Literature DB >> 31169432

Utilizing the Ambulatory Glucose Profile to Standardize and Implement Continuous Glucose Monitoring in Clinical Practice.

Mary L Johnson1, Thomas W Martens2, Amy B Criego3, Anders L Carlson4, Gregg D Simonson1, Richard M Bergenstal1.   

Abstract

Use of continuous glucose monitoring (CGM) is recognized as a valuable component of diabetes self-management and is increasingly considered a standard of care for individuals with diabetes who are treated with intensive insulin therapy. As the clinical use of CGM technology expands, consistent and standardized glycemic metrics and glucose profile visualization have become increasingly important. A common set of CGM metrics has been proposed by an international expert panel in 2017, including standard definitions of time in ranges, glucose variability, and adequacy of data collection. We describe the core CGM metrics, as well as the standardized glucose profile format consolidating 2 weeks of CGM measurements, referred to as the ambulatory glucose profile (AGP), which was also recommended by the CGM expert panel. We present an updated AGP report featuring the core CGM metrics and a visualization of glucose patterns that need clinical attention. New tools for use by clinicians and patients to interpret AGP data are reviewed. Strategies based on the authors' experience in implementing CGM technology across the clinical care spectrum are highlighted.

Entities:  

Keywords:  Ambulatory glucose profile; Continuous glucose monitoring; Diabetes technology; Glucose monitoring.

Mesh:

Substances:

Year:  2019        PMID: 31169432     DOI: 10.1089/dia.2019.0034

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  12 in total

1.  Unproven Glycemic Variability and Hypoglycemia Outcomes in I HART Study in High-Risk Adults with Type 1 Diabetes: Comment on Avari et al.

Authors:  Alexander Seibold
Journal:  J Diabetes Sci Technol       Date:  2020-02-13

2.  Clinical Application of Time in Range and Other Metrics.

Authors:  Grazia Aleppo
Journal:  Diabetes Spectr       Date:  2021-05-25

3.  Effect of Professional CGM (pCGM) on Glucose Management in Type 2 Diabetes Patients in Primary Care.

Authors:  Gregg D Simonson; Richard M Bergenstal; Mary L Johnson; Janet L Davidson; Thomas W Martens
Journal:  J Diabetes Sci Technol       Date:  2021-03-10

4.  Comparing Patch vs Pen Bolus Insulin Delivery in Type 2 Diabetes Using Continuous Glucose Monitoring Metrics and Profiles.

Authors:  Richard M Bergenstal; Mary L Johnson; Vanita R Aroda; Ronald L Brazg; Darlene M Dreon; Juan P Frias; Davida F Kruger; Mark E Molitch; Deborah M Mullen; Mark Peyrot; Sara Richter; Julio Rosenstock; Pierre Serusclat; Carl Vance; Ruth S Weinstock; Brian L Levy
Journal:  J Diabetes Sci Technol       Date:  2021-05-19

5.  Impacts of glycemic variability on the relationship between glucose management indicator from iPro2 and laboratory hemoglobin A1c in adult patients with type 1 diabetes mellitus.

Authors:  Hongxia Liu; Daizhi Yang; Hongrong Deng; Wen Xu; Jing Lv; Yongwen Zhou; Sihui Luo; Xueying Zheng; Hua Liang; Bin Yao; Liling Qiu; Funeng Wang; Fang Liu; Jinhua Yan; Jianping Weng
Journal:  Ther Adv Endocrinol Metab       Date:  2020-06-08       Impact factor: 3.565

6.  Artificial Intelligence in Health Care: Focus on Diabetes Management.

Authors:  Ambika G Unnikrishnan
Journal:  Indian J Endocrinol Metab       Date:  2019 Sep-Oct

7.  Time in Range: How to Measure It, How to Report It, and Its Practical Application in Clinical Decision-Making.

Authors:  Eugene E Wright; Kayla Morgan; Danny K Fu; Nick Wilkins; William J Guffey
Journal:  Clin Diabetes       Date:  2020-12

8.  Time in range-A1c hemoglobin relationship in continuous glucose monitoring of type 1 diabetes: a real-world study.

Authors:  Marina Valenzano; Ivan Cibrario Bertolotti; Adriano Valenzano; Giorgio Grassi
Journal:  BMJ Open Diabetes Res Care       Date:  2021-01

9.  Population-level management of type 1 diabetes via continuous glucose monitoring and algorithm-enabled patient prioritization: Precision health meets population health.

Authors:  Johannes O Ferstad; Jacqueline J Vallon; Daniel Jun; Angela Gu; Anastasiya Vitko; Dianelys P Morales; Jeannine Leverenz; Ming Yeh Lee; Brianna Leverenz; Christos Vasilakis; Esli Osmanlliu; Priya Prahalad; David M Maahs; Ramesh Johari; David Scheinker
Journal:  Pediatr Diabetes       Date:  2021-09-01       Impact factor: 3.409

10.  Diabetes Technology Meeting 2020.

Authors:  Trisha Shang; Jennifer Y Zhang; B Wayne Bequette; Jennifer K Raymond; Gerard Coté; Jennifer L Sherr; Jessica Castle; John Pickup; Yarmela Pavlovic; Juan Espinoza; Laurel H Messer; Tim Heise; Carlos E Mendez; Sarah Kim; Barry H Ginsberg; Umesh Masharani; Rodolfo J Galindo; David C Klonoff
Journal:  J Diabetes Sci Technol       Date:  2021-07
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