抗苗勒管激素的测定:基于abei的全自动免疫分析法的初步评价。

Q2 Medicine
Damien Gruson, Akdim Siham, Catherine Fillée
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引用次数: 0

摘要

背景:抗勒氏激素(AMH)测定的附加价值在卵巢储备评估、体外受精方案监测或肿瘤生育领域等临床应用中得到认可。我们的研究目的是确定一种新型全自动化学发光法检测AMH的性能。方法:采用N-(4-氨基丁基)-N-乙基异亮醇(ABEI)标记,评价Maglumi®800 AMH化学发光免疫分析法的性能。用两级对照品评价测定不精密度。方法采用超灵敏AMH酶联免疫吸附试验(Ansh Laboratories, Inc, Webster, TX, USA)对88例患者进行比较。结果:低、高内控的批内、批间变异系数(CVs)均小于3%。自动化检测方法与ELISA检测方法相关性显著。Bland-Altman图证明了两种方法之间的偏差,平均偏差为0.6 ng/mL。结论:我们的初步评估显示,Maglumi®AMH全自动免疫分析总体上具有良好的分析性能,并且与常规使用的分析具有良好的一致性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Measurement of Anti-Mullerian Hormone: Preliminary Evaluation of an ABEI-Based Fully Automated Immunoassay.

Measurement of Anti-Mullerian Hormone: Preliminary Evaluation of an ABEI-Based Fully Automated Immunoassay.

Measurement of Anti-Mullerian Hormone: Preliminary Evaluation of an ABEI-Based Fully Automated Immunoassay.

Background: The added value of Anti-Müllerian hormone (AMH) measurement is recognized for several clinical applications such as assessment of the ovarian reserve, monitoring of in vitro fertilization protocol or in the field of oncofertility. Our study objective was to determine the performances of a novel fully automated chemiluminescent assay for AMH testing.

Methods: We evaluated the performances of the Maglumi® 800 AMH chemiluminescent immunoassay that applies N-(4-Aminobutyl)-N-ethylisoluminol (ABEI) labels. Assay imprecision was assessed with two levels of control materials. Method comparison was performed with an ultrasensitive AMH ELISA assay (Ansh Laboratories, Inc, Webster, TX, USA) with 88 patients' samples.

Results: The within-run and between-run coefficients of variation (CVs) were below 3% for both low and high internal quality controls. The automated and ELISA methods were significantly correlated. Bland-Altman plot evidenced a bias between the methods with a mean bias of 0.6 ng/mL.

Conclusions: Our preliminary evaluation showed overall good analytical performances for the Maglumi® AMH fully automated immunoassay and good concordance with a routinely used assay.

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CiteScore
2.30
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