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Pellizzari E, Prendin F, Cappon G, Sparacino G, Facchinetti A. drCORRECT: An Algorithm for the Preventive Administration of Postprandial Corrective Insulin Boluses in Type 1 Diabetes Management. J Diabetes Sci Technol 2025; 19:711-721. [PMID: 38158565 PMCID: PMC12035290 DOI: 10.1177/19322968231221768] [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: 01/03/2024]
Abstract
BACKGROUND In type 1 diabetes therapy, precise tuning of postprandial corrective insulin boluses (CIBs) is crucial to mitigate hyperglycemia without inducing dangerous hypoglycemic events. Several heuristic formulas accounting for continuous glucose monitoring (CGM) trend have been proposed in the literature. However, these formulas suggest a lot of quantized CIB adjustments, and they lack personalization. METHOD drCORRECT algorithm proposed in this work employs a patient-specific time parameter and the "dynamic risk" (DR) measure to determine postprandial CIB suggestion. The expected benefits include the reduction of time in hyperglycemia, thanks to the preventive action exploited through DR. drCORRECT has been assessed retrospectively vs the literature methods proposed by Aleppo et al (AL), Bruttomesso et al (BR), and Ziegler et al (ZI) using a data set of 49 CGM daily traces recorded in free-living conditions. Retrospective evaluation of the algorithms is made possible by the use of ReplayBG, a digital twin-based tool that allows assessing alternative insulin therapies on already collected glucose data. Efficacy in terms of glucose control was measured by temporal, risk indicators, and dedicated hyperglycemic/hypoglycemic events metrics. RESULTS drCORRECT significantly reduces time spent in hyperglycemia when compared with AL and BR (33.52 [24.16, 39.89]% vs 39.76 [22.54, 48.15]% and 36.32 [26.91, 45.93]%, respectively); significantly reduces daily injected insulin (5.97 [3.80, 8.06] U vs 7.5 [5.21, 10.34] U), glycemia risk index (38.78 [26.58, 55.39] vs 40.78 [27.95, 70.30]), and time spent in hypoglycemia (0.00 [0.00, 1.74]% vs 0.00 [0.00, 10.23]%) when compared with ZI, resulting overall in a safer strategy. CONCLUSIONS The proposed drCORRECT algorithm allows preventive actions thanks to the personalized timing configuration and the introduction of the innovative DR-based CIB threshold, proving to be a valid alternative to the available heuristic literature methods.
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Affiliation(s)
- Elisa Pellizzari
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Francesco Prendin
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Giacomo Cappon
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Giovanni Sparacino
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Andrea Facchinetti
- Department of Information Engineering, University of Padova, Padova, Italy
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Castorino K, Durnwald C, Ehrenberg S, Ehrhardt N, Isaacs D, Levy CJ, Valent AM. Practical Considerations for Using Continuous Glucose Monitoring in Patients with Gestational Diabetes Mellitus. J Womens Health (Larchmt) 2025; 34:10-20. [PMID: 39378174 DOI: 10.1089/jwh.2023.0864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/10/2024] Open
Abstract
Gestational diabetes mellitus (GDM) is the most prevalent metabolic complication during pregnancy. GDM is associated with adverse perinatal, neonatal, and long-term health consequences. Studies have demonstrated that the use of continuous glucose monitoring (CGM) reduces the incidence of maternal and neonatal complications in pregnant women with type 1 diabetes. Although the use of CGM in GDM has not been well studied, a growing body of evidence is showing potential benefits in the GDM population. This article discusses the advantages and challenges of CGM and provides practical guidelines for using this technology in the GDM population.
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Affiliation(s)
| | - Celeste Durnwald
- Department of Obstetrics and Gynecology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Stacey Ehrenberg
- Department of Obstetrics and Gynecology Institute, Cleveland Clinic Foundation, Cleveland, Ohio, USA
| | - Nicole Ehrhardt
- Division of Endocrinology, Diabetes and Metabolism, University of Washington Diabetes Institute, Seattle, Washington, USA
| | - Dianna Isaacs
- Cleveland Clinic Endocrinology & Metabolism Institute, Cleveland, Ohio, USA
| | - Carol J Levy
- Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Amy M Valent
- Department of Obstetrics and Gynecology, Oregon Health and Science University, Portland, Oregon, USA
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3
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American Diabetes Association Professional Practice Committee, ElSayed NA, McCoy RG, Aleppo G, Bajaj M, Balapattabi K, Beverly EA, Briggs Early K, Bruemmer D, Echouffo-Tcheugui JB, Ekhlaspour L, Gaglia JL, Garg R, Girotra M, Khunti K, Lal R, Lingvay I, Matfin G, Neumiller JJ, Pandya N, Pekas EJ, Pilla SJ, Polsky S, Segal AR, Seley JJ, Stanton RC, Bannuru RR. 9. Pharmacologic Approaches to Glycemic Treatment: Standards of Care in Diabetes-2025. Diabetes Care 2025; 48:S181-S206. [PMID: 39651989 PMCID: PMC11635045 DOI: 10.2337/dc25-s009] [Citation(s) in RCA: 43] [Impact Index Per Article: 43.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2024]
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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Shaw JLV, Bannuru RR, Beach L, ElSayed NA, Freckmann G, Füzéry AK, Fung AWS, Gilbert J, Huang Y, Korpi-Steiner N, Logan S, Longo R, MacKay D, Maks L, Pleus S, Rogers K, Seley JJ, Taxin Z, Thompson-Hutchison F, Tolan NV, Tran NK, Umpierrez GE, Venner AA. Consensus Considerations and Good Practice Points for Use of Continuous Glucose Monitoring Systems in Hospital Settings. Diabetes Care 2024; 47:2062-2075. [PMID: 39452893 DOI: 10.2337/dci24-0073] [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: 09/04/2024] [Accepted: 09/13/2024] [Indexed: 10/26/2024]
Abstract
Continuous glucose monitoring (CGM) systems provide frequent glucose measurements in interstitial fluid and have been used widely in ambulatory settings for diabetes management. During the coronavirus disease 2019 (COVID-19) pandemic, regulators in the U.S. and Canada temporarily allowed for CGM systems to be used in hospitals with the aim of reducing health care professional COVID-19 exposure and limiting use of personal protective equipment. As such, studies on hospital CGM system use have been possible. With improved sensor accuracy, there is increased interest in CGM usage for diabetes management in hospitals. Laboratorians and health care professionals must determine how to integrate CGM usage into practice. The aim of this consensus guidance document is to provide an update on the application of CGM systems in hospital, with insights and opinions from laboratory medicine, endocrinology, and nursing.
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Affiliation(s)
- Julie L V Shaw
- Division of Biochemistry, Eastern Ontario Regional Laboratory Association and The Ottawa Hospital, and Department of Pathology and Laboratory Medicine, University of Ottawa, Ottawa, Ontario, Canada
| | | | - Lori Beach
- Division of Biochemistry, IWK Health, Department of Pathology and Laboratory Medicine, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Nuha A ElSayed
- American Diabetes Association, Arlington, VA
- Harvard Medical School, Cambridge, MA
| | - Guido Freckmann
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Anna K Füzéry
- Alberta Precision Laboratories, Edmonton, Alberta, Canada
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
| | - Angela W S Fung
- Department of Pathology and Laboratory Medicine, St. Paul's Hospital, Providence Health Care and University of British Columbia, Vancouver, British Columbia, Canada
| | - Jeremy Gilbert
- Division of Endocrinology and Metabolism, Sunnybrook Health Sciences Centre, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Yun Huang
- Division of Biochemistry, Kingston Health Sciences Centre, and Department of Pathology and Molecular Medicine, Queen's University, Kingston, Ontario, Canada
| | - Nichole Korpi-Steiner
- Department of Pathology and Laboratory Medicine, The University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Samantha Logan
- Alberta Precision Laboratories, Edmonton, Alberta, Canada
- Department of Pathology and Laboratory Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | | | - Dylan MacKay
- Departments of Food and Human Nutritional Sciences and Internal Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Lisa Maks
- Providence Health Care, Vancouver, British Columbia, Canada
| | - Stefan Pleus
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Kendall Rogers
- Division of Hospital Medicine, Department of Internal Medicine, The University of New Mexico School of Medicine, Albuquerque, NM
| | - Jane Jeffrie Seley
- Division of Endocrinology, Diabetes and Metabolism, Weill Cornell Medicine, New York, NY
| | - Zachary Taxin
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA
| | | | - Nicole V Tolan
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Nam K Tran
- Department of Pathology and Laboratory Medicine, UC Davis Health, University of California, Davis, Sacramento, CA
| | - Guillermo E Umpierrez
- Division of Endocrinology and Metabolism, Department of Medicine, Emory School of Medicine, Emory University, Atlanta, GA
| | - Allison A Venner
- Alberta Precision Laboratories, Edmonton, Alberta, Canada
- Department of Pathology and Laboratory Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
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5
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Klonoff DC, Freckmann G, Pleus S, Kovatchev BP, Kerr D, Tse C(C, Li C, Agus MSD, Dungan K, Voglová Hagerf B, Krouwer JS, Lee WA(A, Misra S, Rhee SY, Sabharwal A, Seley JJ, Shah VN, Tran NK, Waki K, Worth C, Tian T, Aaron RE, Rutledge K, Ho CN, Ayers AT, Adler A, Ahn DT, Aktürk HK, Al-Sofiani ME, Bailey TS, Baker M, Bally L, Bannuru RR, Bauer EM, Bee YM, Blanchette JE, Cengiz E, Chase JG, Y. Chen K, Cherñavvsky D, Clements M, Cote GL, Dhatariya KK, Drincic A, Ejskjaer N, Espinoza J, Fabris C, Fleming GA, Gabbay MAL, Galindo RJ, Gómez-Medina AM, Heinemann L, Hermanns N, Hoang T, Hussain S, Jacobs PG, Jendle J, Joshi SR, Koliwad SK, Lal RA, Leiter LA, Lind M, Mader JK, Maran A, Masharani U, Mathioudakis N, McShane M, Mehta C, Moon SJ, Nichols JH, O’Neal DN, Pasquel FJ, Peters AL, Pfützner A, Pop-Busui R, Ranjitkar P, Rhee CM, Sacks DB, Schmidt S, Schwaighofer SM, Sheng B, Simonson GD, Sode K, Spanakis EK, Spartano NL, Umpierrez GE, Vareth M, Vesper HW, Wang J, Wright E, Wu AH, Yeshiwas S, Zilbermint M, Kohn MA. The Diabetes Technology Society Error Grid and Trend Accuracy Matrix for Glucose Monitors. J Diabetes Sci Technol 2024; 18:1346-1361. [PMID: 39369312 PMCID: PMC11531029 DOI: 10.1177/19322968241275701] [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: 10/07/2024]
Abstract
INTRODUCTION An error grid compares measured versus reference glucose concentrations to assign clinical risk values to observed errors. Widely used error grids for blood glucose monitors (BGMs) have limited value because they do not also reflect clinical accuracy of continuous glucose monitors (CGMs). METHODS Diabetes Technology Society (DTS) convened 89 international experts in glucose monitoring to (1) smooth the borders of the Surveillance Error Grid (SEG) zones and create a user-friendly tool-the DTS Error Grid; (2) define five risk zones of clinical point accuracy (A-E) to be identical for BGMs and CGMs; (3) determine a relationship between DTS Error Grid percent in Zone A and mean absolute relative difference (MARD) from analyzing 22 BGM and nine CGM accuracy studies; and (4) create trend risk categories (1-5) for CGM trend accuracy. RESULTS The DTS Error Grid for point accuracy contains five risk zones (A-E) with straight-line borders that can be applied to both BGM and CGM accuracy data. In a data set combining point accuracy data from 18 BGMs, 2.6% of total data pairs equally moved from Zones A to B and vice versa (SEG compared with DTS Error Grid). For every 1% increase in percent data in Zone A, the MARD decreased by approximately 0.33%. We also created a DTS Trend Accuracy Matrix with five trend risk categories (1-5) for CGM-reported trend indicators compared with reference trends calculated from reference glucose. CONCLUSION The DTS Error Grid combines contemporary clinician input regarding clinical point accuracy for BGMs and CGMs. The DTS Trend Accuracy Matrix assesses accuracy of CGM trend indicators.
