Li GY, Li HY, Li Q. Use of glycated albumin for the identification of diabetes in subjects from northeast China. World J Diabetes 2021; 12(2): 149-157 [PMID: 33594334 DOI: 10.4239/wjd.v12.i2.149]
Corresponding Author of This Article
Qiang Li, PhD, Professor, Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Harbin Medical University, No. 246 Xuefu Road, Nangang District, Harbin 150080, Heilongjiang Province, China. qiangli1964@126.com
Research Domain of This Article
Endocrinology & Metabolism
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Diabetes. Feb 15, 2021; 12(2): 149-157 Published online Feb 15, 2021. doi: 10.4239/wjd.v12.i2.149
Use of glycated albumin for the identification of diabetes in subjects from northeast China
Guo-Yan Li, Hao-Yu Li, Qiang Li
Guo-Yan Li, Qiang Li, Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Harbin Medical University, Harbin 150080, Heilongjiang Province, China
Hao-Yu Li, Faculty of Population Health Sciences, University College London, London WC1E 6BT, United Kingdom
Author contributions: Li GY designed the study, collected the routine blood samples, contributed to the study design, and wrote the manuscript; Li HY analyzed the data; Li Q made critical revisions to the article for important intellectual content; All authors discussed the results and approved the final version of the manuscript.
Supported byYouth Fund Project of the Second Affiliated Hospital of Harbin Medical University, No. QN2010-20.
Institutional review board statement: The study was reviewed and approved by the Second Affiliated Hospital of Harbin Medical University Institutional Review Board (Approval No. KY2019-020).
Informed consent statement: All study participants, or their legal guardian, provided informed written consent prior to study enrollment.
Conflict-of-interest statement: The authors declare no conflict of interest.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at qiangli1964@126.com.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Qiang Li, PhD, Professor, Department of Endocrinology and Metabolism, The Second Affiliated Hospital of Harbin Medical University, No. 246 Xuefu Road, Nangang District, Harbin 150080, Heilongjiang Province, China. qiangli1964@126.com
Received: November 19, 2020 Peer-review started: November 19, 2020 First decision: November 30, 2020 Revised: December 10, 2020 Accepted: December 23, 2020 Article in press: December 23, 2020 Published online: February 15, 2021 Processing time: 64 Days and 19 Hours
ARTICLE HIGHLIGHTS
Research background
The use of hemoglobin A1c (HbA1c) for the diagnosis of diabetes is a complement to other measures. However, HbA1c is affected by a shortened red blood cell lifespan. In patients with anemia and hemoglobinopathies, the measured HbA1c levels may be inaccurate. Compared with HbA1c, glycated albumin (GA) is more rapid to diagnose new-onset diabetes.
Research motivation
To provide cutoff values for GA and to evaluate its utility as a screening and diagnostic tool for diabetes in a large high-risk group study.
Research objectives
This cross-sectional, high-risk based, large sample study evaluated the GA cut-off for the diagnosis of diabetes mellitus. A total of 1935 subjects aged 18-79 years took part in a comprehensive assessment, including a 75-g oral glucose tolerance test (OGTT), and the measurement of HbA1c and GA.
Research methods
A linear relationship between variables was determined using the Pearson correlation coefficient. P < 0.05 was considered statistically significant. A receiver operating characteristic (ROC) curve was drawn to determine diagnostic sensitivity and specificity. The cut-off value of GA for newly diagnosed diabetes using the OGTT was calculated by ROC analysis using the Youden index.
Research results
A significant association at 0, 30, 60, and 120 min. The OGTT was also correlated with GA and HbA1cCorrelations between the OGTT and both GA and HbA1c. GA concentration was significantly and positively correlated with HbA1c level (r = 0.872, P < 0.001). The 2 h-PG levels were positively correlated with GA.
Research conclusions
Our study supports the use of GA as a biomarker for the diagnosis of diabetes.
Research perspectives
The study should be confirmed in multiple centers and extrapolating the study results to other ethnic groups.
