Literature DB >> 25316714

Evaluating quality of glycemic control: graphical displays of hypo- and hyperglycemia, time in target range, and mean glucose.

David Rodbard1.   

Abstract

There is need for readily understandable graphical displays of glucose data to facilitate interpretation by clinicians and researchers. (1) Display of the percentage of glucose values above a specified threshold for hyperglycemia (%High) versus percentage of glucose values below a specified threshold for hypoglycemia (%Low). If all glucose values fell within the target range, then all data points would fall at the origin. (2) After an intervention, one can plot the change in percentage of glucose values above a specified threshold for hyperglycemia versus the change in percentage of glucose values below a specified threshold defining hypoglycemia: The quadrants of this graph correspond to (a) increased risk of both hyper- and hypoglycemia, (b) decreased hyperglycemia but increased risk of hypoglycemia, (c) decreases in both hypo- and hyperglycemia, and (d) decreased hypoglycemia but increased hyperglycemia. (3) A 2-dimensional triangular graph can be used for simultaneous display of %High, %Low, and percentage in target range. (4) Display of risk of hyper- versus risk of hypoglycemia based on both frequency and severity of departures from the target range can be used. (5) Graphs (1) and (4) can also be presented using percentile scores relative to a reference population. (6) It is also useful to analyze %Hypoglycemia or risk of hypoglycemia versus mean glucose. These methods are illustrated with examples from representative cases and shown to be feasible, practical, and informative. These new types of graphical displays can facilitate rapid analysis of risks of hypo- and hypoglycemia simultaneously and responses to therapeutic interventions for individuals or in clinical trials.
© 2014 Diabetes Technology Society.

Entities:  

Keywords:  continuous glucose monitoring; diabetes mellitus; glycemic control; hyperglycemia; hypoglycemia; self-monitoring of blood glucose

Mesh:

Substances:

Year:  2014        PMID: 25316714      PMCID: PMC4495532          DOI: 10.1177/1932296814551046

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  24 in total

1.  Use of continuous glucose monitoring in young children with type 1 diabetes: implications for behavioral research.

Authors:  Susana R Patton; Laura B Williams; Sally J Eder; Megan J Crawford; Lawrence Dolan; Scott W Powers
Journal:  Pediatr Diabetes       Date:  2011-02       Impact factor: 4.866

Review 2.  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

3.  Statistical tools to analyze continuous glucose monitor data.

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

4.  Responses to continuous glucose monitoring in subjects with type 1 diabetes using continuous subcutaneous insulin infusion or multiple daily injections.

Authors:  David Rodbard; Lois Jovanovic; Satish K Garg
Journal:  Diabetes Technol Ther       Date:  2009-12       Impact factor: 6.118

5.  Standardization versus customization of glucose reporting.

Authors:  David Rodbard
Journal:  Diabetes Technol Ther       Date:  2013-05       Impact factor: 6.118

6.  Evaluation of a new measure of blood glucose variability in diabetes.

Authors:  Boris P Kovatchev; Erik Otto; Daniel Cox; Linda Gonder-Frederick; William Clarke
Journal:  Diabetes Care       Date:  2006-11       Impact factor: 19.112

7.  Outpatient glycemic control with a bionic pancreas in type 1 diabetes.

Authors:  Steven J Russell; Firas H El-Khatib; Manasi Sinha; Kendra L Magyar; Katherine McKeon; Laura G Goergen; Courtney Balliro; Mallory A Hillard; David M Nathan; Edward R Damiano
Journal:  N Engl J Med       Date:  2014-06-15       Impact factor: 91.245

8.  Ambulatory glucose profile: representation of verified self-monitored blood glucose data.

Authors:  R S Mazze; D Lucido; O Langer; K Hartmann; D Rodbard
Journal:  Diabetes Care       Date:  1987 Jan-Feb       Impact factor: 19.112

9.  Reduced daily risk of glycemic variability: comparison of exenatide with insulin glargine.

Authors:  Anthony L McCall; Daniel J Cox; Robert Brodows; John Crean; Don Johns; Boris Kovatchev
Journal:  Diabetes Technol Ther       Date:  2009-06       Impact factor: 6.118

10.  Characterizing glucose exposure for individuals with normal glucose tolerance using continuous glucose monitoring and ambulatory glucose profile analysis.

Authors:  Roger S Mazze; Ellie Strock; David Wesley; Sarah Borgman; Blaine Morgan; Richard Bergenstal; Robert Cuddihy
Journal:  Diabetes Technol Ther       Date:  2008-06       Impact factor: 6.118

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  12 in total

1.  Evaluating Glucose Control With a Novel Composite Continuous Glucose Monitoring Index.

Authors:  Lalantha Leelarathna; Hood Thabit; Malgorzata E Wilinska; Lia Bally; Julia K Mader; Thomas R Pieber; Carsten Benesch; Sabine Arnolds; Terri Johnson; Lutz Heinemann; Norbert Hermanns; Mark L Evans; Roman Hovorka
Journal:  J Diabetes Sci Technol       Date:  2019-03-31

Review 2.  Continuous Glucose Monitoring: A Review of Successes, Challenges, and Opportunities.

Authors:  David Rodbard
Journal:  Diabetes Technol Ther       Date:  2016-02       Impact factor: 6.118

3.  The Relationships Between Time in Range, Hyperglycemia Metrics, and HbA1c.

Authors:  Roy W Beck; Richard M Bergenstal; Peiyao Cheng; Craig Kollman; Anders L Carlson; Mary L Johnson; David Rodbard
Journal:  J Diabetes Sci Technol       Date:  2019-01-13

4.  Enhancing Glycemic Control via Detection of Insulin Using Electrochemical Impedance Spectroscopy.

Authors:  Aldin Malkoc; David Probst; Chi Lin; Mukund Khanwalker; Connor Beck; Curtiss B Cook; Jeffrey T La Belle
Journal:  J Diabetes Sci Technol       Date:  2017-03-16

5.  Sensitivity of Traditional and Risk-Based Glycemic Variability Measures to the Effect of Glucose-Lowering Treatment in Type 2 Diabetes Mellitus.

Authors:  Boris Kovatchev; Guillermo Umpierrez; Andres DiGenio; Rong Zhou; Silvio E Inzucchi
Journal:  J Diabetes Sci Technol       Date:  2015-06-15

Review 6.  Continuous Glucose Monitoring: A Review of Recent Studies Demonstrating Improved Glycemic Outcomes.

Authors:  David Rodbard
Journal:  Diabetes Technol Ther       Date:  2017-06       Impact factor: 6.118

7.  The Comprehensive Glucose Pentagon: A Glucose-Centric Composite Metric for Assessing Glycemic Control in Persons With Diabetes.

Authors:  Robert A Vigersky; John Shin; Boyi Jiang; Thorsten Siegmund; Chantal McMahon; Andreas Thomas
Journal:  J Diabetes Sci Technol       Date:  2017-07-27

8.  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

Review 9.  Glucose variability, HbA1c and microvascular complications.

Authors:  Jan Škrha; Jan Šoupal; Jan Škrha; Martin Prázný
Journal:  Rev Endocr Metab Disord       Date:  2016-03       Impact factor: 6.514

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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