Literature DB >> 20144394

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

David Rodbard1.   

Abstract

OBJECTIVE: It would be desirable to improve the ability of physicians and patients to identify hypoglycemic episodes when viewing displays of glucose by date, time of day, or day of the week. RESEARCH DESIGN AND METHODS: A logarithmic scale is utilized for display of glucose versus date and time of day using a range of 40 to 400 mg/dl. Several plausible alternatives are considered for transformation of the glucose data. RESULT: Use of a semilogarithmic plot triples the percentage of the vertical axis allocated to hypoglycemia (e.g., 40-80 mg/dl) from 10% to 30.1% while compressing the hyperglycemic region. The log scale improves the symmetry of the glucose distribution. Transformations were evaluated corresponding to the Schlichtkrull M(100) value, the high blood glucose index/low blood glucose index of Kovatchev and associates, an index of glycemic control developed by the present author, and the GRADE score of Hill and coworkers. Results are similar for all four transformations. This approach is applicable both to self-monitoring of blood glucose (SMBG) and continuous glucose monitoring (CGM). Based on preliminary results, it is proposed that the log transform could potentially facilitate analysis of glucose patterns and may facilitate rapid and consistent detection and appreciation of the severity and consistency of hypoglycemic episodes, even in the presence of complex overlapping patterns commonly observed in both SMBG and CGM glucose profiles.
CONCLUSION: Display of glucose on a logarithmic scale can potentially improve the accuracy of analysis and interpretation of popular methods for graphic display of glucose values. Device manufacturers should consider including options for semilogarithmic display of glucose on SMBG meters, CGM sensors, and software for retrospective analyses of glucose data.

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Year:  2009        PMID: 20144394      PMCID: PMC2787040          DOI: 10.1177/193229680900300620

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


  16 in total

1.  THE M-VALVE, AN INDEX OF BLOOD-SUGAR CONTROL IN DIABETICS.

Authors:  J SCHLICHTKRULL; O MUNCK; M JERSILD
Journal:  Acta Med Scand       Date:  1965-01

2.  Relationship of fasting and hourly blood glucose levels to HbA1c values: safety, accuracy, and improvements in glucose profiles obtained using a 7-day continuous glucose sensor.

Authors:  Satish Garg; Lois Jovanovic
Journal:  Diabetes Care       Date:  2006-12       Impact factor: 19.112

3.  Improvement in glycemic excursions with a transcutaneous, real-time continuous glucose sensor: a randomized controlled trial.

Authors:  Satish Garg; Howard Zisser; Sherwyn Schwartz; Timothy Bailey; Roy Kaplan; Samuel Ellis; Lois Jovanovic
Journal:  Diabetes Care       Date:  2006-01       Impact factor: 19.112

4.  Reduction in hemoglobin A1C with real-time continuous glucose monitoring: results from a 12-week observational study.

Authors:  Timothy S Bailey; Howard C Zisser; Satish K Garg
Journal:  Diabetes Technol Ther       Date:  2007-06       Impact factor: 6.118

5.  Evaluation of a 'true' fractional removal rate of glucose in man by bolus and simulated-ramp increase of glucose.

Authors:  U Rosenqvist; V Licko; J H Karam
Journal:  Diabetes       Date:  1976-07       Impact factor: 9.461

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

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

Review 8.  Intensive glycemic control and the prevention of cardiovascular events: implications of the ACCORD, ADVANCE, and VA Diabetes Trials: a position statement of the American Diabetes Association and a Scientific Statement of the American College of Cardiology Foundation and the American Heart Association.

Authors:  Jay S Skyler; Richard Bergenstal; Robert O Bonow; John Buse; Prakash Deedwania; Edwin A M Gale; Barbara V Howard; M Sue Kirkman; Mikhail Kosiborod; Peter Reaven; Robert S Sherwin
Journal:  J Am Coll Cardiol       Date:  2009-01-20       Impact factor: 24.094

9.  A method for assessing quality of control from glucose profiles.

Authors:  N R Hill; P C Hindmarsh; R J Stevens; I M Stratton; J C Levy; D R Matthews
Journal:  Diabet Med       Date:  2007-04-19       Impact factor: 4.359

10.  Assessment of risk for severe hypoglycemia among adults with IDDM: validation of the low blood glucose index.

Authors:  B P Kovatchev; D J Cox; L A Gonder-Frederick; D Young-Hyman; D Schlundt; W Clarke
Journal:  Diabetes Care       Date:  1998-11       Impact factor: 19.112

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  11 in total

1.  Multiplicative surrogate standard deviation: a group metric for the glycemic variability of individual hospitalized patients.

Authors:  Susan S Braithwaite; Guillermo E Umpierrez; J Geoffrey Chase
Journal:  J Diabetes Sci Technol       Date:  2013-09-01

2.  Modeling Inpatient Glucose Management Programs on Hospital Infection Control Programs: An Infrastructural Model of Excellence.

Authors:  Nestoras Mathioudakis; Peter J Pronovost; Sara E Cosgrove; Daniel Hager; Sherita Hill Golden
Journal:  Jt Comm J Qual Patient Saf       Date:  2015-07

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

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

4.  Escaping the Hemoglobin A1c-Centric World in Evaluating Diabetes Mellitus Interventions.

Authors:  Robert A Vigersky
Journal:  J Diabetes Sci Technol       Date:  2015-02-19

5.  Functional characterization of peroxisome proliferator-activated receptor-β/δ expression in colon cancer.

Authors:  Jennifer E Foreman; Wen-Chi L Chang; Prajakta S Palkar; Bokai Zhu; Michael G Borland; Jennie L Williams; Lance R Kramer; Margie L Clapper; Frank J Gonzalez; Jeffrey M Peters
Journal:  Mol Carcinog       Date:  2011-03-11       Impact factor: 4.784

6.  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

Review 7.  Glycemic variability in hospitalized patients: choosing metrics while awaiting the evidence.

Authors:  Susan S Braithwaite
Journal:  Curr Diab Rep       Date:  2013-02       Impact factor: 4.810

8.  Statistical transformation and the interpretation of inpatient glucose control data from the intensive care unit.

Authors:  George E Saulnier; Janna C Castro; Curtiss B Cook
Journal:  J Diabetes Sci Technol       Date:  2014-02-27

9.  Glucose Fluctuations during Gestation: An Additional Tool for Monitoring Pregnancy Complicated by Diabetes.

Authors:  M G Dalfrà; N C Chilelli; G Di Cianni; G Mello; C Lencioni; S Biagioni; M Scalese; G Sartore; A Lapolla
Journal:  Int J Endocrinol       Date:  2013-11-11       Impact factor: 3.257

10.  Informative graphing of continuous safety variables relative to normal reference limits.

Authors:  Christopher D Breder
Journal:  BMC Med Res Methodol       Date:  2018-05-16       Impact factor: 4.615

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