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Affiliation(s)
- David C. Klonoff
- Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, CA, USA
| | - Guido Freckmann
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Stefan Pleus
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Boris P. Kovatchev
- School of Medicine, University of Virginia, Charlottesville, VA, USA
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA
| | - David Kerr
- Sutter Health Center for Health Systems Research, Santa Barbara, CA, USA
| | | | - Chengdong Li
- College of Nursing, Florida State University, Tallahassee, FL, USA
| | - Michael S. D. Agus
- Divisions of Endocrinology and Medical Critical Care, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Kathleen Dungan
- Division of Endocrinology, Diabetes and Metabolism, Ohio State University, Columbus, OH, USA
| | - Barbora Voglová Hagerf
- Diabetes Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
- First Medical Faculty, Charles University, Prague, Czech Republic
| | | | - Wei-An (Andy) Lee
- Division of Endocrinology, Los Angeles General Medical Center, Los Angeles, CA, USA
| | - Shivani Misra
- Division of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Sang Youl Rhee
- Center for Digital Health and Department of Endocrinology and Metabolism, College of Medicine, Kyung Hee University, Seoul, Republic of Korea
| | | | - Jane Jeffrie Seley
- Division of Endocrinology, Diabetes & Metabolism, Weill Cornell Medicine, New York, NY, USA
| | - Viral N. Shah
- Division of Endocrinology and Metabolism, School of Medicine, Indiana University, Indianapolis, IN, USA
| | - Nam K. Tran
- University of California Davis Health, Sacramento, CA, USA
| | - Kayo Waki
- Department of Biomedical Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Chris Worth
- Department of Paediatric Endocrinology, Royal Manchester Children’s Hospital, Manchester, UK
| | - Tiffany Tian
- Diabetes Technology Society, Burlingame, CA, USA
| | | | | | - Cindy N. Ho
- Diabetes Technology Society, Burlingame, CA, USA
| | | | - Amanda Adler
- Diabetes Trials Unit, University of Oxford, Oxford, UK
| | - David T. Ahn
- Mary & Dick Allen Diabetes Center, Hoag Memorial Hospital Presbyterian, Newport Beach, CA, USA
| | - Halis Kaan Aktürk
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO, USA
| | - Mohammed E. Al-Sofiani
- Division of Endocrinology, Department of Internal Medicine, College of Medicine, King Saud University, Riyadh, Saudi Arabia
- Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins University, Baltimore, MD, USA
| | | | - Matt Baker
- North Kansas City Hospital, North Kansas City, MO, USA
| | - Lia Bally
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern University Hospital and University of Bern, Bern, Switzerland
| | | | | | | | - Julia E. Blanchette
- University Hospitals Cleveland Medical Center, UH Diabetes and Metabolic Care Center, Cleveland, OH, USA
- School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Eda Cengiz
- University of California San Francisco, San Francisco, CA, USA
| | - James Geoffrey Chase
- Centre for Bioengineering, Department of Mechanical Engineering, University of Canterbury, Christchurch, New Zealand
| | - Kong Y. Chen
- National Institute of Diabetes and Digestive and Kidney Diseases Intramural Research Program, National Institutes of Health, Bethesda, MD, USA
| | | | | | - Gerard L. Cote
- Center for Remote Health Technologies and Systems, Department of Biomedical Engineering and Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA
| | - Ketan K. Dhatariya
- Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
- Norwich Medical School, University of East Anglia, Norwich, UK
| | - Andjela Drincic
- Devision of Diabetes, Endocrinology, and Metabolism, University of Nebraska Medical Center, Omaha, NE, USA
| | - Niels Ejskjaer
- Steno Diabetes Center North Denmark and Department of Endocrinology, Aalborg University Hospital, Aalborg, Denmark
- Department of Clinical Medicine, Aalborg University Hospital, Aalborg, Denmark
| | - Juan Espinoza
- Stanley Manne Children’s Research Institute, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA
| | - Chiara Fabris
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA
| | | | | | - Rodolfo J. Galindo
- Division of Endocrinology, Miller School of Medicine, University of Miami, Miami, FL, USA
| | | | - Lutz Heinemann
- Science Consulting in Diabetes GmbH, Düsseldorf, Germany
| | - Norbert Hermanns
- Research Institute Diabetes Academy Mergentheim, Bad Mergentheim, Germany & University of Bamberg, Bamberg, Germany
| | - Thanh Hoang
- Division of Endocrinology, Walter Reed National Military Medical Center, Bethesda, MD, USA
| | - Sufyan Hussain
- Department of Diabetes, King’s College London, London, UK
- Department of Diabetes and Endocrinology, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Peter G. Jacobs
- Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR, USA
| | - Johan Jendle
- Department of Medical Sciences, School of Medicine, Örebro University, Örebro, Sweden
| | | | - Suneil K. Koliwad
- Division of Endocrinology and Metabolism, University of California–San Francisco, San Francisco, CA, USA
| | - Rayhan A. Lal
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
| | - Lawrence A. Leiter
- Li Ka Shing Knowledge Institute, St. Michael’s Hospital, University of Toronto, Toronto, ON, Canada
| | - Marcus Lind
- Institute of Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Julia K. Mader
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Alberto Maran
- Department of Medicine, University of Padua, Padua, Italy
| | - Umesh Masharani
- Division of Endocrinology and Metabolism, University of California–San Francisco, San Francisco, CA, USA
| | - Nestoras Mathioudakis
- Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Michael McShane
- Department of Biomedical Engineering, Department of Materials Science & Engineering, Center for Remote Health Technologies and Systems, Texas A&M University, College Station, TX, USA
| | - Chhavi Mehta
- Mills-Peninsula Medical Center, San Mateo, CA, USA
| | - Sun-Joon Moon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | | | - David N. O’Neal
- Department of Medicine, The University of Melbourne, Melbourne, VIC, Australia
| | | | - Anne L. Peters
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Andreas Pfützner
- Pfützner Science & Health Institute, Mainz, Germany
- University for Digital Technologies in Medicine and Dentistry, Wiltz, Luxembourg
| | - Rodica Pop-Busui
- Division of Metabolism, Endocrinology and Diabetes, University of Michigan, Ann Arbor, MI, USA
| | - Pratistha Ranjitkar
- ADLM DEI Steering Committee, ADLM—Association for Diagnostics & Laboratory Medicine (formerly AACC), Washington, D.C., USA
| | - Connie M. Rhee
- VA Greater Los Angeles Healthcare System and David Geffen School of Medicine, University of California–Los Angeles, Los Angeles, CA, USA
- Cedars-Sinai Health Systems, Los Angeles, CA, USA
| | | | | | | | - Bin Sheng
- Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Gregg D. Simonson
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN, USA
| | - Koji Sode
- Joint Department of Biomedical Engineering, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Joint Department of Biomedical Engineering, North Carolina State University, Chapel Hill, NC, USA
| | - Elias K. Spanakis
- VA Maryland Health Care System, School of Medicine, University of Maryland, Baltimore, MD, USA
| | - Nicole L. Spartano
- Section of Endocrinology, Diabetes, Nutrition, and Weight Management, Chobanian & Avedisian School of Medicine, Boston University, Boston, MA, USA
| | | | - Maryam Vareth
- Berkeley Institute for Data Science, College of Computing, Data Science, and Society, UC Berkeley, Berkeley, CA, USA
- The Center of Intelligent Imaging (Ci), UCSF Department of Radiology and Biomedical Imaging, San Francisco, CA, USA
- UC Berkeley/UCSF Computational Precision Health (CPH) Program, Berkeley, CA, USA
| | | | - Jing Wang
- College of Nursing, Florida State University, Tallahassee, FL, USA
| | - Eugene Wright
- Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | - Alan H.B. Wu
- Department of Lab Medicine, University of California–San Francisco, San Francisco, CA, USA
| | - Sewagegn Yeshiwas
- Department of Pediatric Endocrinology and Child Health, College of Health Science, Addis Abeba University, Addis Ababa, Ethiopia
| | - Mihail Zilbermint
- Division of Hospital Medicine, Johns Hopkins Community Physicians, Johns Hopkins Medicine, Baltimore, MD, USA
- Suburban Hospital, Johns Hopkins Medicine, Bethesda, MD, USA
- Division of Endocrinology, Diabetes, and Metabolism, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Michael A. Kohn
- University of California San Francisco, San Francisco, CA, USA
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Glatzer T, Ehrmann D, Gehr B, Penalba Martinez MT, Onvlee J, Bucklar G, Hofer M, Stangs M, Wolf N. Clinical Usage and Potential Benefits of a Continuous Glucose Monitoring Predict App. J Diabetes Sci Technol 2024; 18:1009-1013. [PMID: 39158995 PMCID: PMC11418506 DOI: 10.1177/19322968241268353] [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: 08/21/2024]
Abstract
Continuous glucose monitoring (CGM) has become an increasingly important tool for self-management in people with diabetes mellitus (DM). In this paper, we discuss recommendations on how to implement predictive features provided by the Accu-Chek SmartGuide Predict app in clinical practice. The Predict app's features are aimed at ultimately reducing diabetes stress and fear of hypoglycemia in people with DM. Furthermore, we explore the use cases and potential benefits of continuous glucose prediction, predictions of low glucose, and nocturnal hypoglycemia.
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Affiliation(s)
| | - Dominic Ehrmann
- Research Institute of the Diabetes-Academy Bad Mergentheim (FIDAM), Bad Mergentheim, Germany
| | | | | | - Joannet Onvlee
- Radboud University Medical Center, Nijmegen, The Netherlands
| | | | | | | | - Nora Wolf
- Roche Diabetes Care GmbH, Mannheim, Germany
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7
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Visser MM, Vangoitsenhoven R, Gillard P, Mathieu C. Review Article - Diabetes Technology in the Hospital: An Update. Curr Diab Rep 2024; 24:173-182. [PMID: 38842632 DOI: 10.1007/s11892-024-01545-3] [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] [Accepted: 05/29/2024] [Indexed: 06/07/2024]
Abstract
PURPOSE OF REVIEW There have been many developments in diabetes technology in recent years, with continuous glucose monitoring (CGM), insulin pump therapy (CSII) and automated insulin delivery (AID) becoming progressively accepted in outpatient diabetes care. However, the use of such advanced diabetes technology in the inpatient setting is still limited for several reasons, including logistical challenges and staff training needs. On the other hand, hospital settings with altered diet and stress-induced hyperglycemia often pose challenges to tight glycemic control using conventional treatment tools. Integrating smarter glucose monitoring and insulin delivery devices into the increasingly technical hospital environment could reduce diabetes-related morbidity and mortality. This narrative review describes the most recent literature on the use of diabetes technology in the hospital and suggests avenues for further research. RECENT FINDINGS Advanced diabetes technology has the potential to improve glycemic control in hospitalized people with and without diabetes, and could add particular value in certain conditions, such as nutrition therapy or perioperative management. Taken together, CGM allows for more accurate and patient-friendly follow-up and ad hoc titration of therapy. AID may also provide benefits, including improved glycemic control and reduced nursing workload. Before advanced diabetes technology can be used on a large scale in the hospital, further research is needed on efficacy, accuracy and safety, while implementation factors such as cost and staff training must also be overcome.
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Affiliation(s)
| | | | - Pieter Gillard
- Department of Endocrinology, University Hospitals Leuven, Louvain, Belgium
| | - Chantal Mathieu
- Department of Endocrinology, University Hospitals Leuven, Louvain, Belgium.
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8
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Novak D. A Serious Game (MyDiabetic) to Support Children's Education in Type 1 Diabetes Mellitus: Iterative Participatory Co-Design and Feasibility Study. JMIR Serious Games 2024; 12:e49478. [PMID: 38713496 PMCID: PMC11109855 DOI: 10.2196/49478] [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: 06/02/2023] [Revised: 08/24/2023] [Accepted: 02/13/2024] [Indexed: 05/08/2024] Open
Abstract
BACKGROUND Serious games, which are gaming applications used for purposes beyond entertainment to educate users on, and address, specific issues, may present a timely approach to promote healthy diabetes management behaviors among children with type 1 diabetes mellitus (T1DM). The lasting benefits associated with these serious games encompass improved patient education; enhanced glycemic control; the reinforcement of bonds within the community of people with diabetes; the facilitation of meaningful dialogues with caregivers, especially within the familial setting; and a significant reduction in the economic burdens associated with subsequent complications. OBJECTIVE This paper primarily aims to provide a detailed overview of the iterative design process and the associated evaluation methods used in the development of the educational game. Furthermore, this study aims to enhance motivation for sustained and extended engagement with the game over time. The MyDiabetic game design aims to educate children on various aspects, including the connections among food, insulin, and physical activity. Furthermore, it seeks to impart knowledge related to the operation of a glucometer and an insulin pen, as well as more advanced technologies such as administering glucagon, measuring ketoacidosis, and continuous glucose monitoring. METHODS The co-design methodology was applied, involving interviews, design workshops, and prototype feedback sessions. A combination of several approaches, such as tailoring, observational learning, social and family support, decision-making practice, and reward systems, was used to support children's compliance. Moreover, incorporating the literature, guidelines, and current practices into the design ensured that the game was aligned with established health care pathways and included relevant information and best practices for diabetes management. RESULTS The game was tested on 32 children in 3 iterations. Positive responses were received from children who tested the game as well as their parents. The game was also presented to 5 schoolmates of children with T1DM who appreciated a better understanding of the disease and the opportunity to support their friends more efficiently in T1DM compensation. The involvement of children and clinicians in participatory co-design contributed to to the game's high acceptance. With regard to the game's impact on education, 1 week of testing revealed an enhancement in educational outcomes. CONCLUSIONS The game is especially suitable for children newly diagnosed with T1DM because it acquaints them in a fun way with new terminology; for example, they can try to measure glycemia levels in an interactive way. The game also caters to children who still need to develop reading skills by including an audio guide. The guide ensures that children of all literacy levels can benefit from the game's educational content and interactive experiences. The game is available for download on Google Play and the Apple App Store.
