Leukocyte Activation Profile Assessed by Raman Spectroscopy Helps Diagnosing Infection and Sepsis.
Leukocyte Activation Profile Assessed by Raman Spectroscopy Helps Diagnosing Infection and Sepsis.
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DOI：
10.1097/cce.0000000000000394
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发表时间：
2021-05
影响因子：
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通讯作者：
Neugebauer U
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文献类型：
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作者：
Ramoji A;Thomas-Rüddel D;Ryabchykov O;Bauer M;Arend N;Giamarellos-Bourboulis EJ;Eugen-Olsen J;Kiehntopf M;Bocklitz T;Popp J;Bloos F;Neugebauer U
补充数字内容可在文本中找到。白细胞是对感染的第一反应者。它们的激活状态可以揭示特异性宿主免疫反应的信息，并识别败血症中的失调。本研究旨在利用血源性白细胞的拉曼光谱指纹图谱来鉴别住院患者的炎症、感染和败血症。诊断的敏感性和特异性应证明白细胞表型直接表征的附加价值。前瞻性非随机、单中心、观察性ii期研究（DRKS00006265）。耶拿大学医院，德国。住院患者61例(无菌性炎症19例，无脏器功能障碍感染23例，脓毒症18例（脓毒症-3定义）。无（抽血）。用拉曼光谱对单个外周血白细胞进行表征。参考诊断包括临床评分、血细胞计数和生物标志物（c反应蛋白、降钙素原和白细胞介素-6）。使用拉曼数据的二元分类模型能够区分感染患者和非感染患者，以及脓毒症患者和非脓毒症患者，并通过已建立的生物标志物实现了准确性。与单独的生物标志物信息相比，加入拉曼信息检测感染的准确率提高了10%（至93%），检测败血症的准确率提高了18%（至92%）。脓毒症患者的白细胞与感染患者的白细胞表现出不同的拉曼光谱特征，说明脓毒症患者具有特殊的免疫表型。拉曼光谱可以以非破坏性、无标记的方式提取白细胞激活状态的信息，以区分无菌炎症、感染和败血症。
Supplemental Digital Content is available in the text. Leukocytes are first responders to infection. Their activation state can reveal information about specific host immune response and identify dysregulation in sepsis. This study aims to use the Raman spectroscopic fingerprints of blood-derived leukocytes to differentiate inflammation, infection, and sepsis in hospitalized patients. Diagnostic sensitivity and specificity shall demonstrate the added value of the direct characterization of leukocyte’s phenotype. Prospective nonrandomized, single-center, observational phase-II study (DRKS00006265). Jena University Hospital, Germany. Sixty-one hospitalized patients (19 with sterile inflammation, 23 with infection without organ dysfunction, 18 with sepsis according to Sepsis-3 definition). None (blood withdrawal). Individual peripheral blood leukocytes were characterized by Raman spectroscopy. Reference diagnostics included established clinical scores, blood count, and biomarkers (C-reactive protein, procalcitonin and interleukin-6). Binary classification models using Raman data were able to distinguish patients with infection from patients without infection, as well as sepsis patients from patients without sepsis, with accuracies achieved with established biomarkers. Compared with biomarker information alone, an increase of 10% (to 93%) accuracy for the detection of infection and an increase of 18% (to 92%) for detection of sepsis were reached by adding the Raman information. Leukocytes from sepsis patients showed different Raman spectral features in comparison to the patients with infection that point to the special immune phenotype of sepsis patients. Raman spectroscopy can extract information on leukocyte’s activation state in a nondestructive, label-free manner to differentiate sterile inflammation, infection, and sepsis.