Glycated albumin in diabetes mellitus: a meta-analysis of diagnostic test accuracy.

Fernando C Chume, Priscila A C Freitas, Luisa G Schiavenin, Ana L Pimentel, Joíza Lins Camargo
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Abstract

Objectives: Guidelines recommend the diagnosis of diabetes should be based on either plasma glucose or glycated hemoglobin (HbA1C) findings. However, lately studies have advocated glycated albumin (GA) as a useful alternative to HbA1c. We conducted a systematic review and meta-analysis to determine the overall diagnostic accuracy of GA for the diagnosis of diabetes.

Content: We searched for articles of GA diabetes diagnostic accuracy that were published up to August 2021. Studies were selected if reported an oral glucose tolerance test as a reference test, measured GA levels by enzymatic methods, and had data necessary for 2 × 2 contingency tables. A bivariate model was used to calculate the pooled estimates.

Summary: This meta-analysis included nine studies, totaling 10,007 individuals. Of those, 3,106 had diabetes. The studies showed substantial heterogeneity caused by a non-threshold effect and reported different GA optimal cut-offs for diagnosing diabetes. The pooled diagnostic odds ratio (DOR) was 15.93 and the area under the curve (AUC) was 0.844, indicating a good level of overall accuracy for the diagnosis of diabetes. The effect of the GA threshold on diagnostic accuracy was reported at 15.0% and 17.1%. The optimal cut-off for diagnosing diabetes with GA was estimated as 17.1% with a pooled sensitivity of 55.1% (95% CI 36.7%-72.2%) and specificity of 94.4% (95% CI 85.3%-97.9%).

Outlook: GA has good diabetes diagnostic accuracy. A GA threshold of 17.1% may be considered optimal for diagnosing diabetes in previously undiagnosed individuals.

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糖化白蛋白在糖尿病:诊断测试准确性的荟萃分析。
目的:指南建议糖尿病的诊断应基于血浆葡萄糖或糖化血红蛋白(HbA1C)结果。然而,最近的研究提倡糖化白蛋白(GA)作为HbA1c的有用替代品。我们进行了一项系统综述和荟萃分析,以确定GA诊断糖尿病的总体诊断准确性。内容:我们检索了截至2021年8月发表的有关GA糖尿病诊断准确性的文章。选择口服葡萄糖耐量试验作为参考试验,用酶法测量GA水平,并具有2 × 2列联表所需的数据的研究。采用双变量模型计算汇总估计。摘要:本荟萃分析包括9项研究,共计10,007人。其中,3106人患有糖尿病。研究显示了非阈值效应引起的大量异质性,并报告了不同的遗传算法诊断糖尿病的最佳截止值。合并诊断优势比(DOR)为15.93,曲线下面积(AUC)为0.844,表明诊断糖尿病的总体准确性较高。GA阈值对诊断准确率的影响分别为15.0%和17.1%。GA诊断糖尿病的最佳临界值估计为17.1%,合并敏感性为55.1% (95% CI 36.7%-72.2%),特异性为94.4% (95% CI 85.3%-97.9%)。展望:遗传分析具有良好的糖尿病诊断准确性。17.1%的GA阈值可能被认为是诊断以前未确诊个体糖尿病的最佳阈值。
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