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210907 r ||| eng |
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|a Hirsch, Irl B.
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|a Role of continuous glucose monitoring in diabetes treatment
|h Elektronische Ressource
|c Irl B. Hirsch [and 5 others]
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260 |
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|a Arlington, VA
|b American Diabetes Association
|c 2018, 2018
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300 |
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|a 1 PDF file (24 pages)
|b illustrations
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|a Includes bibliographical references
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|a Blood Glucose Self-Monitoring / methods
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|a Blood Glucose Self-Monitoring / instrumentation
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653 |
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|a Glucose Metabolism Disorders / therapy
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|a Diabetes Mellitus / blood
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|a American Diabetes Association
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|a eng
|2 ISO 639-2
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|b NCBI
|a National Center for Biotechnology Information
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|u https://www.ncbi.nlm.nih.gov/books/NBK538971
|3 Volltext
|n NLM Bookshelf Books
|3 Volltext
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|a 610
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|a Diabetes-focused technologies are rapidly advancing, giving people with diabetes greater control with regard to self-management and clinicians and educators more tools to help their patients. Continuous glucose monitoring (CGM) is perhaps the best example of such advances. This compendium provides insights into CGM and its evidence base, best practices for its most effective use, and recent developments, including the latest nonintrusive "flash" CGM (FCGM) technology. Editor and lead author Irl B. Hirsch, MD, opens with a succinct history of glucose monitoring, from the first attempts to quantify blood glucose in the mid-1800s to the development of CGM devices in the 1990s and the FCGM system introduced in 2017. Tadej Battelino, MD, PhD, describes the evolution in research and development that allowed CGM to be commercialized and improved. Anne L. Peters, MD, offers a comprehensive review of the clinical trials providing solid evidence of its benefits. James C. Chamberlain, MD, describes available CGM systems and provides a guide to identifying appropriate patients from a diverse group of potential candidates who may benefit from CGM use. Grazia Aleppo, MD, FACE, FACP, explains the key factors involved in achieving successful outcomes with CGM, from matching patients to the device most appropriate for their needs to ensuring adequate education for both providers and patients and acting on data to adjustment diabetes treatment as needed. Richard M. Bergenstal, MD, defines Time in Range (TIR) and other CGM data metrics, explains the correlation between TIR and A1C, and provides a step-by-step guide to using the Ambulatory Glucose Profile report to provide personalized diabetes management. The compendium concludes with description of the future of CGM.
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