively. The technology iteration analysis on users transitioning from MM640G to MM780G system (N = 381) showed 0.4% decrease in GMI (7.1% to 6.7%, p < .0001), 10.7% increase in TIR (65.9% to 76.6%, p < .0001), while TBR remained. The percentage of insulin delivered automatically increased as well (47.5%-57.7%, p < .0001). Users transitioning from MM670G system (N = 78) showed a similar but less pronounced pattern. CONCLUSIONS Real-world Latin American MM780G users on average showed good glucose control, achieving international targets. Glycaemic control increased with every technology iteration of the MM system, providing more automation each time.
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Affiliation(s)
- Bruno Grassi
- Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Ana Maria Gómez
- Pontificia Universidad Javeriana, Bogotá, Colombia
- Hospital Universitario de San Ignacio, Bogotá, Colombia
| | | | - Denise Franco
- CPCLIN/DASA Clinical Research Centre, São Paulo, Brazil
| | | | | | | | | | | | - Arcelia Arrieta
- Medtronic International Trading Sarl, Tolochenaz, Switzerland
| | | | - Ohad Cohen
- Medtronic International Trading Sarl, Tolochenaz, Switzerland
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