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Affiliation(s)
- Daniel Novak
- Department of Cybernetics, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
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9
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American Diabetes Association Professional Practice Committee, ElSayed NA, Aleppo G, Bannuru RR, Bruemmer D, Collins BS, Ekhlaspour L, Gaglia JL, 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. 9. Pharmacologic Approaches to Glycemic Treatment: Standards of Care in Diabetes-2024. Diabetes Care 2024; 47:S158-S178. [PMID: 38078590 PMCID: PMC10725810 DOI: 10.2337/dc24-s009] [Citation(s) in RCA: 289] [Impact Index Per Article: 289.0] [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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10
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Lin YK, Agni A, Chuisano S, Fetters MD, Funnell M, Pop-Busui R, DeJonckheere MJ. Patient-Reported Usefulness and Challenges in Using Hypoglycemia-Informing Features of Continuous Glucose Monitors to Manage Hypoglycemia. Sci Diabetes Self Manag Care 2023; 49:229-238. [PMID: 37086168 PMCID: PMC10960636 DOI: 10.1177/26350106231168859] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/23/2023]
Abstract
PURPOSE The purpose of this study series, which involves a questionnaire survey and qualitative interviews, was to (a) evaluate patient-reported usefulness of continuous glucose monitor (CGM) hypoglycemia-informing features and (b) identify challenges in using these features (ie, CGM glucose numbers, trend arrows, trend graphs, and hypoglycemia alarms) during hypoglycemia in adults with type 1 diabetes (T1DM). METHODS A cross-sectional questionnaire survey study was conducted with adults who have T1DM and were using CGMs to assess the perceived usefulness of hypoglycemia-informing features. A semistructured interview study with T1DM CGM-using adults and inductive thematic analysis were subsequently performed to identify challenges in using CGM hypoglycemia-informing features to manage hypoglycemia. RESULTS In the survey study (N = 252), the CGM glucose numbers, trend arrows, trend graphs, and hypoglycemia alarms were found to be very useful by 79%, 70%, 43%, and 64% of participants, respectively. Several challenges in using these features to manage hypoglycemia were identified in the qualitative study (N = 23): (1) hypoglycemia information not fully reliable,; (2) unpredictability of future blood glucose levels, (3) lack of awareness about how information can be used, and (4) disruptions associated with information. CONCLUSIONS Although the majority of T1DM adults found their CGMs' hypoglycemia-informing features helpful, challenges in optimally using these features persisted. Targeted knowledge and behavioral interventions could improve CGM use to reduce hypoglycemia.
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Affiliation(s)
- Yu Kuei Lin
- Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan
| | - Annika Agni
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor, Michigan
| | - Samantha Chuisano
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor, Michigan
| | - Michael D Fetters
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor, Michigan
- Mixed Methods Program, University of Michigan Medical School, Ann Arbor, Michigan
| | - Martha Funnell
- Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, Michigan
| | - Rodica Pop-Busui
- Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan
| | - Melissa J DeJonckheere
- Department of Family Medicine, University of Michigan Medical School, Ann Arbor, Michigan
- Mixed Methods Program, University of Michigan Medical School, Ann Arbor, Michigan
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11
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Unsworth R, Armiger R, Jugnee N, Thomas M, Herrero P, Georgiou P, Oliver N, Reddy M. Safety and Efficacy of an Adaptive Bolus Calculator for Type 1 Diabetes: a Randomised Control Cross over Study. Diabetes Technol Ther 2023. [PMID: 37017468 DOI: 10.1089/dia.2022.0504] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/06/2023]
Abstract
Background The Advanced Bolus Calculator for Type 1 Diabetes (ABC4D) is a decision support system employing the artificial intelligence technique of case-based reasoning to adapt and personalise insulin bolus doses. The integrated system comprises a smartphone application and clinical web portal. We aimed to assess safety and efficacy of the ABC4D (intervention) compared to a non-adaptive bolus calculator (control). Methods This was a prospective randomised controlled crossover study. Following a 2-week run-in period, participants were randomised to ABC4D or control for 12 weeks. After a 6-week washout period, participants crossed over for 12 weeks. The primary outcome was difference in percentage (%) time in range (TIR) (3.9-10.0 mmol/L (70-180mg/dL)) change during the daytime (07:00-22:00) between groups. Results 37 adults with type 1 diabetes on multiple daily injections of insulin were randomised, median (IQR) age 44.7 (28.2-55.2) years, diabetes duration 15.0 (9.5-29.0) years, HbA1C 61.0 (58.0-67.0) mmol/mol (7.7 (7.5-8.3)%). Data from 33 participants were analysed. There was no significant difference in daytime %TIR change with ABC4D compared to control (median (IQR) +0.1 (-2.6 to + 4.0)% versus +1.9 (-3.8 to + 10.1)%; p = 0.53). Participants accepted fewer meal dose recommendations in the intervention compared to control (78.7 (55.8-97.6)% versus 93.5 (73.8-100)%; p = 0.009) with a greater reduction in insulin dosage from that recommended. Conclusion The ABC4D is safe for adapting insulin bolus doses and provided the same level of glycaemic control as the non-adaptive bolus calculator. Results suggest that participants did not follow ABC4D recommendations as frequently as control, impacting its effectiveness.
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Affiliation(s)
- Rebecca Unsworth
- Imperial College London, 4615, Department of Metabolism, Digestion and Reproduction, London, London, United Kingdom of Great Britain and Northern Ireland;
| | - Ryan Armiger
- Imperial College London, 4615, Department of Electrical and Electronic Engineering, London, London, United Kingdom of Great Britain and Northern Ireland;
| | - Narvada Jugnee
- Imperial College London, 4615, Department of Metabolism, Digestion and Reproduction, London, London, United Kingdom of Great Britain and Northern Ireland;
| | - Maria Thomas
- Imperial College London, 4615, Department of Metabolism, Digestion and Reproduction, London, London, United Kingdom of Great Britain and Northern Ireland;
| | - Pau Herrero
- Imperial College London, 4615, Department of Electrical and Electronic Engineering, London, London, United Kingdom of Great Britain and Northern Ireland;
| | - Pantelis Georgiou
- Imperial College London, 4615, Department of Electrical and Electronic Engineering, London, London, United Kingdom of Great Britain and Northern Ireland;
| | - Nick Oliver
- Imperial College London, 4615, Department of Metabolism, Digestion and Reproduction, London, London, United Kingdom of Great Britain and Northern Ireland;
| | - Monika Reddy
- Imperial College London, 4615, Department of Metabolism, Digestion & Reproduction, London, London, United Kingdom of Great Britain and Northern Ireland;
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12
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Parise M, Di Molfetta S, Graziano RT, Fiorentino R, Cutruzzolà A, Gnasso A, Irace C. A Head-to-Head Comparison of Two Algorithms for Adjusting Mealtime Insulin Doses Based on CGM Trend Arrows in Adult Patients with Type 1 Diabetes: Results from an Exploratory Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:3945. [PMID: 36900956 PMCID: PMC10002216 DOI: 10.3390/ijerph20053945] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 02/16/2023] [Accepted: 02/20/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Continuous glucose monitoring (CGM) users are encouraged to consider trend arrows before injecting a meal bolus. We evaluated the efficacy and safety of two different algorithms for trend-informed bolus adjustments, the Diabetes Research in Children Network/Juvenile Diabetes Research Foundation (DirectNet/JDRF) and the Ziegler algorithm, in type 1 diabetes. METHODS We conducted a cross-over study of type 1 diabetes patients using Dexcom G6. Participants were randomly assigned to either the DirectNet/JDRF or the Ziegler algorithm for two weeks. After a 7-day wash-out period with no trend-informed bolus adjustments, they crossed to the alternative algorithm. RESULTS Twenty patients, with an average age of 36 ± 10 years, completed this study. Compared to the baseline and the DirectNet/JDRF algorithm, the Ziegler algorithm was associated with a significantly higher time in range (TIR) and lower time above range and mean glucose. A separate analysis of patients on CSII and MDI revealed that the Ziegler algorithm provides better glucose control and variability than DirectNet/JDRF in CSII-treated patients. The two algorithms were equally effective in increasing TIR in MDI-treated patients. No severe hypoglycemic or hyperglycemic episode occurred during the study. CONCLUSIONS The Ziegler algorithm is safe and may provide better glucose control and variability than the DirectNet/JDRF over a two-week period, especially in patients treated with CSII.
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Affiliation(s)
- Martina Parise
- Department of Health Science, University Magna Graecia, 88100 Catanzaro, Italy
| | - Sergio Di Molfetta
- Section of Internal Medicine, Endocrinology, Andrology, and Metabolic Diseases, Department of Precision and Regenerative Medicine and Ionian Area, University of Bari, 70121 Bari, Italy
| | | | | | - Antonio Cutruzzolà
- Department of Clinical and Experimental Medicine, University Magna Graecia, 88100 Catanzaro, Italy
| | - Agostino Gnasso
- Department of Clinical and Experimental Medicine, University Magna Graecia, 88100 Catanzaro, Italy
| | - Concetta Irace
- Department of Health Science, University Magna Graecia, 88100 Catanzaro, Italy
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13
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McCall AL, Lieb DC, Gianchandani R, MacMaster H, Maynard GA, Murad MH, Seaquist E, Wolfsdorf JI, Wright RF, Wiercioch W. Management of Individuals With Diabetes at High Risk for Hypoglycemia: An Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab 2023; 108:529-562. [PMID: 36477488 DOI: 10.1210/clinem/dgac596] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Indexed: 12/12/2022]
Abstract
CONTEXT Hypoglycemia in people with diabetes is common, especially in those taking medications such as insulin and sulfonylureas (SU) that place them at higher risk. Hypoglycemia is associated with distress in those with diabetes and their families, medication nonadherence, and disruption of life and work, and it leads to costly emergency department visits and hospitalizations, morbidity, and mortality. OBJECTIVE To review and update the diabetes-specific parts of the 2009 Evaluation and Management of Adult Hypoglycemic Disorders: Endocrine Society Clinical Practice Guideline and to address developing issues surrounding hypoglycemia in both adults and children living with diabetes. The overriding objectives are to reduce and prevent hypoglycemia. METHODS A multidisciplinary panel of clinician experts, together with a patient representative, and methodologists with expertise in evidence synthesis and guideline development, identified and prioritized 10 clinical questions related to hypoglycemia in people living with diabetes. Systematic reviews were conducted to address all the questions. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess the certainty of evidence and make recommendations. RESULTS The panel agreed on 10 questions specific to hypoglycemia risk and prevention in people with diabetes for which 10 recommendations were made. The guideline includes conditional recommendations for use of real-time continuous glucose monitoring (CGM) and algorithm-driven insulin pumps in people with type 1 diabetes (T1D), use of CGM for outpatients with type 2 diabetes at high risk for hypoglycemia, use of long-acting and rapid-acting insulin analogs, and initiation of and continuation of CGM for select inpatient populations at high risk for hypoglycemia. Strong recommendations were made for structured diabetes education programs for those at high risk for hypoglycemia, use of glucagon preparations that do not require reconstitution vs those that do for managing severe outpatient hypoglycemia for adults and children, use of real-time CGM for individuals with T1D receiving multiple daily injections, and the use of inpatient glycemic management programs leveraging electronic health record data to reduce the risk of hypoglycemia. CONCLUSION The recommendations are based on the consideration of critical outcomes as well as implementation factors such as feasibility and values and preferences of people with diabetes. These recommendations can be used to inform clinical practice and health care system improvement for this important complication for people living with diabetes.
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Affiliation(s)
- Anthony L McCall
- University of Virginia Medical School, Department of Medicine, Division of Endocrinology and Metabolism, Charlottesville, VA 22901, USA
| | - David C Lieb
- Eastern Virginia Medical School, Division of Endocrine and Metabolic Disorders, Department of Medicine, Norfolk, VA 23510, USA
| | | | | | | | - M Hassan Murad
- Mayo Clinic Evidence-Based Practice Center, Rochester, MN 55905, USA
| | - Elizabeth Seaquist
- Diabetes Center and the Division of Endocrinology & Metabolism, Minneapolis, MN 55455, USA
| | - Joseph I Wolfsdorf
- Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | | | - Wojtek Wiercioch
- McMaster University GRADE Centre and Michael G. DeGroote Cochrane Canada Centre Department of Health Research Methods, Evidence, and Impact, Hamilton, ON, L8S 4L8, Canada
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14
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Noaro G, Cappon G, Sparacino G, Boscari F, Bruttomesso D, Facchinetti A. Methods for Insulin Bolus Adjustment Based on the Continuous Glucose Monitoring Trend Arrows in Type 1 Diabetes: Performance and Safety Assessment in an In Silico Clinical Trial. J Diabetes Sci Technol 2023; 17:107-116. [PMID: 34486426 PMCID: PMC9846415 DOI: 10.1177/19322968211043162] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
BACKGROUND Providing real-time magnitude and direction of glucose rate-of-change (ROC) via trend arrows represents one of the major strengths of continuous glucose monitoring (CGM) sensors in managing type 1 diabetes (T1D). Several literature methods were proposed to adjust the standard formula (SF) used for insulin bolus calculation by accounting for glucose ROC, but each of them provides different suggestions, making it difficult to understand which should be applied in practice. This work aims at performing an extensive in-silico assessment of their performance and safety. METHODS The methods of Buckingham (BU), Scheiner (SC), Pettus/Edelman (PE), Klonoff/Kerr (KL), Aleppo/Laffel (AL), Ziegler (ZI), and Bruttomesso (BR) were evaluated using the UVa/Padova T1D simulator, in single-meal scenarios, where ROC and glucose at mealtime varied between [-2,+2] mg/dL/min and [80,200] mg/dL, respectively. Efficacy of postprandial glucose control was quantitatively assessed by time in, above and below range (TIR, TAR, and TBR, respectively). RESULTS For negative ROCs, all methods proved to increase TIR and decrease TAR and TBR vs SF, with KL, PE, and BR being the most effective. For positive ROCs, a general worsening of the performances is present, only BR improved the glycemic control when mealtime glucose was close to hypoglycemia, while SC resulted the safest in the other conditions. CONCLUSIONS Insulin bolus adjustment methods are effective for negative ROCs, but they generally appear to overdose for positive ROCs, calling for safer strategies in such a scenario. These results can be useful in outlining guidelines to identify which adjustment to apply based on the mealtime condition.
