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剖析脓毒症中失调的免疫反应:克服挑战,实现精准医学目标。

Profiling the dysregulated immune response in sepsis: overcoming challenges to achieve the goal of precision medicine.

机构信息

Department of Infectious Diseases, Faculty of Medicine and Health, Örebro University, Örebro, Sweden.

Department of Intensive Care Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, Netherlands.

出版信息

Lancet Respir Med. 2024 Apr;12(4):305-322. doi: 10.1016/S2213-2600(23)00330-2. Epub 2023 Dec 21.

Abstract

Sepsis is characterised by a dysregulated host immune response to infection. Despite recognition of its significance, immune status monitoring is not implemented in clinical practice due in part to the current absence of direct therapeutic implications. Technological advances in immunological profiling could enhance our understanding of immune dysregulation and facilitate integration into clinical practice. In this Review, we provide an overview of the current state of immune profiling in sepsis, including its use, current challenges, and opportunities for progress. We highlight the important role of immunological biomarkers in facilitating predictive enrichment in current and future treatment scenarios. We propose that multiple immune and non-immune-related parameters, including clinical and microbiological data, be integrated into diagnostic and predictive combitypes, with the aid of machine learning and artificial intelligence techniques. These combitypes could form the basis of workable algorithms to guide clinical decisions that make precision medicine in sepsis a reality and improve patient outcomes.

摘要

脓毒症的特征是宿主对感染的免疫反应失调。尽管人们认识到其重要性,但由于目前没有直接的治疗意义,免疫状态监测并未在临床实践中实施。免疫分析技术的进步可以增强我们对免疫失调的理解,并有助于将其纳入临床实践。在这篇综述中,我们概述了脓毒症免疫分析的现状,包括其用途、当前的挑战和进展的机会。我们强调了免疫生物标志物在促进当前和未来治疗方案中的预测性富集方面的重要作用。我们建议将多种免疫和非免疫相关参数(包括临床和微生物学数据)与机器学习和人工智能技术结合起来,整合到诊断和预测组合类型中。这些组合类型可以作为可行算法的基础,以指导临床决策,使脓毒症精准医学成为现实,并改善患者的预后。

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