Literature DB >> 28585873

A Simple Composite Metric for the Assessment of Glycemic Status from Continuous Glucose Monitoring Data: Implications for Clinical Practice and the Artificial Pancreas.

Irl B Hirsch1, Andrew K Balo2, Kevin Sayer2, Arturo Garcia2, Bruce A Buckingham3, Thomas A Peyser4.   

Abstract

BACKGROUND: The potential clinical benefits of continuous glucose monitoring (CGM) have been recognized for many years, but CGM is used by a small fraction of patients with diabetes. One obstacle to greater use of the technology is the lack of simplified tools for assessing glycemic control from CGM data without complicated visual displays of data.
METHODS: We developed a simple new metric, the personal glycemic state (PGS), to assess glycemic control solely from continuous glucose monitoring data. PGS is a composite index that assesses four domains of glycemic control: mean glucose, glycemic variability, time in range and frequency and severity of hypoglycemia. The metric was applied to data from six clinical studies for the G4 Platinum continuous glucose monitoring system (Dexcom, San Diego, CA). The PGS was also applied to data from a study of artificial pancreas comparing results from open loop and closed loop in adolescents and in adults.
RESULTS: The new metric for glycemic control, PGS, was able to characterize the quality of glycemic control in a wide range of study subjects with various mean glucose, minimal, moderate, and excessive glycemic variability and subjects on open loop versus closed loop control.
CONCLUSION: A new composite metric for the assessment of glycemic control based on CGM data has been defined for use in assessing glycemic control in clinical practice and research settings. The new metric may help rapidly identify problems in glycemic control and may assist with optimizing diabetes therapy during time-constrained physician office visits.

Entities:  

Keywords:  Artificial pancreas.; Composite metric; Continuous glucose monitoring; Glycemic state; Glycemic variability

Mesh:

Substances:

Year:  2017        PMID: 28585873      PMCID: PMC5467104          DOI: 10.1089/dia.2017.0080

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


  28 in total

1.  A proposal for a new method of evaluation of the newborn infant.

Authors:  V APGAR
Journal:  Curr Res Anesth Analg       Date:  1953 Jul-Aug

Review 2.  Glycemic variability: it's not just about A1C anymore!

Authors:  Irl B Hirsch
Journal:  Diabetes Technol Ther       Date:  2005-10       Impact factor: 6.118

3.  Improved glycemic control in poorly controlled patients with type 1 diabetes using real-time continuous glucose monitoring.

Authors:  Dorothee Deiss; Jan Bolinder; Jean-Pierre Riveline; Tadej Battelino; Emanuele Bosi; Nadia Tubiana-Rufi; David Kerr; Moshe Phillip
Journal:  Diabetes Care       Date:  2006-12       Impact factor: 19.112

Review 4.  Interpretation of continuous glucose monitoring data: glycemic variability and quality of glycemic control.

Authors:  David Rodbard
Journal:  Diabetes Technol Ther       Date:  2009-06       Impact factor: 6.118

5.  Statistical tools to analyze continuous glucose monitor data.

Authors:  William Clarke; Boris Kovatchev
Journal:  Diabetes Technol Ther       Date:  2009-06       Impact factor: 6.118

6.  The role of reimbursement in the adoption of continuous glucose monitors.

Authors:  Amanda Bartelme; Perry Bridger
Journal:  J Diabetes Sci Technol       Date:  2009-07-01

7.  The "glucose pentagon": assessing glycemic control of patients with diabetes mellitus by a model integrating different parameters from glucose profiles.