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Affiliation(s)
- Giulia Noaro
- Department of Information Engineering,
University of Padova, Padova, Italy
| | - Giacomo Cappon
- Department of Information Engineering,
University of Padova, Padova, Italy
| | - Giovanni Sparacino
- Department of Information Engineering,
University of Padova, Padova, Italy
| | | | | | - Andrea Facchinetti
- Department of Information Engineering,
University of Padova, Padova, Italy
- Andrea Facchinetti, Department of
Information Engineering, University of Padova, via Gradenigo, 6B, Padova 35131,
Italy.
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15
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Longo RR, Joshi R. The Devil Is in the Details: Use, Limitations, and Implementation of Continuous Glucose Monitoring in the Inpatient Setting. Diabetes Spectr 2022; 35:405-419. [PMID: 36561647 PMCID: PMC9668728 DOI: 10.2337/dsi22-0009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Until recently, continuous glucose monitoring (CGM) systems were reserved for use in the outpatient setting or for investigational purposes in hospitalized patients. However, during the coronavirus disease 2019 pandemic, use of CGM in the inpatient setting has grown rapidly. This review outlines important details related to the accuracy, limitations, and implementation of, as well as necessary staff education for, inpatient CGM use and offers a glimpse into the future of CGM in the inpatient setting.
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Affiliation(s)
- Rebecca Rick Longo
- Lahey Hospital and Medical Center–Beth Israel Lahey Health, Burlington, MA
| | - Renu Joshi
- University of Pittsburgh Medical Center, Harrisburg, PA
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16
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Subcutaneous amperometric biosensors for continuous glucose monitoring in diabetes. Talanta 2022. [DOI: 10.1016/j.talanta.2022.124033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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17
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Camerlingo N, Vettoretti M, Del Favero S, Facchinetti A, Choudhary P, Sparacino G. Generation of post-meal insulin correction boluses in type 1 diabetes simulation models for in-silico clinical trials: More realistic scenarios obtained using a decision tree approach. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2022; 221:106862. [PMID: 35597208 DOI: 10.1016/j.cmpb.2022.106862] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 04/19/2022] [Accepted: 05/07/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND AND OBJECTIVE In type 1 diabetes (T1D) research, in-silico clinical trials (ISCTs) notably facilitate the design/testing of new therapies. Published simulation tools embed mathematical models of blood glucose (BG) and insulin dynamics, continuous glucose monitoring (CGM) sensors, and insulin treatments, but lack a realistic description of some aspects of patient lifestyle impacting on glucose control. Specifically, to effectively simulate insulin correction boluses, required to treat post-meal hyperglycemia (BG > 180 mg/dL), the timing of the bolus may be influenced by subjects' behavioral attitudes. In this work, we develop an easily interpretable model of the variability of correction bolus timing observed in real data, and embed it into a popular simulation tool for ISCTs. METHODS Using data collected in 196 adults with T1D monitored in free-living conditions, we trained a decision tree (DT) model to classify whether a correction bolus is injected in a future time window, based on predictors collected back in time, related to CGM data, previous insulin boluses and subject's characteristics. The performance was compared to that of a logistic regression classifier with LASSO regularization (LC), trained on the same dataset. After validation, the DT was embedded within a popular T1D simulation tool and an ISCT was performed to compare the simulated correction boluses against those observed in a subset of data not used for model training. RESULTS The DT provided better classification performance (accuracy: 0.792, sensitivity: 0.430, specificity: 0.878, precision: 0.455) than the LC and presented good interpretability. The most predictive features were related to CGM (and its temporal variations), time since the last insulin bolus, and time of the day. The correction boluses simulated by the DT, after implementation in the simulation tool, showed a good agreement with real-world data. CONCLUSIONS The DT developed in this work represents a simple set of rules to mimic the same timing of correction boluses observed on real data. The inclusion of the model in simulation tools allows investigators to perform ISCTs that more realistically represent the patient behavior in taking correction boluses and the post-prandial BG response. In the future, more complex models can be investigated.
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Affiliation(s)
- N Camerlingo
- Department of Information Engineering, University of Padova, Via G. Gradenigo 6B, Padova 35131, Italy
| | - M Vettoretti
- Department of Information Engineering, University of Padova, Via G. Gradenigo 6B, Padova 35131, Italy
| | - S Del Favero
- Department of Information Engineering, University of Padova, Via G. Gradenigo 6B, Padova 35131, Italy
| | - A Facchinetti
- Department of Information Engineering, University of Padova, Via G. Gradenigo 6B, Padova 35131, Italy
| | - P Choudhary
- Department of Diabetes, Leicester Diabetes Centre, University of Leicester, Gwendolen Rd, Leicester LE5 4PW, United Kingdom
| | - G Sparacino
- Department of Information Engineering, University of Padova, Via G. Gradenigo 6B, Padova 35131, Italy.
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18
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Ahn DT. Automated Bolus Calculators and Connected Insulin Pens: A Smart Combination for Multiple Daily Injection Insulin Therapy. J Diabetes Sci Technol 2022; 16:605-609. [PMID: 34933594 PMCID: PMC9294589 DOI: 10.1177/19322968211062624] [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
Although automated bolus calculators (ABCs) have become a mainstay in insulin pump therapy, they have not achieved similar levels of adoption by persons with diabetes (PWD) using multiple daily injections of insulin (MDI). Only a small number of blood glucose meters (BGMs) have incorporated ABC functionality and the proliferation of unregulated ABC smartphone apps raised safety concerns and eventually led to Food and Drug Administration (FDA)-mandated regulatory oversight for these types of apps. With the recent introduction of smartphone-connected insulin pens, manufacturer-supported companion ABC apps may offer an ideal solution for PWD and health care professionals that reduces errors of mental math when calculating bolus insulin dosing, increases the quality of diabetes data reporting, and improves glycemic outcomes.
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Affiliation(s)
- David T Ahn
- Mary & Dick Allen Diabetes
Center, Hoag Memorial Hospital Presbyterian, Newport Beach, CA, USA
- David Ahn, MD, Mary & Dick
Allen Diabetes Center, Hoag Memorial Hospital Presbyterian, 520
Superior Avenue, Suite 150, Newport Beach, CA 92663, USA.
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19
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Marks BE, Williams KM, Sherwood JS, Putman MS. Practical aspects of diabetes technology use: Continuous glucose monitors, insulin pumps, and automated insulin delivery systems. J Clin Transl Endocrinol 2022; 27:100282. [PMID: 34917483 PMCID: PMC8666668 DOI: 10.1016/j.jcte.2021.100282] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 11/01/2021] [Accepted: 11/27/2021] [Indexed: 02/06/2023] Open
Abstract
There have been tremendous advances in diabetes technology in the last decade. Continuous glucose monitors (CGM), insulin pumps, and automated insulin delivery (AID) systems aim to improve glycemic control while simultaneously decreasing the burden of diabetes management. Although diabetes technologies have been shown to decrease both hypoglycemia and hyperglycemia and to improve health-related quality of life in individuals with type 1 diabetes, the impact of these devices in individuals with cystic fibrosis-related diabetes (CFRD) is less clear. There are unique aspects of CFRD, including the different underlying pathophysiology and unique lived health care experience and comorbidities, that likely affect the use, efficacy, and uptake of diabetes technology in this population. Small studies suggest that CGM is accurate and may be helpful in guiding insulin therapy for individuals with CFRD. Insulin pump use has been linked to improvements in lean body mass and hemoglobin A1c among adults with CFRD. A recent pilot study highlighted the promise of AID systems in this population. This article provides an overview of practical aspects of diabetes technology use and device limitations that clinicians must be aware of in caring for individuals with CF and CFRD. Cost and limited insurance coverage remain significant barriers to wider implementation of diabetes technology use among patients with CFRD. Future studies exploring strategies to improve patient and CF provider education about these devices and studies showing the effectiveness of these technologies on health and patient-reported outcomes may lead to improved insurance coverage and increased rates of uptake and sustained use of these technologies in the CFRD community.
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Affiliation(s)
- Brynn E. Marks
- Division of Endocrinology and Diabetes, Children’s National Hospital, 111 Michigan Ave, NW, Washington, DC 20010, USA
| | - Kristen M. Williams
- Division of Pediatric Endocrinology, Diabetes, and Metabolism, Columbia University Irving Medical Center, 1150 St Nicholas Avenue, New York, NY 10032, United States
| | - Jordan S. Sherwood
- Diabetes Research Center, Division of Pediatric Endocrinology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, United States
| | - Melissa S. Putman
- Division of Endocrinology, Boston Children’s Hospital, 300 Longwood Ave, Boston, MA 02115, United States
- Diabetes Research Center, Division of Endocrinology, Massachusetts General Hospital, 55 Fruit St, Boston, MA 02114, United States
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20
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Miller E, Gavin JR, Kruger DF, Brunton SA. Continuous Glucose Monitoring: Optimizing Diabetes Care: Executive Summary. Clin Diabetes 2022; 40:394-398. [PMID: 36385970 PMCID: PMC9622212 DOI: 10.2337/cd22-0043] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Eden Miller
- Diabetes Nation and Diabetes and Obesity Care, Bend, OR
| | | | - Davida F. Kruger
- Division of Endocrinology, Diabetes, Bone and Mineral Disease, Henry Ford Health System, Detroit, MI
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21
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Pinsker JE, Church MM, Brown SA, Voelmle MK, Bode BW, Narron B, Huyett LM, Lee JB, O'Connor J, Benjamin E, Dumais B, Ly TT. Clinical Evaluation of a Novel CGM-Informed Bolus Calculator with Automatic Glucose Trend Adjustment. Diabetes Technol Ther 2022; 24:18-25. [PMID: 34491825 PMCID: PMC8783627 DOI: 10.1089/dia.2021.0140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Background: Expert opinion guidelines and limited data from clinical trials recommend adjustment to bolus insulin doses based on continuous glucose monitor (CGM) trend data, yet minimal evidence exists to support this approach. We performed a clinical evaluation of a novel CGM-informed bolus calculator (CIBC) with automatic insulin bolus dose adjustment based on CGM trend used with sensor-augmented pump therapy. Materials and Methods: In this multicenter, outpatient study, participants 6-70 years of age with type 1 diabetes (T1D) used the Omnipod® 5 System in Manual Mode, first for 7 days without a connected CGM (standard bolus calculator, SBC, phase 1) and then for 7 days with a connected CGM using the CIBC (CIBC phase 2). The integrated bolus calculator used stored pump settings plus user-estimated meal size and/or either a manually entered capillary glucose value (SBC phase) or an imported current CGM value and trend (CIBC phase) to recommend a bolus amount. The CIBC automatically increased or decreased the suggested bolus amount based on the CGM trend. Results: Twenty-five participants, (mean ± standard deviation) 27 ± 15 years of age, with T1D duration 12 ± 9 years and A1C 7.0% ± 0.9% completed the study. There were significantly fewer sensor readings <70 mg/dL 4 h postbolus with the CIBC compared to the SBC (2.1% ± 2.0% vs. 2.8 ± 2.7, P = 0.03), while percent of sensor readings >180 and 70-180 mg/dL remained the same. There was no difference in insulin use or number of boluses given between the two phases. Conclusion: The CIBC was safe when used with the Omnipod 5 System in Manual Mode, with fewer hypoglycemic readings in the postbolus period compared to the SBC. This trial was registered at ClinicalTrials.gov (NCT04320069).
