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脓毒症的临床表型:一项叙述性综述。

Clinical phenotypes of sepsis: a narrative review.

作者信息

Liu Beibei, Zhou Qingtao

机构信息

Department of Respiratory and Critical Care Medicine, Peking University Third Hospital, Beijing, China.

Department of Intensive Care Medicine, Peking University Third Hospital, Beijing, China.

出版信息

J Thorac Dis. 2024 Jul 30;16(7):4772-4779. doi: 10.21037/jtd-24-114. Epub 2024 Jul 26.

Abstract

BACKGROUND AND OBJECTIVE

Sepsis, characterized by an aberrant immune response to infection leading to acute organ dysfunction, impacts millions of individuals each year and carries a substantial risk of mortality, even with prompt care. Despite notable medical advancements, managing sepsis remains a formidable challenge for clinicians and researchers, with treatment options limited to antibiotics, fluid therapy, and organ-supportive measures. Given the heterogeneous nature of sepsis, the identification of distinct clinical phenotypes holds the promise of more precise therapy and enhanced patient care. In this review, we explore various phenotyping schemes applied to sepsis.

METHODS

We searched PubMed with the terms "Clinical phenotypes AND sepsis" for any type of article published in English up to September 2023. Only reports in English were included, editorials or articles lacking full text were excluded. A review of clinical phenotypes of sepsis is provided.

KEY CONTENT AND FINDINGS

While discerning clinical phenotypes may seem daunting, the application of artificial intelligence and machine learning techniques provides a viable approach to quantifying similarities among individuals within a sepsis population. These methods enable the differentiation of individuals into distinct phenotypes based on not only factors such as infectious diseases, infection sites, pathogens, body temperature changes and hemodynamics, but also conventional clinical data and molecular omics.

CONCLUSIONS

The classification of sepsis holds immense significance in improving clinical cure rates, reducing mortality, and alleviating the economic burden associated with this condition.

摘要

背景与目的

脓毒症以对感染的异常免疫反应导致急性器官功能障碍为特征,每年影响数百万人,即使得到及时治疗,也有相当高的死亡风险。尽管医学取得了显著进展,但对临床医生和研究人员来说,脓毒症的管理仍然是一项艰巨的挑战,治疗选择仅限于抗生素、液体疗法和器官支持措施。鉴于脓毒症的异质性,识别不同的临床表型有望实现更精确的治疗并改善患者护理。在本综述中,我们探讨了应用于脓毒症的各种表型分析方案。

方法

我们在PubMed上搜索了截至2023年9月发表的任何英文类型文章,搜索词为“临床表型与脓毒症”。仅纳入英文报告,排除社论或缺乏全文的文章。提供了脓毒症临床表型的综述。

关键内容与发现

虽然识别临床表型看似艰巨,但人工智能和机器学习技术的应用为量化脓毒症人群中个体间的相似性提供了一种可行的方法。这些方法不仅能够根据传染病、感染部位、病原体、体温变化和血流动力学等因素,还能根据传统临床数据和分子组学将个体分为不同的表型。

结论

脓毒症的分类对于提高临床治愈率、降低死亡率以及减轻与该病症相关的经济负担具有重大意义。

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