Abstract：
OBJECTIVE: Matrix-assisted laser desorption ionization time of flight (MALDI-TOF) has revolutionized clinical microbiology laboratories, enabling the identification of microorganisms in minutes. Although this advancement has significantly enhanced patient care by providing early diagnosis, the use of MALDI-TOF for routine detection of antimicrobial resistance (AMR) remains an ongoing area of research. The purpose of this scoping review was to identify and summarize the existing literature on MALDI-TOF-based methodologies for detecting AMR.
METHODS: The PubMed, Embase, and Cumulative Index to Nursing and Allied Health Literature databases were searched for articles published up to July 2023. Publications were carefully screened, and inclusion was based on their relevance to the topic and detailed explanations of the methodologies employed.
RESULTS: We reviewed 49 articles and identified various MALDI-TOF-based approaches for detecting AMR that we grouped in 2 main categories: (1) bacterial growth detection following a brief incubation with antibiotics and (2) identification of specific mass spectral profiles associated with drug resistance. Recently, the use of machine learning algorithms has been explored to detect characteristic patterns associated with AMR. Thorough evaluation of each study\'s procedures was conducted to determine their potential for implementation in clinical laboratories.
CONCLUSIONS: MALDI-TOF shows promise as a tool for AMR detection, but its readiness for wider clinical adoption relies on ongoing research, development of algorithms and software for automated interpretation of mass spectra, and validation efforts. Its role in routine clinical practice may evolve as technology and knowledge progress.
METHODS: The PubMed, Embase, and Cumulative Index to Nursing and Allied Health Literature databases were searched for articles published up to July 2023. Publications were carefully screened, and inclusion was based on their relevance to the topic and detailed explanations of the methodologies employed.
RESULTS: We reviewed 49 articles and identified various MALDI-TOF-based approaches for detecting AMR that we grouped in 2 main categories: (1) bacterial growth detection following a brief incubation with antibiotics and (2) identification of specific mass spectral profiles associated with drug resistance. Recently, the use of machine learning algorithms has been explored to detect characteristic patterns associated with AMR. Thorough evaluation of each study\'s procedures was conducted to determine their potential for implementation in clinical laboratories.
CONCLUSIONS: MALDI-TOF shows promise as a tool for AMR detection, but its readiness for wider clinical adoption relies on ongoing research, development of algorithms and software for automated interpretation of mass spectra, and validation efforts. Its role in routine clinical practice may evolve as technology and knowledge progress.
摘要：
目的：基质辅助激光解吸电离飞行时间（MALDI-TOF）彻底改变了临床微生物学实验室，能够在几分钟内识别微生物。尽管这一进步通过提供早期诊断显着增强了患者护理，使用MALDI-TOF常规检测抗菌素耐药性(AMR)仍是一个正在进行的研究领域.本范围审查的目的是确定和总结现有的基于MALDI-TOF的AMR检测方法的文献。
方法：PubMed，Embase,并搜索了截至2023年7月发表的文章的护理和相关健康文献数据库的累积指数。出版物经过仔细筛选，和纳入是基于它们与主题的相关性以及对所采用方法的详细解释。
结果：我们回顾了49篇文章，并确定了各种基于MALDI-TOF的AMR检测方法，我们将其分为两个主要类别：（1）与抗生素短暂孵育后的细菌生长检测和（2）鉴定与耐药性相关的特定质谱图。最近,已经探索了使用机器学习算法来检测与AMR相关的特征模式。对每个研究程序进行全面评估，以确定其在临床实验室中实施的潜力。
结论：MALDI-TOF有望成为AMR检测的工具，但是它对更广泛的临床应用的准备依赖于正在进行的研究，用于自动解释质谱的算法和软件的开发，和验证工作。它在常规临床实践中的作用可能随着技术和知识的进步而发展。
方法：PubMed，Embase,并搜索了截至2023年7月发表的文章的护理和相关健康文献数据库的累积指数。出版物经过仔细筛选，和纳入是基于它们与主题的相关性以及对所采用方法的详细解释。
结果：我们回顾了49篇文章，并确定了各种基于MALDI-TOF的AMR检测方法，我们将其分为两个主要类别：（1）与抗生素短暂孵育后的细菌生长检测和（2）鉴定与耐药性相关的特定质谱图。最近,已经探索了使用机器学习算法来检测与AMR相关的特征模式。对每个研究程序进行全面评估，以确定其在临床实验室中实施的潜力。
结论：MALDI-TOF有望成为AMR检测的工具，但是它对更广泛的临床应用的准备依赖于正在进行的研究，用于自动解释质谱的算法和软件的开发，和验证工作。它在常规临床实践中的作用可能随着技术和知识的进步而发展。