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Affiliation(s)
- Jordan E. Pinsker
- Sansum Diabetes Research Institute, Santa Barbara, California, USA
- Results of this study were presented in abstract form at the 14th International Conference on Advanced Technologies & Treatments for Diabetes, June 2021
| | - Mei Mei Church
- Sansum Diabetes Research Institute, Santa Barbara, California, USA
- Results of this study were presented in abstract form at the 14th International Conference on Advanced Technologies & Treatments for Diabetes, June 2021
| | - Sue A. Brown
- Division of Endocrinology, Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
- Results of this study were presented in abstract form at the 14th International Conference on Advanced Technologies & Treatments for Diabetes, June 2021
| | - Mary K. Voelmle
- Division of Endocrinology, Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
- Results of this study were presented in abstract form at the 14th International Conference on Advanced Technologies & Treatments for Diabetes, June 2021
| | - Bruce W. Bode
- Atlanta Diabetes Associates, Atlanta, Georgia, USA
- Results of this study were presented in abstract form at the 14th International Conference on Advanced Technologies & Treatments for Diabetes, June 2021
| | - Brooke Narron
- Atlanta Diabetes Associates, Atlanta, Georgia, USA
- Results of this study were presented in abstract form at the 14th International Conference on Advanced Technologies & Treatments for Diabetes, June 2021
| | - Lauren M. Huyett
- Insulet Corporation, Acton, Massachusetts, USA
- Results of this study were presented in abstract form at the 14th International Conference on Advanced Technologies & Treatments for Diabetes, June 2021
| | - Joon Bok Lee
- Insulet Corporation, Acton, Massachusetts, USA
- Results of this study were presented in abstract form at the 14th International Conference on Advanced Technologies & Treatments for Diabetes, June 2021
| | - Jason O'Connor
- Insulet Corporation, Acton, Massachusetts, USA
- Results of this study were presented in abstract form at the 14th International Conference on Advanced Technologies & Treatments for Diabetes, June 2021
| | - Eric Benjamin
- Insulet Corporation, Acton, Massachusetts, USA
- Results of this study were presented in abstract form at the 14th International Conference on Advanced Technologies & Treatments for Diabetes, June 2021
| | - Bonnie Dumais
- Insulet Corporation, Acton, Massachusetts, USA
- Results of this study were presented in abstract form at the 14th International Conference on Advanced Technologies & Treatments for Diabetes, June 2021
| | - Trang T. Ly
- Insulet Corporation, Acton, Massachusetts, USA
- Results of this study were presented in abstract form at the 14th International Conference on Advanced Technologies & Treatments for Diabetes, June 2021
- Address correspondence to: Trang T. Ly, MBBS, FRACP, PhD, Insulet Corporation, 100 Nagog Park, Acton, MA 01720, USA
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22
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Cappon G, Pighin E, Prendin F, Sparacino G, Facchinetti A. A Correction Insulin Bolus Delivery Strategy for Decision Support Systems in Type 1 Diabetes. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:1832-1835. [PMID: 34891643 DOI: 10.1109/embc46164.2021.9630052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Management of type 1 diabetes (T1D) requires affected individuals to perform multiple daily actions to keep their blood glucose levels within the safe rage and avoid adverse hypo-/hyperglycemic episodes. Decision support systems (DSS) for T1D are composite tools that implement multiple software modules aiming to ease such a burden and to improve glucose control. At the University of Padova, we are developing a new DSS that currently integrate a smart insulin bolus calculator for optimal insulin dosing and a rescue carbohydrate intake advisor to tackle hypoglycemia. However, a module specifically targeting hyperglycemia, that suggests the administration of corrective insulin boluses (CIB), is still missing. For such a scope, this work aims to assess a recent literature methodology, proposed by Aleppo et al., which provides a simple strategy for dealing with hyperglycemia. The methodology is tested retrospectively on clinical data of individuals with T1D. In particular, here we leveraged a novel in silico tool that first identifies a non-linear model of glucose-insulin dynamics on data, then uses such model to simulate and compare the glucose trace obtained by "replaying" the recorded scenario and the glucose trace obtained using the CIB delivery strategy under evaluation. Results show that the CIB delivery strategy significantly reduce the percentage of time spent in hyperglycemia (-15.63%) without inducing any hypoglycemic episode, demonstrating both safety and efficacy of its use. These preliminary results suggest that the CIB delivery strategy proposed by Aleppo et al. is a promising candidate to be included in our system to counteract hyperglycemia. Future work will extensively evaluate the methodology and will compare it against other competing approaches.
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23
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Elbarbary N, Moser O, Al yaarubi S, Alsaffar H, Al Shaikh A, Ajjan RA, Deeb A. Use of continuous glucose monitoring trend arrows in the younger population with type 1 diabetes. Diab Vasc Dis Res 2021; 18:14791641211062155. [PMID: 34898300 PMCID: PMC8671682 DOI: 10.1177/14791641211062155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Early control of glycaemia is key to reduce vascular complications in individuals with Type 1 diabetes. Therefore, encouraging children and adolescents with T1DM to take responsibility for controlling glucose levels is an important yet a challenging task. The rapid expansion of continuous glucose monitoring (CGM) systems has allowed for more comprehensive analysis of glycaemia in T1D. Moreover, CGM devices have the ability to calculate rate of change in glucose levels and display the information as trend arrows. In turn, this can help to take evasive actions to return glucose levels to near physiological glycaemia, which can be highly motivating for young people with T1DM. In the absence of standardised, evidence-based guidance, this consensus document, generated by experts from the Arab Society of Paediatric Endocrinology and Diabetes and international advisors, summarises recent literature on the use of trend arrows in young people with T1DM. The use of trend arrows in different CGM systems is reviewed and their clinical significance is highlighted. Adjusting insulin doses according to trend arrows is discussed while also addressing special situations, such as exercise, fasting, nocturnal hypoglycaemia and menstruation. Adequate understanding of trend arrows should facilitate optimisation of glycaemic control in the T1D population.
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Affiliation(s)
- Nancy Elbarbary
- Diabetes Unit, Department of Pediatrics, Faculty of Medicine, Ain Shams University, Cairo, Egypt
- Nancy Elbarbary, Professor of Pediatrics, Department of Pediatrics, Diabetes Unit, Faculty of Medicine, Ain Shams University, 25 Ahmed Fuad St. Saint Fatima, Heliopolis, Cairo 11361, Egypt.
| | - Othmar Moser
- Division Exercise Physiology and Metabolism, Department of Sport Science, University of Bayreuth, Bayreuth, Germany
- Trials Unit for Interdisciplinary Metabolic Medicine, Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Saif Al yaarubi
- Pediatric Endocrine Department, Sultan Qaboos University Hospital, College of Medicine, Seeb, Oman
| | - Hussain Alsaffar
- Paediatric Endocrine and Diabetics Unit, Department of Child Health, Sultan Qaboos University Hospital, Muscat, Oman
| | - Adnan Al Shaikh
- Pediatric Department, King Abdulaziz Medical City, King Saud Bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, Jeddah, Saudi Arabia
| | - Ramzi A Ajjan
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Asma Deeb
- Paediatric Endocrinology Department, Sheikh Shakhbout Medical City and Khalifa University Abu Dhabi, Abu Dhabi, UAE
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24
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Addala A, Zaharieva DP, Gu AJ, Prahalad P, Scheinker D, Buckingham B, Hood KK, Maahs DM. Clinically Serious Hypoglycemia Is Rare and Not Associated With Time-in-range in Youth With New-onset Type 1 Diabetes. J Clin Endocrinol Metab 2021; 106:3239-3247. [PMID: 34265059 PMCID: PMC8530719 DOI: 10.1210/clinem/dgab522] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Indexed: 02/06/2023]
Abstract
CONTEXT Early initiation of continuous glucose monitoring (CGM) is advocated for youth with type 1 diabetes (T1D). Data to guide CGM use on time-in-range (TIR), hypoglycemia, and the role of partial clinical remission (PCR) are limited. OBJECTIVE Our aims were to assess whether 1) an association between increased TIR and hypoglycemia exists, and 2) how time in hypoglycemia varies by PCR status. METHODS We analyzed 80 youth who were started on CGM shortly after T1D diagnosis and were followed for up to 1-year post diagnosis. TIR and hypoglycemia rates were determined by CGM data and retrospectively analyzed. PCR was defined as (visit glycated hemoglobin A1c) + (4*units/kg/day) less than 9. RESULTS Youth were started on CGM 8.0 (interquartile range, 6.0-13.0) days post diagnosis. Time spent at less than 70 mg/dL remained low despite changes in TIR (highest TIR 74.6 ± 16.7%, 2.4 ± 2.4% hypoglycemia at 1 month post diagnosis; lowest TIR 61.3 ± 20.3%, 2.1 ± 2.7% hypoglycemia at 12 months post diagnosis). No events of severe hypoglycemia occurred. Hypoglycemia was rare and there was minimal difference for PCR vs non-PCR youth (54-70 mg/dL: 1.8% vs 1.2%, P = .04; < 54mg/dL: 0.3% vs 0.3%, P = .55). Approximately 50% of the time spent in hypoglycemia was in the 65 to 70 mg/dL range. CONCLUSION As TIR gradually decreased over 12 months post diagnosis, hypoglycemia was limited with no episodes of severe hypoglycemia. Hypoglycemia rates did not vary in a clinically meaningful manner by PCR status. With CGM being started earlier, consideration needs to be given to modifying CGM hypoglycemia education, including alarm settings. These data support a trial in the year post diagnosis to determine alarm thresholds for youth who wear CGM.
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Affiliation(s)
- Ananta Addala
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, California, USA
- Correspondence: Ananta Addala, DO, MPH, Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, CA 94305, USA.
| | - Dessi P Zaharieva
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, California, USA
| | - Angela J Gu
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, California, USA
- Department of Management Science and Engineering, Stanford University, Stanford, California, USA
| | - Priya Prahalad
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, California, USA
- Stanford Diabetes Research Center, Stanford, California, USA
| | - David Scheinker
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, California, USA
- Department of Management Science and Engineering, Stanford University, Stanford, California, USA
- Stanford Diabetes Research Center, Stanford, California, USA
| | - Bruce Buckingham
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, California, USA
- Stanford Diabetes Research Center, Stanford, California, USA
| | - Korey K Hood
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, California, USA
- Stanford Diabetes Research Center, Stanford, California, USA
| | - David M Maahs
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, California, USA
- Stanford Diabetes Research Center, Stanford, California, USA
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25
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Hirsch IB, Miller E. Integrating Continuous Glucose Monitoring Into Clinical Practices and Patients' Lives. Diabetes Technol Ther 2021; 23:S72-S80. [PMID: 34546085 DOI: 10.1089/dia.2021.0233] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Numerous studies have demonstrated the clinical benefits of continuous glucose monitoring (CGM) in individuals with diabetes. Within ongoing innovations in CGM technology, individuals now have an expanding array of options that allow them to select the device that meets their individual needs and preferences. Although demand for CGM in primary care continues to grow, many clinicians are reluctant to prescribe this technology due to their unfamiliarity with the various devices, uncertainty about which devices are best suited to each patient and the feasibility of using CGM. This article reviews the features and functionality of the most recent commercially available CGM devices and provides guidance for integrating CGM use into clinical practices.
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Affiliation(s)
- Irl B Hirsch
- Division of Metabolism, Endocrinology and Nutrition, University of Washington School of Medicine, Seattle, Washington, USA
| | - Eden Miller
- Diabetes and Obesity Care, Bend, Oregon, USA
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26
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Peeks F, Hoogeveen IJ, Feldbrugge RL, Burghard R, de Boer F, Fokkert‐Wilts MJ, van der Klauw MM, Oosterveer MH, Derks TGJ. A retrospective in-depth analysis of continuous glucose monitoring datasets for patients with hepatic glycogen storage disease: Recommended outcome parameters for glucose management. J Inherit Metab Dis 2021; 44:1136-1150. [PMID: 33834518 PMCID: PMC8519135 DOI: 10.1002/jimd.12383] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 03/15/2021] [Accepted: 04/07/2021] [Indexed: 11/12/2022]
Abstract
Continuous glucose monitoring (CGM) systems have great potential for real-time assessment of glycemic variation in patients with hepatic glycogen storage disease (GSD). However, detailed descriptions and in-depth analysis of CGM data from hepatic GSD patients during interventions are scarce. This is a retrospective in-depth analysis of CGM parameters, acquired in a continuous, real-time fashion describing glucose management in 15 individual GSD patients. CGM subsets are obtained both in-hospital and at home, upon nocturnal dietary intervention (n = 1), starch loads (n = 11) and treatment of GSD Ib patients with empagliflozin (n = 3). Descriptive CGM parameters, and parameters reflecting glycemic variation and glycemic control are considered useful CGM outcome parameters. Furthermore, the combination of first and second order derivatives, cumulative sum and Fourier analysis identified both subtle and sudden changes in glucose management; hence, aiding assessment of dietary and medical interventions. CGM data interpolation for nocturnal intervals reduced confounding by physical activity and diet. Based on these analyses, we conclude that in-depth CGM analysis can be a powerful tool to assess glucose management and optimize treatment in individual hepatic GSD patients.
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Affiliation(s)
- Fabian Peeks
- Section of Metabolic DiseasesBeatrix Children's Hospital, University Medical Center Groningen, University of GroningenGroningenThe Netherlands
| | - Irene J. Hoogeveen
- Section of Metabolic DiseasesBeatrix Children's Hospital, University Medical Center Groningen, University of GroningenGroningenThe Netherlands
| | | | | | - Foekje de Boer
- Section of Metabolic DiseasesBeatrix Children's Hospital, University Medical Center Groningen, University of GroningenGroningenThe Netherlands
| | - Marieke J. Fokkert‐Wilts
- Section of Metabolic DiseasesBeatrix Children's Hospital, University Medical Center Groningen, University of GroningenGroningenThe Netherlands
| | - Melanie M. van der Klauw
- Department of EndocrinologyUniversity of Groningen, University Medical Center GroningenGroningenThe Netherlands
| | - Maaike H. Oosterveer
- Laboratory of PediatricsUniversity of Groningen, University Medical Center GroningenGroningenThe Netherlands
| | - Terry G. J. Derks
- Section of Metabolic DiseasesBeatrix Children's Hospital, University Medical Center Groningen, University of GroningenGroningenThe Netherlands
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Forlenza GP, Buckingham BA, Brown SA, Bode BW, Levy CJ, Criego AB, Wadwa RP, Cobry EC, Slover RJ, Messer LH, Berget C, McCoy S, Ekhlaspour L, Kingman RS, Voelmle MK, Boyd J, O'Malley G, Grieme A, Kivilaid K, Kleve K, Dumais B, Vienneau T, Huyett LM, Lee JB, O'Connor J, Benjamin E, Ly TT. First Outpatient Evaluation of a Tubeless Automated Insulin Delivery System with Customizable Glucose Targets in Children and Adults with Type 1 Diabetes. Diabetes Technol Ther 2021; 23:410-424. [PMID: 33325779 PMCID: PMC8215410 DOI: 10.1089/dia.2020.0546] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Background: The objective of this study was to assess the safety and effectiveness of the first commercial configuration of a tubeless automated insulin delivery system, Omnipod® 5, in children (6-13.9 years) and adults (14-70 years) with type 1 diabetes (T1D) in an outpatient setting. Materials and Methods: This was a single-arm, multicenter, prospective clinical study. Data were collected over a 14-day standard therapy (ST) phase followed by a 14-day hybrid closed-loop (HCL) phase, where participants (n = 36) spent 72 h at each of three prespecified glucose targets (130, 140, and 150 mg/dL, 9 days total) then 5 days with free choice of glucose targets (110-150 mg/dL) using the Omnipod 5. Remote safety monitoring alerts were enabled during the HCL phase. Primary endpoints were difference in time in range (TIR) (70-180 mg/dL) between ST and HCL phases and proportion of participants reporting serious device-related adverse events. Results: Mean TIR was significantly higher among children in the free-choice period overall (64.9% ± 12.2%, P < 0.01) and when using a 110 mg/dL target (71.2% ± 10.2%, P < 0.01), a 130 mg/dL target (61.5% ± 7.7%, P < 0.01), and a 140 mg/dL target (64.8% ± 11.6%, P < 0.01), and among adults using a 130 mg/dL target (75.1% ± 11.6%, P < 0.05), compared to the ST phase (children: 51.0% ± 13.3% and adults: 65.6% ± 15.7%). There were no serious device-related adverse events reported during the HCL phase, nor were there episodes of severe hypoglycemia or diabetic ketoacidosis. Conclusion: The Omnipod 5 System was safe and effective when used at glucose targets from 110 to 150 mg/dL for 14 days at home in children and adults with T1D.
