2009
DOI: 10.1111/j.1464-5491.2008.02652.x
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Validation of an algorithm combining haemoglobin A1c and fasting plasma glucose for diagnosis of diabetes mellitus in UK and Australian populations

Abstract: Use of this algorithm would simplify procedures for diagnosis of diabetes and could also be used for monitoring pre-diabetes. Validation is now required in other populations and patient groups.

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Cited by 37 publications
(48 citation statements)
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“…It is clear that fluorescence intensity of DM group increased significantly compared with normal group (p<0.05) while that of intervention group decreased and no statistic difference of fluorescence intensity between normal group and diet intervention group was observed. Similar phenomenon was found in the differences of concentration of GHbA1c, glycated protein which is used as a golden standard in the diagnosis and monitoring of diabetes mellitus [29]. These results showed that the inhibition of TP on glycation occured in diabetic mice.…”
Section: Journal Of Food and Nutrition Researchsupporting
confidence: 69%
“…It is clear that fluorescence intensity of DM group increased significantly compared with normal group (p<0.05) while that of intervention group decreased and no statistic difference of fluorescence intensity between normal group and diet intervention group was observed. Similar phenomenon was found in the differences of concentration of GHbA1c, glycated protein which is used as a golden standard in the diagnosis and monitoring of diabetes mellitus [29]. These results showed that the inhibition of TP on glycation occured in diabetic mice.…”
Section: Journal Of Food and Nutrition Researchsupporting
confidence: 69%
“…Established risk scores and tools were calculated within the Mesy-Bepo cohort according to the information provided in the respective publications (7,17,18).…”
Section: Discussionmentioning
confidence: 99%
“…Thus, a regression-analysis-based questionnaire may have a better screening quality, if specifically individuals with IGM are targeted. A recent publication also proposed a decision tree to identify subjects with existing T2DM (7). We also applied this tree to our cohort.…”
Section: Discussionmentioning
confidence: 99%
“…Anecdotally, HbA1c has been used in community opportunistic screening for many years, however without the support of guidelines, therefore there was no standardisation of which HbA1c cut-point which detect T2DM and this was left to the discretion of the health care professional (Ealovega et al, 2004). There is accumulating evidence that HbA1c has equally as good if not higher discriminatory ability for detecting T2DM and cardiovascular disease (CVD) than FPG (Perry et al, 2001;Kim et al, 2008;Droumaguet et al, 2006;Manley et al, 2009;Buell et al 2007;Rohlfing et al, 2000;Selvin et al, 2010).…”
Section: Glycated Haemoglobin (Hba1c)mentioning
confidence: 99%