Association of variation range in glycated albumin (GA) with increase but not decrease in plasma glucose: Implication for the mechanism by which GA reflects glycemic excursion

Hashimoto, Kunihiko; Tanikawa, Kazuko; Nishikawa, Jun; Chen, Yingchao; Suzuki, Toshinobu; Koga, Masafumi

doi:10.1016/j.clinbiochem.2014.12.021

Cited by 10 publications

(9 citation statements)

References 13 publications

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“…Compared with HbA1c, GA has more obvious advantages with rapid changes in blood sugar or rapid deterioration of blood glucose [31], such as in fulminant type I diabetes. GA can also monitor postprandial blood glucose's swimming uctuations and hypoglycemia as well as other pathologic factors [32,33].…”

Section: Discussionmentioning

confidence: 99%

Prognostic Implication of Serum Glycated Albumin for Patients With Non-ST-segment Elevation Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention

Liu

Zhao

et al. 2021

Preprint

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Background: It has been demonstrated that glycated albumin (GA) is significantly associated with diabetes complications and mortality. However, among patients diagnosed with non-ST-elevation acute coronary syndrome (NSTE-ACS) administered percutaneous coronary intervention (PCI), the predictive value of GA for poor prognosis is unclear.Methods: This study eventually included 2247 NSTE-ACS patients in Beijing Anzhen Hospital, Capital Medical University in January-December 2015 who received PCI. All patients were followed up until death or for 48 months post-discharge. The primary endpoint was major adverse cardio-cerebral events (MACCEs), including all-cause death, non-fatal myocardial infarction, ischemia-induced revascularization and non-fatal ischemic stroke.Results: In total, 547 (24.3%) MACCEs were recorded during the follow-up period. Upon adjusting for potential confounders, GA remained an important risk predictor of MACCEs (hazard ratio [HR]=1.051, 95% confidence interval [CI] 1.026-1.077; P<0.001). GA addition significantly enhanced the predictive ability of the traditional risk model (Harrell’s C-index, GA vs. Baseline model, 0.691 vs. 0.678, comparison P=0.001; continuous net reclassification improvement (continuous-NRI)=0.099, P=0.027; integrated discrimination improvement (IDI)=0.008, P=0.020).Conclusion: GA is highly correlated with poor prognosis in NSTE-ACS patients undergoing PCI, suggesting that it may be a major predictive factor of adverse events among these individuals.

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Section: Discussionmentioning

confidence: 99%

Prognostic Implication of Serum Glycated Albumin for Patients With Non-ST-segment Elevation Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention

Liu

Zhao

et al. 2021

Preprint

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“…A study in Taiwan involving 12 individuals without DM who underwent 75 g of OGTT showed via pair analysis that the GA levels were similar in fasting and postprandial samples [ 7 ]. However, Hashimoto et al [ 8 ] found that the GA levels increased between preprandial and 2 h postprandial specimens in 16 Japanese DM patients with poor glycemic control ( p < 0.05), especially after breakfast ( p < 0.05) and observed a significant correlation between the variation ranges of GA and blood glucose measurements ( r = 0.322, p = 0.021). The present study utilized the Wilcoxon signed-rank sum test and Spearman correlation to evaluate the central tendency and correlation, respectively.…”

Section: Discussionmentioning

confidence: 99%

“…Published data include only small sample-sized studies that have used relatively simple evaluations and drawn inconsistent conclusions. Some studies found no significant changes in serum GA levels after a glucose load [ 6 , 7 ], whereas Hashimoto et al [ 8 ] showed that the 2-hour postprandial GA levels were slightly increased in diabetes patients with poor glycemic control. Therefore, to provide evidence for clinical application of GA measurements, this study aimed at comparing results between fasting and nonfasting GA levels and providing an analysis of diabetes screening efficiency for postload GA in a large population sample with different glucose tolerance statuses.…”

Section: Introductionmentioning

confidence: 99%

Postload Glycated Albumin as an Alternate Measure for Diabetes Screening in a Chinese Population