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Affiliation(s)
- Gregory P. Forlenza
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Bruce A. Buckingham
- Department of Pediatrics, Division of Pediatric Endocrinology, Stanford University, Stanford, California, USA
| | - Sue A. Brown
- Division of Endocrinology and Medicine, University of Virginia, Charlottesville, Virginia, USA
| | | | - Carol J. Levy
- Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Amy B. Criego
- Department of Pediatric Endocrinology, Park Nicollet Clinic, International Diabetes Center at Park Nicollet, Minneapolis, Minnesota, USA
| | - R. Paul Wadwa
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Erin C. Cobry
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Robert J. Slover
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Laurel H. Messer
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Cari Berget
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Susan McCoy
- Barbara Davis Center for Diabetes, University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Laya Ekhlaspour
- Department of Pediatrics, Division of Pediatric Endocrinology, Stanford University, Stanford, California, USA
| | - Ryan S. Kingman
- Department of Pediatrics, Division of Pediatric Endocrinology, Stanford University, Stanford, California, USA
| | - Mary K. Voelmle
- Division of Endocrinology and Medicine, University of Virginia, Charlottesville, Virginia, USA
| | | | - Grenye O'Malley
- Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Aimee Grieme
- Department of Pediatric Endocrinology, Park Nicollet Clinic, International Diabetes Center at Park Nicollet, Minneapolis, Minnesota, USA
| | | | | | | | | | | | | | | | | | - Trang T. Ly
- Insulet Corporation, Acton, Massachusetts, USA
- Address correspondence to: Trang T. Ly, MBBS, FRACP, PhD, Insulet Corporation, 100 Nagog Park, Acton, MA 01720, USA
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Bruttomesso D, Boscari F, Lepore G, Noaro G, Cappon G, Girelli A, Bozzetto L, Tumminia A, Grassi G, Sparacino G, Laviola L, Facchinetti A. A "Slide Rule" to Adjust Insulin Dose Using Trend Arrows in Adults with Type 1 Diabetes: Test in Silico and in Real Life. Diabetes Ther 2021; 12:1313-1324. [PMID: 33725276 PMCID: PMC8099956 DOI: 10.1007/s13300-021-01020-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Accepted: 01/30/2021] [Indexed: 12/01/2022] Open
Abstract
INTRODUCTION In persons with type 1 diabetes (T1D) insulin dosing can be adjusted based on trend arrows derived from continuous glucose monitoring (CGM). We propose a slide rule with narrower blood glucose intervals and more classes of insulin sensitivity than are available in current models. METHODS The slide rule was tested in silico, in which a meal was simulated in 100 virtual subjects and the insulin bolus was calculated either in the standard way based on the insulin-to-carbohydrate ratio and the correction factor or according to the slide rule, following which the percentage time spent in range (70-180 mg/dl; %TIR), hypoglycemia (< 70 mg/dl; %THYPO), and hyperglycemia (> 180 mg/dl; %THYPER) was compared between the methods during the 4 h after the meal. Slide rule performance was also tested in real life by analyzing the same variables at during the 4 h postprandial period in 27 individuals with T1D. Only meals starting while the rate of change was at least 1 mg/dl per minute (increasing or decreasing) were considered for analysis. RESULTS In silico, when the preprandial trend arrow was increasing, our slide rule reduced %THYPER and increased %TIR (p < 0.05), whereas when the preprandial trend arrow was decreasing, it reduced %THYPO and slightly increased %THYPER (p < 0.05). In real life, our slide rule kept subjects on target for 70.8 and 91.6% of postprandial time when preprandial trend arrows were increasing or decreasing, respectively. CONCLUSION The proposed slide rule performed well both in silico and in real life, suggesting that it could be safely adopted by individuals with T1D to improve glucose control.
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Affiliation(s)
- Daniela Bruttomesso
- Unit of Metabolic Diseases, Department of Medicine, University of Padova, Padova, Italy.
| | - Federico Boscari
- Unit of Metabolic Diseases, Department of Medicine, University of Padova, Padova, Italy
| | - Giuseppe Lepore
- Unit of Endocrine Diseases and Diabetology, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Giulia Noaro
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Giacomo Cappon
- Department of Information Engineering, University of Padova, Padova, Italy
| | | | - Lutgarda Bozzetto
- Department of Clinical Medicine and Surgery, Federico II University, Napoli, Italy
| | - Andrea Tumminia
- Endocrinology, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy
| | - Giorgio Grassi
- Department of Endocrinology, Diabetology, and Metabolism, Città della Salute e della Scienza University Hospital, Torino, Italy
| | - Giovanni Sparacino
- Department of Information Engineering, University of Padova, Padova, Italy
| | - Luigi Laviola
- Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy
| | - Andrea Facchinetti
- Department of Information Engineering, University of Padova, Padova, Italy
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29
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Waldenmaier D, Freckmann G, Pleus S, Hermanns N, Ehrmann D, Heinemann L, Haug C. Therapy adjustments in people with type 1 diabetes with impaired hypoglycemia awareness on multiple daily injections using real-time continuous glucose monitoring: a mechanistic analysis of the HypoDE study. BMJ Open Diabetes Res Care 2021; 9:9/1/e001848. [PMID: 33863716 PMCID: PMC8055114 DOI: 10.1136/bmjdrc-2020-001848] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 02/26/2021] [Accepted: 03/28/2021] [Indexed: 11/29/2022] Open
Abstract
INTRODUCTION Studies have shown beneficial effects of real-time continuous glucose monitoring (rtCGM) usage on clinical outcomes. The objective of this analysis was to identify which therapy adjustments were made by people with type 1 diabetes with impaired hypoglycemia awareness during rtCGM usage enabling reductions in the number of low glucose events observed in the HypoDE (Hypoglycemia in Deutschland) study. RESEARCH DESIGN AND METHODS In the multicenter randomized controlled trial in people with type 1 diabetes on multiple daily injections with impaired hypoglycemia awareness, participants recorded their diabetes therapy in 7-day logbooks at baseline and at 6-month follow-up. They used rtCGM or self-monitoring of blood glucose for therapy adjustments. This mechanistic analysis looked at changes in various aspects of therapy. RESULTS Logbooks were completed by 70 participants in the rtCGM group and 65 participants in the control group. Participants in the rtCGM group kept their total carbohydrate consumption, daily insulin doses and distribution constant during the study. However, they reported an increased intake of rescue carbohydrates (0.8±0.6 (mean±SD) vs 1.0±0.8 intake/day; baseline-adjusted between-group difference 0.3 intake (0.1-0.5), p=0.031). The glucose threshold at which rescue carbohydrate intake was initiated was elevated from 71±13 mg/dL (3.9±0.7 mmol/L) to 79±14 mg/dL (4.4±0.8 mmol/L) (adjusted between-group difference +7.6 mg/dL (2.4-12.8) (+0.4 mmol/L (0.1-0.7)); p=0.005) in the rtCGM group. Regression analysis showed that follow-up low glucose events were associated with group allocation (p<0.001), low glucose events at baseline (p=0.016) and rescue threshold (p=0.001). CONCLUSIONS No major adjustments in insulin therapy were made by study participants with impaired hypoglycemia awareness; however, they were more active in preventing hypoglycemia by taking rescue carbohydrates earlier and more often. TRIAL REGISTRATION NUMBER NCT02671968.
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Affiliation(s)
- Delia Waldenmaier
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Guido Freckmann
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Stefan Pleus
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Norbert Hermanns
- Research Institute of the Diabetes Academy Mergentheim, Bad Mergentheim, Germany
| | - Dominic Ehrmann
- Research Institute of the Diabetes Academy Mergentheim, Bad Mergentheim, Germany
| | | | - Cornelia Haug
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
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Edelman SV, Cavaiola TS, Boeder S, Pettus J. Utilizing continuous glucose monitoring in primary care practice: What the numbers mean. Prim Care Diabetes 2021; 15:199-207. [PMID: 33257275 DOI: 10.1016/j.pcd.2020.10.013] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Revised: 10/26/2020] [Accepted: 10/31/2020] [Indexed: 12/17/2022]
Abstract
Use of continuous glucose monitoring (CGM) has been shown to improve glycemia control, reduce hypoglycemia, lower glycemic variability and enhance quality of life for individuals with type 1 diabetes and type 2 diabetes. However, many primary care physicians may be unfamiliar with the how CGM data can interpreted and acted upon. As adoption of this technology continues to grow, primary care physicians will be challenged to integrate CGM into their clinical practices. This article is intended to provide clinicians with practical guidance in interpreting and utilizing CGM data with their patients.
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Affiliation(s)
- Steven V Edelman
- University of California San Diego and Taking Control of Your Diabetes 501c3, San Diego, CA 92161, USA.
| | - Tricia Santos Cavaiola
- Department of Medicine, Clinical and Translational Research Institute (CTRI), San Diego, CA 92161, USA.
| | - Schafer Boeder
- Department of Medicine, Clinical and Translational Research Institute (CTRI), University of California SanDiego, San Diego, CA 92161, USA.
| | - Jeremy Pettus
- Department of Medicine, Clinical and Translational Research Institute (CTRI), University of California SanDiego, San Diego, CA 92161, USA.
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Deeb A, Muammar T, Alsaffar H, Sedaghat S, Al Hassani N, Odeh R, Alkhayyat H, Al Sinani A, Attia N, Adhami S, Elbarbary N. Use of ambulatory glucose monitoring and analysis of ambulatory glucose profile in clinical practice for diabetes management; a position statement of the Arab Society of Paediatric Endocrinology and diabetes. Diabetes Res Clin Pract 2021; 173:108671. [PMID: 33493578 DOI: 10.1016/j.diabres.2021.108671] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Revised: 01/03/2021] [Accepted: 01/12/2021] [Indexed: 12/15/2022]
Abstract
BACKGROUND AND AIM Diabetes mellitus imposes a significant burden around the world generally and in the Middle East and North Africa specifically. Glucose monitoring is a cornerstone of diabetes management. METHODS Glycated haemoglobin has always been the main metric for assessing glycaemic control, but its use is linked with multiple pitfalls. As an alternative, continuous glucose monitoring is becoming a standard of care in many countries. Intermittent scanning glucose monitoring (isCGM) has acquired a worldwide popularity and has been proven to improve glycaemic control, hypoglycaemia detection and prevention, and quality of life. RESULTS The most recent International Society of Paediatric and Adolescent Diabetes practice. guidelines recommended its use in young people with diabetes observing Ramadan to ensure safe fasting. At a meeting in Abu Dhabi in November 2019, the Arab Society for Paediatric. Endocrinology and Diabetes brought together a number of regional diabetes experts, patient. representatives and international expert advisors to review the evidence for isCGM and propose. guidelines for its use in the Middle East and North Africa region. CONCLUSION In this paper, the authors strongly recommend the use of isCGM for patients in MENA and present general recommendations and compressive specific guidance for physicians and patients, which they believe will also have wider resonance.
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Affiliation(s)
- Asma Deeb
- Paediatric Endocrinology Department, Sheikh Shakhbout Medical City, Abu Dhabi, United Arab Emirates
| | - Tawfik Muammar
- Imperial College London Diabetes Centre, Abu Dhabi, United Arab Emirates
| | - Hussain Alsaffar
- Paediatric Endocrine and Diabetics Unit, Department of Child Health, Sultan Qaboos University Hospital, Muscat, Oman
| | | | - Noura Al Hassani
- Department of Paediatrics, Tawam Hospital and UAE College of Medicine and Health Sciences, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Rasha Odeh
- Department of Paediatrics, School of Medicine, University of Jordan, Amman, Jordan
| | - Haya Alkhayyat
- Bahrain Defence Force Royal Medical Services Military Hospital, West Riffa, Kingdom of Bahrain, Kingdom of Bahrain, Royal College of Surgeons in Ireland Medical University of Bahrain, Adliya, Bahrain
| | - Aisha Al Sinani
- National Diabetic and Endocrine Center, Royal Hospital, Muscat, Oman
| | - Najya Attia
- King Abdulaziz Medical City, Riyadh, Saudi Arabia
| | - Sarah Adhami
- Mediclinic City Hospital, Dubai, United Arab Emirates
| | - Nancy Elbarbary
- Diabetes Unit, Department of Pediatrics, Faculty of medicine, Ain Shams University, Cairo, Egypt.
