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脓毒症的诊断挑战

Diagnostic Challenges in Sepsis.

作者信息

Duncan Chris F, Youngstein Taryn, Kirrane Marianne D, Lonsdale Dagan O

机构信息

Department of Critical Care, St George's University Hospitals NHS Foundation Trust, London, UK.

Department of Rheumatology, Hammersmith Hospital, Imperial College Healthcare NHS Trust, London, UK.

出版信息

Curr Infect Dis Rep. 2021;23(12):22. doi: 10.1007/s11908-021-00765-y. Epub 2021 Oct 25.

Abstract

PURPOSE OF REVIEW

Sepsis is a leading cause of death worldwide. Groundbreaking international collaborative efforts have culminated in the widely accepted surviving sepsis guidelines, with iterative improvements in management strategies and definitions providing important advances in care for patients. Key to the diagnosis of sepsis is identification of infection, and whilst the diagnostic criteria for sepsis is now clear, the diagnosis of infection remains a challenge and there is often discordance between clinician assessments for infection.

RECENT FINDINGS

We review the utility of common biochemical, microbiological and radiological tools employed by clinicians to diagnose infection and explore the difficulty of making a diagnosis of infection in severe inflammatory states through illustrative case reports. Finally, we discuss some of the novel and emerging approaches in diagnosis of infection and sepsis.

SUMMARY

While prompt diagnosis and treatment of sepsis is essential to improve outcomes in sepsis, there remains no single tool to reliably identify or exclude infection. This contributes to unnecessary antimicrobial use that is harmful to individuals and populations. There is therefore a pressing need for novel solutions. Machine learning approaches using multiple diagnostic and clinical inputs may offer a potential solution but as yet these approaches remain experimental.

摘要

综述目的

脓毒症是全球主要的死亡原因。开创性的国际合作努力最终形成了被广泛接受的《脓毒症存活指南》,管理策略和定义的不断改进为患者护理带来了重要进展。脓毒症诊断的关键是识别感染,虽然目前脓毒症的诊断标准已经明确,但感染的诊断仍然是一项挑战,临床医生对感染的评估往往存在不一致。

最新发现

我们回顾了临床医生用于诊断感染的常见生化、微生物学和放射学工具的效用,并通过实例病例报告探讨了在严重炎症状态下进行感染诊断的困难。最后,我们讨论了一些诊断感染和脓毒症的新颖和新兴方法。

总结

虽然及时诊断和治疗脓毒症对于改善脓毒症患者的预后至关重要,但仍然没有单一工具能够可靠地识别或排除感染。这导致了不必要的抗菌药物使用,对个体和人群都有害。因此,迫切需要新的解决方案。使用多种诊断和临床输入的机器学习方法可能提供一个潜在的解决方案,但目前这些方法仍处于实验阶段。

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