Tang

et al. 2018

Journal of Diabetes Research

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In previous epidemiological screening in China, glycated albumin (GA) was mostly detected during the fasting state. This strict restriction causes some problems with diabetes screening. It is unclear if GA could help improve the efficiency of screening for diabetes for subjects who are not in the fasting state. The present study analyzed the differences between fasting and postload (30, 60, 120, and 180 min) GA levels. A total of 691 participants were enrolled in the present study. The Bland-Altman difference plots revealed that 95.4, 94.8, 93.6, and 93.9% of data points were within the limits of agreement for each time point. The receiver operating characteristic curve showed that the areas under the curve (AUC) for baseline GA and postload GA for every time point were 0.822 (95% CI 0.791–0.849), 0.821 (95% CI 0.790–0.848), 0.833 (95% CI 0.803–0.860), 0.840 (95% CI 0.811–0.867), and 0.840 (95% CI 0.810–0.867), with sensitivities of 67.5, 68.1, 69.3, 71.6, and 69.3%, respectively. There was no difference between the baseline and postload GA levels in either AUC or sensitivity (all p > 0.05). In conclusion, postload serum GA levels were in good agreement with those at baseline, and thus, it may be reasonable to employ nonfasting measurements of GA levels for diabetes screening.

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“…GA has been verified for various aspects in the management of DM in clinical chemistry. For instance, monitoring glucose excursions specifically reflects postprandial[ 25 ] glucose levels and helps to guide the treatment strategies for DM[ 26 ]. GA has been strongly correlated with the development of diabetes complications, especially retinopathy and nephropathy[ 27 ], and has also been proposed as a marker for the assessment of atherosclerosis risk and coronary artery diseases[ 10 ].…”

Section: Introductionmentioning

confidence: 99%

Glycated albumin as a biomarker for diagnosis of diabetes mellitus: A systematic review and meta-analysis

Xiong¹,

Wang²,

Zhao³

et al. 2021

WJCC

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BACKGROUND Glycated albumin (GA), the non-enzymatic glycation product of albumin in plasma, became a glycemic marker in the beginning of the 21st century. The assay is not affected by hemoglobin levels and reflects the glycemic status over a shorter period as compared to HbA1c measurements. Thus, GA may contributes as an intermediate glucose index in the current diabetes mellitus (DM) diagnostic system. AIM To search and summarize the available data on glycated albumin measurements required for the diagnosis of diabetes mellitus. METHODS Databases, including PubMed, Embase, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL), among others, were systematically searched. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was applied for the assessment of quality, and the bivariate model was used to pool the sensitivity and specificity. The hierarchical summary receiver operator characteristic curves (HSROC) model was utilized to estimate the summary receiver operating characteristics curve (SROC). Sensitivity analysis was performed to investigate the association of the study design and patient characteristics with the test accuracy and meta-regression to find the source of heterogeneity. RESULTS Three studies regarding gestational diabetes mellitus (GDM) and a meta-analysis of 16 non-GDM studies, comprising a total sample size of 12876, were included in the work. Results reveal that the average cut-off values of GA reported for the diagnosis of GDM diagnosis was much lower than those for non-GDM. For non-GDM cases, diagnosing DM with a circulating GA cut-off of 14.0% had a sensitivity of 0.766 (95%CI: 0.539, 0.901), specificity of 0.687 (95%CI: 0.364, 0.894), and area under the curve of 0.80 (95%CI: 0.76, 0.83) for the SROC. The estimated SROC at different GA cut-off values for non-GDM exhibited that the average location parameter lambda of 16 non-GDM studies was 2.354 (95%CI: 2.002, 2.707), and the scale parameter beta was -0.163 (95%CI: -0.614, 0.288). These non-GDM studies with various thresholds had substantial heterogeneity, which may be attributed to the type of DM, age, and body mass index as possible sources. CONCLUSION Glycated albumin in non-DM exhibits a moderate diagnostic accuracy. Further research on the diagnostic accuracy of GA for GDM and combinational measurements of GA and other assays is suggested.

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Association of variation range in glycated albumin (GA) with increase but not decrease in plasma glucose: Implication for the mechanism by which GA reflects glycemic excursion

Cited by 10 publications

References 13 publications

Prognostic Implication of Serum Glycated Albumin for Patients With Non-ST-segment Elevation Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention

Prognostic Implication of Serum Glycated Albumin for Patients With Non-ST-segment Elevation Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention

Postload Glycated Albumin as an Alternate Measure for Diabetes Screening in a Chinese Population

Glycated albumin as a biomarker for diagnosis of diabetes mellitus: A systematic review and meta-analysis

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