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Rodacki M, Calliari LE, Ramalho AC, Vianna AGD, Franco DR, Melo KFS, Araujo LR, Krakauer M, Scharf M, Minicucci W, Ziegler R, Gabbay M. Using trend arrows in continuous glucose monitoring systems for insulin adjustment in clinical practice: Brazilian Diabetes Society Position Statement. Diabetol Metab Syndr 2021; 13:2. [PMID: 33390180 PMCID: PMC7780381 DOI: 10.1186/s13098-020-00607-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 11/03/2020] [Indexed: 11/24/2022] Open
Abstract
This manuscript reports the Brazilian Diabetes Society Position Statement for insulin adjustments based on trend arrows observed in continuous glucose monitoring systems. The Brazilian Diabetes Society supports the utilization of trend arrows for insulin dose adjustments in patients with diabetes on basal-bolus insulin therapy, both with multiple daily insulin doses or insulin pumps without closed-loop features. For those on insulin pumps with predictive low-glucose suspend feature, we suggest that only upward trend arrows should be used for adjustments. In this paper, tables for insulin adjustment based on sensitivity factors are provided and strategies to optimize the use of trend arrows in clinical practice are discussed.
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Affiliation(s)
- M Rodacki
- Department of Internal Medicine, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, RJ, Brazil.
| | - L E Calliari
- Pediatric Endocrinology Unit, Pediatric Department, Santa Casa de São Paulo School of Mediccal Sciences, São Paulo, Brazil
| | - A C Ramalho
- Department of Endocrinology, Federal University of Bahia, Salvador, BA, Brazil
| | - A G D Vianna
- Curitiba Diabetes Center, Hospital Nossa Senhora das Graças, Curitiba, PR, Brazil
| | - D R Franco
- CPCLIN/DASA Clinical Research Center, São Paulo, Brazil
| | - K F S Melo
- Diabetes Secion, Hospital das Clinicas, University of São Paulo (USP), Quasar Telemedicine (Glic), São Paulo, Brazil
| | - L R Araujo
- Endocrinology Section, School of Medical Sciences, Belo Horizonte, MG, Brazil
| | - M Krakauer
- Diabetes and Endocrinology, Science Valley Research Institute, Santo André, SP, Brazil
| | - M Scharf
- Curitiba Diabetes Center, Hospital Nossa Senhora das Graças, Curitiba, PR, Brazil
| | - W Minicucci
- Endocrinology Section, University of Campinas (UNICAMP), Campinas, SP, Brazil
| | - R Ziegler
- Diabetes Clinic for Children and Adolescents, Munster, Germany
| | - M Gabbay
- Diabetes Centre-UNIFESP, Federal University of São Paulo, São Paulo, Brazil
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Noaro G, Cappon G, Vettoretti M, Sparacino G, Favero SD, Facchinetti A. Machine-Learning Based Model to Improve Insulin Bolus Calculation in Type 1 Diabetes Therapy. IEEE Trans Biomed Eng 2021; 68:247-255. [DOI: 10.1109/tbme.2020.3004031] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Piras de Oliveira C, Mitchell BD, Fan L, Garey C, Liao B, Bispham J, Vint N, Perez-Nieves M, Hughes A, McAuliffe-Fogarty A. Patient perspectives on the use of half-unit insulin pens by people with type 1 diabetes: a cross-sectional observational study. Curr Med Res Opin 2021; 37:45-51. [PMID: 33108218 DOI: 10.1080/03007995.2020.1843423] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
BACKGROUND Half-unit pens offer the ability to dose insulin more precisely. Information about half-unit pen use and evidence of their benefits and drawbacks is limited. This study aims to characterize people with type 1 diabetes (T1D) who have used (current/former = EVER) vs. those who have never used half-unit pens (NEVER users) and to understand their perspective. METHODS An observational cross-sectional online survey was administered through T1D Exchange's online patient community, myGlu.org, to understand the use of half-unit insulin pens. RESULTS The 278 adult participants (156 EVER, 122 NEVER) had a mean age of 41.8 ± 12.7 years, body mass index of 26.0 ± 3.8 kg/m2, glycated hemoglobin of 6.3% ± 1.0%, and 55% were male. EVER users had T1D for a shorter duration than NEVER users (p < .001). EVER users were less likely to use continuous subcutaneous insulin infusion (p < .001) and more likely to start correcting high blood glucose at a lower level (p < .001) and low blood glucose at a higher level (p < .001). The highest ranked benefits of half-unit pen reported by its current users (N = 131) included prevention of hyperglycemia (40.5%), less anxiety or worry (23.7%), and prevention of hypoglycemia (16.8%). CONCLUSIONS Half-unit insulin pen is perceived as an insulin device that may help people with T1D to avoid hypo- and hyperglycemic events and decrease their level of disease worry and anxiety. This study highlights the need for patients and health care providers to understand the benefits of half-unit pens while considering options for individualized diabetes management.
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Affiliation(s)
| | | | - Ludi Fan
- Eli Lilly and Company, Indianapolis, IN, USA
| | | | - Birong Liao
- Eli Lilly and Company, Indianapolis, IN, USA
| | | | - Nan Vint
- Eli Lilly and Company, Indianapolis, IN, USA
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Abstract
Continuous glucose monitoring is poised to radically change the treatment of diabetes and patient engagement of those afflicted with this disease. This article will provide an overview of CGM and equip health care providers to begin integrating this technology into their clinical practice.
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36
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Kushner PR, Kruger DF. The Changing Landscape of Glycemic Targets: Focus on Continuous Glucose Monitoring. Clin Diabetes 2020; 38:348-356. [PMID: 33132504 PMCID: PMC7566931 DOI: 10.2337/cd19-0093] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Continuous glucose monitoring (CGM) provides comprehensive assessment of daily glucose measurements for patients with diabetes and can reveal high and low blood glucose values that may occur even when a patient's A1C is adequately controlled. Among the measures captured by CGM, the percentage of time in the target glycemic range, or "time in range" (typically 70-180 mg/dL), has emerged as one of the strongest indicators of good glycemic control. This review examines the shift to using CGM to assess glycemic control and guide diabetes treatment decisions, with a focus on time in range as the key metric of glycemic control.
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Chan AJ, Halperin IJ. Beyond Glycated Hemoglobin: Harnessing Data From Sensor-Based Technology to Improve Glucose Variability, Time in Range and Hypoglycemia in Adult Patients With Type 1 Diabetes. Can J Diabetes 2020; 45:269-272.e3. [PMID: 33046398 DOI: 10.1016/j.jcjd.2020.08.103] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 07/25/2020] [Accepted: 08/21/2020] [Indexed: 12/19/2022]
Affiliation(s)
- Alvita J Chan
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada.
| | - Ilana J Halperin
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada; Division of Endocrinology, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
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Lundholm MD, Emanuele MA, Ashraf A, Nadeem S. Applications and pitfalls of hemoglobin A1C and alternative methods of glycemic monitoring. J Diabetes Complications 2020; 34:107585. [PMID: 32553575 DOI: 10.1016/j.jdiacomp.2020.107585] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 04/08/2020] [Accepted: 04/08/2020] [Indexed: 12/21/2022]
Abstract
INTRODUCTION Intensive glycemic control minimizes the risks of microvascular complications in diabetes. A1C is a convenient estimate of mean blood glucose, but is not the only marker available. The practical use and limitations of alternative markers and continuous glucose monitors are the focus of this review. METHODS PubMed and the Cochrane Library were searched for studies concerning applications or limitations of A1C, fructosamine, glycated albumin, 1,5-anhydroglucitol, skin autofluorescence, and continuous glucose monitoring. Papers reporting on strengths, limitations, or comparisons of these methods were reviewed for inclusion. RESULTS A1C reflects three months of glycemic control and is not an ideal marker in all patient populations. Fructosamine and glycated albumin reflect mean blood glucose over three weeks. 1,5-Anhydroglucitol can measure hyperglycemic excursions in days to weeks. Continuous glucose monitors provide immediate feedback for timely intervention to reduce glycemic excursions and can assess glycemic variability. Current barriers to continuous glucose monitor use include inexperience, cost, discomfort, and medication interference. CONCLUSIONS Many promising alternative glycemic markers exist. The main limitations for all alternative methods of glycemic monitoring are a lack of standardization for clinically useful cut-offs or guidelines, and a lack of long-term data on their association with complications, particularly in varied patient populations.
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Affiliation(s)
- Michelle D Lundholm
- Department of Internal Medicine, Loyola University Medical Center, Maywood, IL, USA
| | - Mary Ann Emanuele
- Department of Medicine, Division of Endocrinology, Loyola University Health Care System, Maywood, IL, USA.
| | - Alina Ashraf
- Aga Khan University Medical College, Karachi, Sindh, Pakistan
| | - Sarah Nadeem
- Department of Medicine, Division of Endocrinology, Aga Khan University Hospital, Karachi, Sindh, Pakistan
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Pratley RE, Kanapka LG, Rickels MR, Ahmann A, Aleppo G, Beck R, Bhargava A, Bode BW, Carlson A, Chaytor NS, Fox DS, Goland R, Hirsch IB, Kruger D, Kudva YC, Levy C, McGill JB, Peters A, Philipson L, Philis-Tsimikas A, Pop-Busui R, Shah VN, Thompson M, Vendrame F, Verdejo A, Weinstock RS, Young L, Miller KM. Effect of Continuous Glucose Monitoring on Hypoglycemia in Older Adults With Type 1 Diabetes: A Randomized Clinical Trial. JAMA 2020; 323:2397-2406. [PMID: 32543682 PMCID: PMC7298607 DOI: 10.1001/jama.2020.6928] [Citation(s) in RCA: 227] [Impact Index Per Article: 45.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
IMPORTANCE Continuous glucose monitoring (CGM) provides real-time assessment of glucose levels and may be beneficial in reducing hypoglycemia in older adults with type 1 diabetes. OBJECTIVE To determine whether CGM is effective in reducing hypoglycemia compared with standard blood glucose monitoring (BGM) in older adults with type 1 diabetes. DESIGN, SETTING, AND PARTICIPANTS Randomized clinical trial conducted at 22 endocrinology practices in the United States among 203 adults at least 60 years of age with type 1 diabetes. INTERVENTIONS Participants were randomly assigned in a 1:1 ratio to use CGM (n = 103) or standard BGM (n = 100). MAIN OUTCOMES AND MEASURES The primary outcome was CGM-measured percentage of time that sensor glucose values were less than 70 mg/dL during 6 months of follow-up. There were 31 prespecified secondary outcomes, including additional CGM metrics for hypoglycemia, hyperglycemia, and glucose control; hemoglobin A1c (HbA1c); and cognition and patient-reported outcomes, with adjustment for multiple comparisons to control for false-discovery rate. RESULTS Of the 203 participants (median age, 68 [interquartile range {IQR}, 65-71] years; median type 1 diabetes duration, 36 [IQR, 25-48] years; 52% female; 53% insulin pump use; mean HbA1c, 7.5% [SD, 0.9%]), 83% used CGM at least 6 days per week during month 6. Median time with glucose levels less than 70 mg/dL was 5.1% (73 minutes per day) at baseline and 2.7% (39 minutes per day) during follow-up in the CGM group vs 4.7% (68 minutes per day) and 4.9% (70 minutes per day), respectively, in the standard BGM group (adjusted treatment difference, -1.9% (-27 minutes per day); 95% CI, -2.8% to -1.1% [-40 to -16 minutes per day]; P <.001). Of the 31 prespecified secondary end points, there were statistically significant differences for all 9 CGM metrics, 6 of 7 HbA1c outcomes, and none of the 15 cognitive and patient-reported outcomes. Mean HbA1c decreased in the CGM group compared with the standard BGM group (adjusted group difference, -0.3%; 95% CI, -0.4% to -0.1%; P <.001). The most commonly reported adverse events using CGM and standard BGM, respectively, were severe hypoglycemia (1 and 10), fractures (5 and 1), falls (4 and 3), and emergency department visits (6 and 8). CONCLUSIONS AND RELEVANCE Among adults aged 60 years or older with type 1 diabetes, continuous glucose monitoring compared with standard blood glucose monitoring resulted in a small but statistically significant improvement in hypoglycemia over 6 months. Further research is needed to understand the long-term clinical benefit. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT03240432.
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Affiliation(s)
| | | | - Michael R. Rickels
- Rodebaugh Diabetes Center, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | | | - Grazia Aleppo
- Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Roy Beck
- Jaeb Center for Health Research, Tampa, Florida
| | - Anuj Bhargava
- Iowa Diabetes and Endocrinology Research Center, Des Moines
| | | | - Anders Carlson
- Park Nicollet International Diabetes Center, Minneapolis, Minnesota
| | - Naomi S. Chaytor
- Elson S. Floyd College of Medicine, Washington State University, Spokane
| | - D. Steven Fox
- University of South California, School of Pharmacy, Los Angeles
| | - Robin Goland
- Naomi Berri Diabetes Center, Columbia University, New York, New York
| | | | | | | | - Carol Levy
- Icahn School of Medicine at Mount Sinai, New York, New York
| | - Janet B. McGill
- Washington University School of Medicine in St Louis, St Louis, Missouri
| | - Anne Peters
- Keck School of Medicine, University of Southern California, Los Angeles
| | | | | | | | - Viral N. Shah
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora
| | | | | | | | | | - Laura Young
- University of North Carolina at Chapel Hill, Chapel Hill
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40
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Moorman JM. Part I: Continuous glucose monitoring systems. JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY 2020. [DOI: 10.1002/jac5.1260] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Unger J, Kushner P, Anderson JE. Practical guidance for using the FreeStyle Libre flash continuous glucose monitoring in primary care. Postgrad Med 2020; 132:305-313. [PMID: 32223687 DOI: 10.1080/00325481.2020.1744393] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Use of continuous glucose monitoring (CGM) improves clinical outcomes in type 1 diabetes, and significant benefits been demonstrated in patients with type 2 diabetes, including improved glycemic control, better treatment adherence, and an increased understanding of their treatment regimens. Currently, there are two types of CGM systems: real-time CGM (rtCGM) and flash CGM (FCGM). Retrospective analysis of CGM data allows patients and their clinicians to identify glycemic patterns that support and facilitate informed therapy decisions. With the increasing prevalence of diabetes, primary care physicians will be compelled to take on more responsibility for managing patients with diabetes. This article focuses on practical approaches and decision-making strategies for utilizing FCGM in primary care settings.
