Literature DB >> 20144393

Display of glucose distributions by date, time of day, and day of week: new and improved methods.

David Rodbard1.   

Abstract

OBJECTIVE: There is a need for improved methods for display of glucose distributions to facilitate comparisons by date, time of day, day of the week, and other variables for data obtained using self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM).
METHOD: Stacked bar charts are utilized for multiple ranges of glucose values, e.g., very low, low, borderline low, target range, borderline high, high, and very high. Glucose ranges for these categories can be defined by the user, e.g., <40, 40-70, 71-80, 81-140, 141-180, 181-250, and 251-400 mg/dl. Glucose distributions can be displayed by time of day, in relation to meals, by date, or by day of week. The graphic display can be generated using general purpose spreadsheet software such as Microsoft Excel or with special purpose software. RESULT: Stacked bar charts are extremely compact and effective. They facilitate comparison of multiple days, multiple time segments within a day, preprandial and postprandial glucose levels, days of the week, treatment periods, patients, and groups of patients. They are superior to use of pie charts in terms of compactness and in their ability to facilitate comparisons using multiple criteria and multiple subsets of the data. One can identify episodes of hypoglycemia and hyperglycemia and can display standard errors of estimates of percentages. Interpretation of these graphs is readily learned and requires minimal training.
CONCLUSION: Use of stacked bar charts is generally superior to use of pie charts for display of glucose distributions and can potentially facilitate the analysis and interpretation of SMBG and CGM data.

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Year:  2009        PMID: 20144393      PMCID: PMC2787039          DOI: 10.1177/193229680900300619

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


  9 in total

1.  New approaches to display of self-monitoring of blood glucose data.

Authors:  David Rodbard
Journal:  J Diabetes Sci Technol       Date:  2009-09-01

2.  A semilogarithmic scale for glucose provides a balanced view of hyperglycemia and hypoglycemia.

Authors:  David Rodbard
Journal:  J Diabetes Sci Technol       Date:  2009-11-01

3.  Optimizing display, analysis, interpretation and utility of self-monitoring of blood glucose (SMBG) data for management of patients with diabetes.

Authors:  David Rodbard
Journal:  J Diabetes Sci Technol       Date:  2007-01

Review 4.  Potential role of computers in clinical investigation and management of diabetes mellitus.

Authors:  D Rodbard
Journal:  Diabetes Care       Date:  1988 Nov-Dec       Impact factor: 19.112

5.  Contributions of fasting and postprandial plasma glucose increments to the overall diurnal hyperglycemia of type 2 diabetic patients: variations with increasing levels of HbA(1c).

Authors:  Louis Monnier; Hélène Lapinski; Claude Colette
Journal:  Diabetes Care       Date:  2003-03       Impact factor: 19.112

6.  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

7.  Personal computer programs to assist with self-monitoring of blood glucose and self-adjustment of insulin dosage.

Authors:  N L Pernick; D Rodbard
Journal:  Diabetes Care       Date:  1986 Jan-Feb       Impact factor: 19.112

8.  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

9.  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 in total
  14 in total

1.  A semilogarithmic scale for glucose provides a balanced view of hyperglycemia and hypoglycemia.

Authors:  David Rodbard
Journal:  J Diabetes Sci Technol       Date:  2009-11-01

2.  Self-adjustment of insulin dose using graphically depicted self-monitoring of blood glucose measurements in patients with type 1 diabetes mellitus.

Authors:  Andreas Reichel; Hannes Rietzsch; Barbara Ludwig; Katrin Röthig; Annette Moritz; Stefan R Bornstein
Journal:  J Diabetes Sci Technol       Date:  2013-01-01

Review 3.  Positioning time in range in diabetes management.

Authors:  Andrew Advani
Journal:  Diabetologia       Date:  2019-11-07       Impact factor: 10.122

4.  How Knowledge Emerges From Artificial Intelligence Algorithm and Data Visualization for Diabetes Management.

Authors:  Vincent Derozier; Sylvie Arnavielhe; Eric Renard; Gérard Dray; Sophie Martin
Journal:  J Diabetes Sci Technol       Date:  2019-05-21

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

Authors:  David Rodbard
Journal:  J Diabetes Sci Technol       Date:  2014-10-14

6.  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

7.  New Paradigm of Personalized Glycemic Control Using Glucose Temporal Density Histograms.

Authors:  Uriel Trahtemberg; Tova Hallas; Yehonatan Segman; Ella Sheiman; Michal Shasha; Kobi Nissim; Yosef Joseph Segman
Journal:  J Diabetes Sci Technol       Date:  2019-01-08

Review 8.  Approaches to display of multiple-point glucose profiles: A UK patient's perspective.

Authors:  Daniel Kay
Journal:  J Diabetes Sci Technol       Date:  2014-07-02

9.  Consensus report: the current role of self-monitoring of blood glucose in non-insulin-treated type 2 diabetes.

Authors:  David C Klonoff; Lawrence Blonde; George Cembrowski; Antonio Roberto Chacra; Guillaume Charpentier; Stephen Colagiuri; George Dailey; Robert A Gabbay; Lutz Heinemann; David Kerr; Antonio Nicolucci; William Polonsky; Oliver Schnell; Robert Vigersky; Jean-François Yale
Journal:  J Diabetes Sci Technol       Date:  2011-11-01

10.  Design of a decision support system to help clinicians manage glycemia in patients with type 2 diabetes mellitus.

Authors:  David Rodbard; Robert A Vigersky
Journal:  J Diabetes Sci Technol       Date:  2011-03-01
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