Clinical impact of variability in HbA<sub>1c</sub> as assessed by simultaneously measuring fructosamine and use of error grid analysis

Macdonald, David R.; Hanson, Alison M.; Holland, M R; Singh, Baldev

doi:10.1258/acb.2008.007259

Cited by 16 publications

(24 citation statements)

References 34 publications

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“…These deviations in mean blood glucose and the A1C value are called the glycohemoglobin index (GHI), and the biological variation of A1C has been examined [3,4,42,43]. The G-gap is also reported to be an indicator with biological variation [5,31], and Nayak et al [6] reported that the G-gap has consistent biological variability in individuals. Recently, as mentioned above, fructosamine or GA and G-gap have been reported as predictive indicators for diabetic complications independent of A1C [16,17,32].…”

Section: Discussionmentioning

confidence: 99%

“…For the G-gap, following the reports of Macdonald et al [31] and Nayak et al [6], fructosamine was replaced with GA, and GA-derived A1C = {[(GA−GA(M))/ GA(SD)] × A1C (SD)} + A1C (M) was obtained. The G-gap was then obtained as G-gap = the HbA1c measured value − the GA-derived A1C (M and SD indicate mean and standard deviation, respectively).…”

Section: Statistical Analysesmentioning

confidence: 99%

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The ratio of glycated albumin to hemoglobin A1c measured in IFCC units accurately represents the glycation gap

et al. 2015

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Section: Discussionmentioning

confidence: 99%

Section: Statistical Analysesmentioning

confidence: 99%

The ratio of glycated albumin to hemoglobin A1c measured in IFCC units accurately represents the glycation gap

et al. 2015

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“…This categorization was taken from our previously published clinical error grid analysis of the impact of G-gap on assessment of glycemic control (19). …”

Section: Methodsmentioning

confidence: 99%

Association of Glycation Gap With Mortality and Vascular Complications in Diabetes

Nayak

Nevill

Bassett³

et al. 2013

Diabetes Care

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OBJECTIVEThe “glycation gap” (G-gap), an essentially unproven concept, is an empiric measure of disagreement between HbA1c and fructosamine, the two indirect estimates of glycemic control. Its association with demographic features and key clinical outcomes in individuals with diabetes is uncertain.RESEARCH DESIGN AND METHODSThe G-gap was calculated as the difference between measured HbA1c and a fructosamine-derived standardized predicted HbA1c in 3,182 individuals with diabetes. The G-gap’s associations with demographics and clinical outcomes (retinopathy, nephropathy, macrovascular disease, and mortality) were determined.RESULTSDemographics varied significantly with G-gap for age, sex, ethnic status, smoking status, type and duration of diabetes, insulin use, and obesity. A positive G-gap was associated with retinopathy (odds ratio 1.24 [95% CI 1.01–1.52], P = 0.039), nephropathy (1.55 [1.23–1.95], P < 0.001), and, in a subset, macrovascular disease (1.91 [1.18–3.09], P = 0.008). In Cox regression analysis, the G-gap had a “U”-shaped quadratic relationship with mortality, with both negative G-gap (1.96 [1.50–2.55], P < 0.001) and positive G-gap (2.02 [1.57–2.60], P < 0.001) being associated with a significantly higher mortality.CONCLUSIONSWe confirm published associations of G-gap with retinopathy and nephropathy. We newly demonstrate a relationship with macrovascular and mortality outcomes and potential links to distinct subpopulations of diabetes.

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“…37 Some studies have reviewed the usefulness of FA. [37][38][39] It has been suggested that FA testing should be performed as a routine check in diabetes patients with normal HbA1c concentrations to confirm that their glucose is under control. 37 This study measured MAGE c and MAGE gos with CGMS data as markers for glucose variability.…”

mentioning

confidence: 99%

Evaluation of Glycemic Variability in Well-Controlled Type 2 Diabetes Mellitus

Chon

Lee²,

Fraterrigo³

et al. 2013

Diabetes Technology & Therapeutics

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Aims: It is necessary to evaluate glucose variability and postprandial hyperglycemia in patients with well-controlled type 2 diabetes mellitus because of the limitations associated with hemoglobin A1c (HbA1c) measurements. We evaluated parameters reflecting postprandial hyperglycemia and glycemic variability in patients with optimal HbA1c. Patients and Methods: Thirty-nine patients with HbA1c levels below 7% were recruited to the study. A continuous glucose monitoring system (CGMS) was applied for two 72-h periods. 1,5-Anhydroglucitol (1,5-AG) and fructosamine (FA) were measured as parameters for postprandial hyperglycemia and glucose variability. Using CGMS data, the following postprandial hyperglycemia parameters were calculated: mean postprandial maximum glucose (MPMG) and area under the curve for glucose above 180 mg/dL (AUC-180). To measure glycemic variability, we calculated mean amplitude of glucose excursion (MAGE) using a classical (MAGE c ) and new method (MAGE group of sign [MAGE gos ]). Results: The baseline HbA1c level was 6.3 -0.3%. The mean MPMG was 10.34 -1.84 mmol/L, and the mean AUC-180 was 0.17 -0.23 mmol/L/day. The mean MAGE gos was 3.27 -1.29 mmol/L, and MAGE c was 4.30 -1.43 mmol/L, indicating glycemic variability in our patients. The mean levels of 1,5-AG and FA were 16.7 -7.4 lg/mL and 273.0 -22.5 lmol/L, respectively. In a correlation analysis, FA was significantly correlated with MPMG, AUC-180, MAGE gos , and MAGE c . In contrast, 1,5-AG was only correlated with AUC-180. Conclusions: This study demonstrated postprandial hyperglycemia and glycemic variability in subjects with well-controlled diabetes. FA may reflect postprandial hyperglycemia and glycemic variability, but 1,5-AG may be of limited value for assessing glucose variability in patients with well-controlled type 2 diabetes mellitus.

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Clinical impact of variability in HbA_1c as assessed by simultaneously measuring fructosamine and use of error grid analysis

Abstract: HbA1c may not accurately reflect glucose control. Our method, utilizing co-assessment with serum fructosamine, evaluates the possible clinical impact of this. We suggest the analysis used in this paper should be used routinely in diabetes practice.

Cited by 16 publications

References 34 publications

The ratio of glycated albumin to hemoglobin A1c measured in IFCC units accurately represents the glycation gap

The ratio of glycated albumin to hemoglobin A1c measured in IFCC units accurately represents the glycation gap

Association of Glycation Gap With Mortality and Vascular Complications in Diabetes

Evaluation of Glycemic Variability in Well-Controlled Type 2 Diabetes Mellitus

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Clinical impact of variability in HbA1c as assessed by simultaneously measuring fructosamine and use of error grid analysis

Abstract: HbA1c may not accurately reflect glucose control. Our method, utilizing co-assessment with serum fructosamine, evaluates the possible clinical impact of this. We suggest the analysis used in this paper should be used routinely in diabetes practice.

Cited by 16 publications

References 34 publications

The ratio of glycated albumin to hemoglobin A1c measured in IFCC units accurately represents the glycation gap

The ratio of glycated albumin to hemoglobin A1c measured in IFCC units accurately represents the glycation gap

Association of Glycation Gap With Mortality and Vascular Complications in Diabetes

Evaluation of Glycemic Variability in Well-Controlled Type 2 Diabetes Mellitus

Contact Info

Product

Resources

About

Clinical impact of variability in HbA_1c as assessed by simultaneously measuring fructosamine and use of error grid analysis