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Affiliation(s)
- Jeff Unger
- Unger Primary Care , Rancho Cucamonga, CA, USA
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Kravarusic J, Aleppo G. Diabetes Technology Use in Adults with Type 1 and Type 2 Diabetes. Endocrinol Metab Clin North Am 2020; 49:37-55. [PMID: 31980120 DOI: 10.1016/j.ecl.2019.10.006] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
In the last 2 decades, diabetes technology has emerged as a branch of diabetes management thanks to the advent of continuous glucose monitoring (CGM) and increased availability of continuous subcutaneous insulin infusion systems, or insulin pumps. These tools have progressed from rudimentary instruments to sophisticated therapeutic options for advanced diabetes management. This article discusses the available CGM and insulin pump systems and the clinical benefits of their use in adults with type 1 diabetes, intensively insulin-treated type 2 diabetes, and pregnant patients with preexisting diabetes.
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Affiliation(s)
- Jelena Kravarusic
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, 645 North Michigan Avenue, Suite 530, Chicago, IL 60611, USA
| | - Grazia Aleppo
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, 645 North Michigan Avenue, Suite 530, Chicago, IL 60611, USA.
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Corathers SD, DeSalvo DJ. Therapeutic Inertia in Pediatric Diabetes: Challenges to and Strategies for Overcoming Acceptance of the Status Quo. Diabetes Spectr 2020; 33:22-30. [PMID: 32116450 PMCID: PMC7026749 DOI: 10.2337/ds19-0017] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Despite significant advances in therapies for pediatric type 1 diabetes, achievement of glycemic targets remains elusive, and management remains burdensome for patients and their families. This article identifies common challenges in diabetes management at the patient-provider and health care system levels and proposes practical approaches to overcoming therapeutic inertia to enhance health outcomes for youth with type 1 diabetes.
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Affiliation(s)
- Sarah D. Corathers
- Division of Endocrinology, Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH
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45
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Stone JY, Bailey TS. Benefits and limitations of continuous glucose monitoring in type 1 diabetes. Expert Rev Endocrinol Metab 2020; 15:41-49. [PMID: 31928104 DOI: 10.1080/17446651.2020.1706482] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2019] [Accepted: 12/16/2019] [Indexed: 12/14/2022]
Abstract
Introduction: Type 1 diabetes (T1D) is a chronic condition characterized by a complete deficiency in insulin production. Optimal management requires constant knowledge of glucose levels for safe and effective insulin administration. Self-monitoring of blood glucose (SMBG) using capillary blood glucose meters is cumbersome and provides limited information to guide management. Continuous glucose monitoring (CGM) technology addresses many of these gaps, but itself has limitations which have prevented people with diabetes and their clinicians from fully embracing this technology. This review covers the benefits and limitations of CGM use, and looks toward future application of this technology in the management of T1D.Areas covered: Impact of CGM on physical and psychosocial outcomes in people with T1D. Barriers to CGM uptake. Integration with insulin pumps and other technologies. Opportunities for future application.Expert opinion: CGM technology will be utilized by the majority of people with T1D and increasing numbers of people with type 2 diabetes due to improved insurance coverage and easier-to-use systems. Its use as part of artificial pancreas systems will add further utility, as it will help to protect from both hypoglycemia and hyperglycemia. People with diabetes will spend more time in range and experience fewer acute and chronic complications.
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Affiliation(s)
- Jenine Y Stone
- AMCR Institute, Escondido, CA, USA
- Vanderbilt University School of Nursing, Nashville, TN, USA
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Chico A, Aguilera E, Ampudia-Blasco FJ, Bellido V, Cardona-Hernández R, Escalada FJ, Fernández D, Gómez-Peralta F, González Pérez de Villar N, Gorgojo JJ, Mezquita-Raya P, Morales C, de Pablos Velasco P, Palomares R, Parra J, Rivero MT, González-Blanco C. Clinical Approach to Flash Glucose Monitoring: An Expert Recommendation. J Diabetes Sci Technol 2020; 14:155-164. [PMID: 31081362 PMCID: PMC7189166 DOI: 10.1177/1932296819841911] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
The flash glucose monitoring (FGM) system FreeStyle Libre® is a device that measures interstitial glucose in a very simple way and indicates direction and speed of glucose change. This allows persons with diabetes to prevent hypoglycemic and hyperglycemic events. Scientific evidence indicates that the system can improve glycemic control and quality of life. To obtain the maximum benefit, it is necessary to properly handle glucose values and trends. Due to the generalization of the system use, the purpose of the document is to provide recommendations for the optimal use of the device, not only in the management of glucose values and trends but also in the prevention of hypoglycemia, actuation in exercise, special situations, and retrospective analysis of the glucose data, among others.
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Affiliation(s)
- Ana Chico
- Endocrinology Department, Hospital Santa
Creu i Sant Pau, CIBER-BBN, Universitat Autònoma de Barcelona, Barcelona,
Spain
- Ana Isabel Chico, MD, PhD, Endocrinology
Department, Hospital Santa Creu i Sant Pau, Av Pare Claret 167, 08025
Barcelona,, Spain.
| | - Eva Aguilera
- Endocrinology Department, Hospital
Germans Trias i Pujol, Badalona, Spain
| | | | - Virgina Bellido
- Endocrinology Department, Hospital
Universitario Central de Asturias, Oviedo, Spain
| | - Roque Cardona-Hernández
- Division of Pediatric Endocrinology,
Diabetes Unit, Hospital Sant Joan de Déu, Esplugues de Llobregat, Barcelona,
Spain
| | | | - Diego Fernández
- Endocrinology Department, Hospital
Universitario Virgen de la Victoria, Málaga, Spain
| | | | | | - Juan José Gorgojo
- Endocrinology Department, Hospital
Universitario Fundación Alcorcón, Alcorcón, Madrid, Spain
| | - Pedro Mezquita-Raya
- Endocrinology Department, Hospital
Universitario Torrecárdenas, Almería, Spain
| | - Cristóbal Morales
- Endocrinology Department, Hospital
Universitario Virgen de la Macarena, Sevilla, Spain
| | | | - Rafael Palomares
- Endocrinologist, Hospital
Universitario Reina Sofía, Córdoba, Spain
| | - Juan Parra
- Endocrinology Department, Hospital de
Mérida, Mérida, Badajoz, Spain
| | - María Teresa Rivero
- Endocrinology Department, Complexo
Hospitalario Universitario de Ourense, Orense, Spain
| | - Cintia González-Blanco
- Endocrinology Department, Hospital Santa
Creu i Sant Pau, CIBER-BBN, Universitat Autònoma de Barcelona, Barcelona,
Spain
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47
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Abstract
Regular self-monitoring of blood glucose levels, and ketones when indicated, is an essential component of type 1 diabetes (T1D) management. Although fingerstick blood glucose monitoring has been the standard of care for decades, ongoing rapid technological developments have resulted in increasingly widespread use of continuous glucose monitoring (CGM). This article reviews recommendations for self-monitoring of glucose and ketones in pediatric T1D with particular emphasis on CGM and factors that impact the accuracy and real-world use of this technology.
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Affiliation(s)
- Brynn E. Marks
- Division of Endocrinology and Diabetes, Children's National Hospital, Washington, DC, United States
- *Correspondence: Brynn E. Marks
| | - Joseph I. Wolfsdorf
- Division of Endocrinology, Boston Children's Hospital, Boston, MA, United States
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48
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Beck RW, Bergenstal RM, Laffel LM, Pickup JC. Advances in technology for management of type 1 diabetes. Lancet 2019; 394:1265-1273. [PMID: 31533908 DOI: 10.1016/s0140-6736(19)31142-0] [Citation(s) in RCA: 153] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 04/26/2019] [Accepted: 05/01/2019] [Indexed: 01/07/2023]
Abstract
Technological advances have had a major effect on the management of type 1 diabetes. In addition to blood glucose meters, devices used by people with type 1 diabetes include insulin pumps, continuous glucose monitors, and, most recently, systems that combine both a pump and a monitor for algorithm-driven automation of insulin delivery. In the next 5 years, as many advances are expected in technology for the management of diabetes as there have been in the past 5 years, with improvements in continuous glucose monitoring and more available choices of systems that automate insulin delivery. Expansion of the use of technology will be needed beyond endocrinology practices to primary-care settings and broader populations of patients. Tools to support decision making will also need to be developed to help patients and health-care providers to use the output of these devices to optimise diabetes management.
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Affiliation(s)
- Roy W Beck
- Jaeb Center for Health Research, Tampa, FL, USA.
| | - Richard M Bergenstal
- International Diabetes Center, Park Nicollet and Health Partners, Minneapolis, MN, USA
| | - Lori M Laffel
- Joslin Diabetes Center, Harvard Medical School, Boston, MA, USA
| | - John C Pickup
- King's College London, Faculty of Life Sciences and Medicine, Guy's Hospital, London, UK
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49
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Leahy J(JL, Aleppo G, Fonseca VA, Garg SK, Hirsch IB, McCall AL, McGill JB, Polonsky WH. Optimizing Postprandial Glucose Management in Adults With Insulin-Requiring Diabetes: Report and Recommendations. J Endocr Soc 2019; 3:1942-1957. [PMID: 31608313 PMCID: PMC6781941 DOI: 10.1210/js.2019-00222] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Accepted: 09/20/2019] [Indexed: 02/06/2023] Open
Abstract
Faster-acting insulins, new noninsulin drug classes, more flexible insulin-delivery systems, and improved continuous glucose monitoring devices offer unprecedented opportunities to improve postprandial glucose (PPG) management and overall care for adults with insulin-treated diabetes. These developments led the Endocrine Society to convene a working panel of diabetes experts in December 2018 to assess the current state of PPG management, identify innovative ways to improve self-management and quality of life, and align best practices to current and emerging treatment and monitoring options. Drawing on current research and collective clinical experience, we considered the following issues for the ∼200 million adults worldwide with type 1 and insulin-requiring type 2 diabetes: (i) the role of PPG management in reducing the risk of diabetes complications; (ii) barriers preventing effective PPG management; (iii) strategies to reduce PPG excursions and improve patient quality of life; and (iv) education and clinical tools to support endocrinologists in improving PPG management. We concluded that managing PPG to minimize or prevent diabetes-related complications will require elucidating fundamental questions about optimal ways to quantify and clinically assess the metabolic dysregulation and consequences of the abnormal postprandial state in diabetes and recommend research strategies to address these questions. We also identified practical strategies and tools that are already available to reduce barriers to effective PPG management, optimize use of new and emerging clinical tools, and improve patient self-management and quality of life.
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Affiliation(s)
| | - Grazia Aleppo
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Vivian A Fonseca
- Tulane University Health Sciences Center, New Orleans, Louisiana
| | | | - Irl B Hirsch
- Treatment and Teaching Chair, University of Washington School of Medicine, Seattle, Washington
| | - Anthony L McCall
- University of Virginia School of Medicine, Charlottesville, Virginia
- Cornell University, Ithaca, New York
| | - Janet B McGill
- Washington University School of Medicine, St. Louis, Missouri
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50
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Fantasia K, Modzelewski K, Steenkamp D. Predictive Glucose Trends From Continuous Glucose Monitoring: Friend or Foe in Clinical Decision Making? J Diabetes Sci Technol 2019; 13:963-966. [PMID: 30636438 PMCID: PMC6955446 DOI: 10.1177/1932296818823538] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
In this commentary, we briefly review the currently recommended approaches to interpretation and management of continuous glucose monitor (CGM) rate of change (ROC) trend arrows and discuss the inherent difficulty in incorporating practical recommendations for their application into routine clinical care. We have limited our review and discussion to the currently available Dexcom G5 and G6 CGM systems and Abbott's Freestyle Libre flash glucose monitor (FGM) system, as they are the most widely used and currently approved for nonadjunctive use in the United States.
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Affiliation(s)
- Kathryn Fantasia
- Section of Endocrinology, Diabetes, and Nutrition, Boston University School of Medicine and Boston Medical Center, Boston, MA, USA
- Kathryn Fantasia, MD, Boston Medical Center, 720 Harrison Ave, Ste 8100, Boston, MA 02118, USA.
| | - Katherine Modzelewski
- Section of Endocrinology, Diabetes, and Nutrition, Boston University School of Medicine and Boston Medical Center, Boston, MA, USA
| | - Devin Steenkamp
- Section of Endocrinology, Diabetes, and Nutrition, Boston University School of Medicine and Boston Medical Center, Boston, MA, USA
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