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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Diabetes Technology ...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Diabetes Technology & Therapeutics
Article . 2007 . Peer-reviewed
License: Mary Ann Liebert TDM
Data sources: Crossref
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Calibration of The Continuous Glucose Monitoring System for Transient Glucose Monitoring

Authors: Leann M, Lesperance; Anna, Spektor; Kenneth J, McLeod;

Calibration of The Continuous Glucose Monitoring System for Transient Glucose Monitoring

Abstract

Oral glucose tolerance testing (OGTT) remains the gold standard for diagnosis of diabetes and is used commonly in the research laboratory. The Medtronic MiniMed (North-ridge, CA) Continuous Glucose Monitoring System (CGMS Gold), developed for long-term monitoring of glycemic levels, could provide a convenient means for tracking OGTT results during research protocols; however, the sensor demonstrates glucose and time dependencies that preclude direct application of the company-provided conversion algorithm in the first 12-24 h after sensor insertion. Here, we propose an alternative conversion algorithm that permits utilization of the CGMS monitor for glucose monitoring during this time.Healthy female participants underwent CGMS monitoring during OGTT or fasting sessions in combination with finger-stick blood glucose measurements. Logarithmic transformations and multiple regression analysis were used to quantify the time and glucose dependence of the sensors.Sensor performance, as characterized by sensitivity (ratio of sensor current to capillary blood glucose levels), was shown to vary logarithmically with glucose levels as well as time after sensor insertion. A conversion algorithm developed on the basis of these observations was tested on 17 subjects during OGTT. A mean absolute relative difference between capillary blood glucose and CGMS values of 11.6 +/- 6.5% for the new algorithm was seen, compared to 20.6 +/- 5.9% with the Medtronic Solutions version 3.0c algorithm.Incorporation of the glucose and time dependence in CGMS sensor data yields an improved mean absolute difference between actual and estimated blood glucose values compared to the Medtronic-supplied algorithm in the immediate time period following sensor insertion.

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Keywords

Adult, Blood Glucose, Monitoring, Ambulatory, Reproducibility of Results, Glucose Tolerance Test, Middle Aged, Sensitivity and Specificity, Reference Values, Calibration, Humans, Female, Algorithms

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
11
Average
Average
Top 10%
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