Literature DB >> 29792750

Metrics to Evaluate Quality of Glycemic Control: Comparison of Time in Target, Hypoglycemic, and Hyperglycemic Ranges with "Risk Indices".

David Rodbard1.   

Abstract

OBJECTIVE: We sought to cross validate several metrics for quality of glycemic control, hypoglycemia, and hyperglycemia. RESEARCH DESIGN AND METHODS: We analyzed the mathematical properties of several metrics for overall glycemic control, and for hypo- and hyperglycemia, to evaluate their similarities, differences, and interrelationships. We used linear regression to describe interrelationships and examined correlations between metrics within three conceptual groups.
RESULTS: There were consistently high correlations between %Time in range (%TIR) and previously described risk indices (M100, Blood Glucose Risk Index [BGRI], Glycemic Risk Assessment Diabetes Equation [GRADE], Index of Glycemic Control [IGC]), and with J-Index (J). There were also high correlations among %Hypoglycemia, Low Blood Glucose Index (LBGI), percentage of GRADE attributable to hypoglycemia (GRADE%Hypoglycemia), and Hypoglycemia Index, but negligible correlation with J. There were high correlations of percentage of time in hyperglycemic range (%Hyperglycemia) with High Blood Glucose Index (HBGI), percentage of GRADE attributable to hyperglycemia (GRADE%Hyperglycemia), Hyperglycemia Index, and J. %TIR is highly negatively correlated with %Hyperglycemia but very weakly correlated with %Hypoglycemia. By adjusting the parameters used in IGC, Hypoglycemia Index, Hyperglycemia Index, or in MR, one can more closely approximate the properties of BGRI, LBGI, or HBGI, and of GRADE, GRADE%Hypoglycemia, or GRADE%Hyperglycemia.
CONCLUSIONS: Simple readily understandable criteria such as %TIR, %Hypoglycemia, and %Hyperglycemia are highly correlated with and appear to be as informative as "risk indices." The J-Index is sensitive to hyperglycemia but insensitive to hypoglycemia.

Entities:  

Keywords:  Continuous glucose monitoring; Glycemic control; Hyperglycemia; Hypoglycemia; Risk indices; Self-monitoring of blood glucose

Mesh:

Substances:

Year:  2018        PMID: 29792750     DOI: 10.1089/dia.2017.0416

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


  13 in total

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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
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4.  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
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6.  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

7.  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

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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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