Authors:  Andreas Thomas; Martin Schönauer; Frank Achermann; Oliver Schnell; Markolf Hanefeld; Hans-Jürgen Ziegelasch; John Mastrototaro; Lutz Heinemann
Journal:  Diabetes Technol Ther       Date:  2009-06       Impact factor: 6.118

8.  Continuous glucose monitoring and intensive treatment of type 1 diabetes.

Authors:  William V Tamborlane; Roy W Beck; Bruce W Bode; Bruce Buckingham; H Peter Chase; Robert Clemons; Rosanna Fiallo-Scharer; Larry A Fox; Lisa K Gilliam; Irl B Hirsch; Elbert S Huang; Craig Kollman; Aaron J Kowalski; Lori Laffel; Jean M Lawrence; Joyce Lee; Nelly Mauras; Michael O'Grady; Katrina J Ruedy; Michael Tansey; Eva Tsalikian; Stuart Weinzimer; Darrell M Wilson; Howard Wolpert; Tim Wysocki; Dongyuan Xing
Journal:  N Engl J Med       Date:  2008-09-08       Impact factor: 91.245

9.  Glucose variability is associated with intensive care unit mortality.

Authors:  Jeroen Hermanides; Titia M Vriesendorp; Robert J Bosman; Durk F Zandstra; Joost B Hoekstra; J Hans Devries
Journal:  Crit Care Med       Date:  2010-03       Impact factor: 7.598

10.  Translating the A1C assay into estimated average glucose values.

Authors:  David M Nathan; Judith Kuenen; Rikke Borg; Hui Zheng; David Schoenfeld; Robert J Heine
Journal:  Diabetes Care       Date:  2008-06-07       Impact factor: 19.112

View more
  9 in total

1.  Assessment of Glucose Control Metrics by Discriminant Ratio.

Authors:  Vanessa Moscardó; Pau Herrero; Monika Reddy; Nathan R Hill; Pantelis Georgiou; Nick Oliver
Journal:  Diabetes Technol Ther       Date:  2020-10       Impact factor: 6.118

2.  The Future of Continuous Glucose Monitoring.

Authors:  Satish K Garg; Halis K Akturk
Journal:  Diabetes Technol Ther       Date:  2017-06       Impact factor: 6.118

3.  Glycemic Variability Percentage: A Novel Method for Assessing Glycemic Variability from Continuous Glucose Monitor Data.

Authors:  Thomas A Peyser; Andrew K Balo; Bruce A Buckingham; Irl B Hirsch; Arturo Garcia
Journal:  Diabetes Technol Ther       Date:  2017-12-11       Impact factor: 6.118

4.  A Review of Continuous Glucose Monitoring-Based Composite Metrics for Glycemic Control.

Authors:  Michelle Nguyen; Julia Han; Elias K Spanakis; Boris P Kovatchev; David C Klonoff
Journal:  Diabetes Technol Ther       Date:  2020-03-04       Impact factor: 6.118

5.  Updated Software for Automated Assessment of Glucose Variability and Quality of Glycemic Control in Diabetes.

Authors:  Vanessa Moscardó; Marga Giménez; Nick Oliver; Nathan R Hill
Journal:  Diabetes Technol Ther       Date:  2020-04-22       Impact factor: 6.118

6.  Diabetes Healthcare Professionals Use Multiple Continuous Glucose Monitoring Data Indicators to Assess Glucose Management.

Authors:  Tong Sheng; Reid Offringa; David Kerr; Mark Clements; Jerome Fischer; Linda Parks; Michael Greenfield
Journal:  J Diabetes Sci Technol       Date:  2019-09-06

7.  Calculating the Mean Amplitude of Glycemic Excursions from Continuous Glucose Data Using an Open-Code Programmable Algorithm Based on the Integer Nonlinear Method.

Authors:  Xuefei Yu; Liangzhuo Lin; Jie Shen; Zhi Chen; Jun Jian; Bin Li; Sherman Xuegang Xin
Journal:  Comput Math Methods Med       Date:  2018-03-08       Impact factor: 2.238

8.  Glycemic deviation index: a novel method of integrating glycemic numerical value and variability.

Authors:  Yizhou Zou; Wanli Wang; Dongmei Zheng; Xu Hou
Journal:  BMC Endocr Disord       Date:  2021-03-19       Impact factor: 2.763

9.  Towards a Rational Balanced Pancreatic and Islet Allocation Schema.

Authors:  Fouad Kandeel; Mohamed El-Shahawy; Gagandeep Singh; Donald C Dafoe; Jeffrey S Isenberg; Arthur D Riggs
Journal:  Cell Transplant       Date:  2021 Jan-Dec       Impact factor: 4.064

  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.