Inflammatory phenotyping predicts clinical outcome in COVID-19.
Inflammatory phenotyping predicts clinical outcome in COVID-19.
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DOI：
10.1186/s12931-020-01511-z
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发表时间：
2020-09-22
影响因子：
5.8
通讯作者：
REACT COVID investigators
中科院分区：
文献类型：
--
作者：
Burke H;Freeman A;Cellura DC;Stuart BL;Brendish NJ;Poole S;Borca F;Phan HTT;Sheard N;Williams S;Spalluto CM;Staples KJ;Clark TW;Wilkinson TMA;REACT COVID investigators
COVID-19疫情已导致全球逾760，000人死亡（截至二零二零年八月十六日）。研究表明，炎症反应是疾病严重程度和死亡的主要原因。识别患有炎症过度的COVID-19患者可能会识别出可以从靶向免疫调节治疗中受益的亚组。在诊断SARS-CoV-2感染时分析细胞因子水平可以识别有恶化风险的患者。我们使用多重细胞因子测定法测量了南安普顿大学医院（英国）100名确诊为COVID-19的住院患者的血清IL-6、IL-8、TNF、IL-1β、GM-CSF、IL-10、IL-33和IFN-γ。收集人口统计学、临床和结局数据进行分析。年龄> 70岁是死亡的最强预测因子（OR 28，95%CI 5.94，139.45）。IL-6、IL-8、TNF、IL-1β和IL-33与不良结局显著相关。临床参数可预测不良结局（AUROC 0.71），添加联合细胞因子组可显著提高预测性（AUROC 0.85）。在≤70岁的患者中，IL-33和TNF可预测不良结局（AUROC 0.83和0.84），增加联合细胞因子组显示比单独临床参数更可预测不良结局（AUROC 0.92 vs 0.77）。一个联合的细胞因子组提高了不良结局预测值的准确性，超过了单独的标准临床数据。识别特定的细胞因子可能有助于对患者进行分层，以进行特定免疫调节治疗试验，以改善COVID-19的结局。
The COVID-19 pandemic has led to more than 760,000 deaths worldwide (correct as of 16th August 2020). Studies suggest a hyperinflammatory response is a major cause of disease severity and death. Identitfying COVID-19 patients with hyperinflammation may identify subgroups who could benefit from targeted immunomodulatory treatments. Analysis of cytokine levels at the point of diagnosis of SARS-CoV-2 infection can identify patients at risk of deterioration. We used a multiplex cytokine assay to measure serum IL-6, IL-8, TNF, IL-1β, GM-CSF, IL-10, IL-33 and IFN-γ in 100 hospitalised patients with confirmed COVID-19 at admission to University Hospital Southampton (UK). Demographic, clinical and outcome data were collected for analysis. Age > 70 years was the strongest predictor of death (OR 28, 95% CI 5.94, 139.45). IL-6, IL-8, TNF, IL-1β and IL-33 were significantly associated with adverse outcome. Clinical parameters were predictive of poor outcome (AUROC 0.71), addition of a combined cytokine panel significantly improved the predictability (AUROC 0.85). In those ≤70 years, IL-33 and TNF were predictive of poor outcome (AUROC 0.83 and 0.84), addition of a combined cytokine panel demonstrated greater predictability of poor outcome than clinical parameters alone (AUROC 0.92 vs 0.77). A combined cytokine panel improves the accuracy of the predictive value for adverse outcome beyond standard clinical data alone. Identification of specific cytokines may help to stratify patients towards trials of specific immunomodulatory treatments to improve outcomes in COVID-19.
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DOI：
10.1164/rccm.201901-0214oc
发表时间：
2020-01-01
影响因子：
24.7
作者：
Watson, Alastair;Spalluto, C. Mirella;Wilkinson, Tom
通讯作者：
Wilkinson, Tom
影响因子：
15.1
作者：
Zhao, Yu-miao;Shang, Yao-min;Xu, Ai-guo
通讯作者：
Xu, Ai-guo
影响因子：
11.8
作者：
Qin, Chuan;Zhou, Luoqi;Tian, Dai-Shi
通讯作者：
Tian, Dai-Shi
死亡预测因素，包括成人 COVID-19 患者的放射学检查结果
影响因子：
5.8
作者：
Li, Kaiyan;Chen, Dian;Zhen, Guohua
通讯作者：
Zhen, Guohua
111例甲型H7N9流感病毒感染临床观察
影响因子：
158.5
作者：
Gao, Hai-Nv;Lu, Hong-Zhou;Li, Lan-Juan
通讯作者：
Li, Lan-Juan