Linked Life Data

20214595

Source:http://linkedlifedata.com/resource/pubmed/id/20214595

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2010-3-10
pubmed:abstractText
The measurement of glycaemic variation (GV) is conceived to be of clinical significance in determining diabetes outcomes. The debate as to the importance of GV has been complicated by studies using various metrics of GV in qualitatively different datasets. The purpose of this review is to discuss the properties of 8 of the more commonly used metrics (M-value, MAGE, "J"-index, CONGA, BG rate of change, ADRR, Lability/HYPO score and GRADE). Comparable metrics that can be used to measure continuous glycaemic measurements (CGM) (SDBGL, "J"-index, MAGE, CONGA, GRADE) were then compared in assessing diabetic and non-diabetic datasets. In non-diabetic conditions there was very close correlation (correlation coefficients >0.92) between SDBGL, MAGE and CONGA, however under diabetic conditions the correlation coefficients of the GV metrics diminished significantly. The varying GV metrics have varying inherent properties depending upon the purpose for which they were designed and should not be seen as being interchangeable. Investigators therefore need to be clear about the nature of their enquiry of GV and choose an appropriate metric.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jan
pubmed:issn
1875-6417
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
17-26
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Measuring glycaemic variation.
pubmed:affiliation
Dept of Endocrinology & Diabetes, Royal Children's Hospital, University of Melbourne, Murdoch Children's Research Institute Parkville, Victoria, Australia. fergus.cameron@rch.org.au
pubmed:publicationType
Journal Article, Review