Cardiac troponin

IF 3.2 3区医学 Q2 MEDICAL LABORATORY TECHNOLOGY

Clinica Chimica Acta Pub Date : 2025-05-03 DOI:10.1016/j.cca.2025.120344

Yumeng Gao , Danchen Wang , Danni Mu , Yichen Ma , Yuemeng Li , Ling Qiu , Songlin Yu , Xinqi Cheng

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引用次数: 0

Abstract

Cardiac troponin (cTn) testing plays a crucial role in the diagnosis of cardiovascular diseases, particularly acute coronary syndrome (ACS), which includes acute myocardial infarction (AMI). However, conventional immunoassays may be subject to interference from autoantibodies, cross-reactivity, and biotin-related effects, compromising diagnostic accuracy. A thorough investigation of these interference mechanisms is necessary to improve assay methodologies, ensuring greater reliability and precision. In recent years, significant advancements in mass spectrometry (MS) technology have sparked increased interest in its application for cTn testing. For instance, liquid chromatography-tandem mass spectrometry (LC-MS/MS) employs multiple reaction monitoring (MRM) to accurately quantify cardiac troponin I (cTnI)-specific tryptic peptides along with their fragment ions. This technique effectively reduces immunoassay interference while improving analytical specificity. Compared to traditional immunoassays, MS-based approaches alleviate matrix effects and analytical interferences while achieving superior specificity. Nonetheless, clinical adoption remains constrained by technical complexity; thus clinicians can obtain more reliable diagnostic insights. This review summarizes the current landscape of cTn detection technologies by examining the prevalence of false-positive results across various methods. It further explores both the practical applications and challenges associated with MS-based techniques in cTn testing. Ultimately, this review aims to improve cTn testing reliability, enhance cardiovascular disease diagnosis, and guide personalized treatment strategies.

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心肌肌钙蛋白

心肌肌钙蛋白（cTn）检测在心血管疾病，特别是急性冠脉综合征（ACS），包括急性心肌梗死（AMI）的诊断中起着至关重要的作用。然而，传统的免疫测定法可能受到自身抗体、交叉反应性和生物素相关效应的干扰，从而影响诊断的准确性。有必要对这些干扰机制进行彻底的调查，以改进分析方法，确保更高的可靠性和准确性。近年来，质谱（MS）技术的显著进步引起了人们对其在cTn检测中的应用的兴趣。例如，液相色谱-串联质谱（LC-MS/MS）采用多重反应监测（MRM）来准确定量心脏肌钙蛋白I （cTnI）特异性色氨酸肽及其片段离子。该技术有效地减少了免疫分析干扰，同时提高了分析特异性。与传统的免疫分析方法相比，MS-based方法减轻了基质效应和分析干扰，同时具有优越的特异性。尽管如此，临床应用仍然受到技术复杂性的限制；因此，临床医生可以获得更可靠的诊断见解。本综述通过检查各种方法中假阳性结果的流行情况，总结了目前cTn检测技术的现状。它进一步探讨了与基于ms的技术在cTn测试中的实际应用和挑战。最终，本综述旨在提高cTn检测的可靠性，提高心血管疾病的诊断，指导个性化的治疗策略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Clinica Chimica Acta 医学-医学实验技术

CiteScore

10.10

自引率

2.00%

发文量

1268

审稿时长

23 days

期刊介绍： The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.