Development of the Likelihood of Low Glucose (LLG) Algorithm for Evaluating Risk of Hypoglycemia

  • Dunn T
  • Hayter G
  • Doniger K
  • et al.
N/ACitations
Citations of this article
5Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Objective:The objective was to develop an analysis methodology for generating diabetes therapy decision guidance using continuous glucose (CG) data.Methods:The novel Likelihood of Low Glucose (LLG) methodology, which exploits the relationship between glucose median, glucose variability, and hypoglycemia risk, is mathematically based and can be implemented in computer software. Using JDRF Continuous Glucose Monitoring Clinical Trial data, CG values for all participants were divided into 4-week periods starting at the first available sensor reading. The safety and sensitivity performance regarding hypoglycemia guidance “stoplights” were compared between the LLG method and one based on 10th percentile (P10) values.Results:Examining 13 932 hypoglycemia guidance outputs, the safety performance of the LLG method ranged from 0.5% to 5.4% incorrect “green” indicators, compared with 0.9% to 6.0% for P10 value of 110 mg/dL. Guidance with lower P10 values yielded higher rates of incorrect indicators, such as 11.7% t...

Cite

CITATION STYLE

APA

Dunn, T. C., Hayter, G. A., Doniger, K. J., & Wolpert, H. A. (2014). Development of the Likelihood of Low Glucose (LLG) Algorithm for Evaluating Risk of Hypoglycemia. Journal of Diabetes Science and Technology, 8(4), 720–730. https://doi.org/10.1177/1932296814532200

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free