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细胞因子预测 COVID-19 患者的死亡率。

Cytokine prediction of mortality in COVID19 patients.

机构信息

Blood Bank, Sheba Medical Center, Tel-Hashomer, Sackler School of Medicine, Tel-Aviv University, Israel.

Medistat, Tel-Aviv, Sackler School of Medicine, Tel-Aviv University, Israel.

出版信息

Cytokine. 2020 Oct;134:155190. doi: 10.1016/j.cyto.2020.155190. Epub 2020 Jul 10.

Abstract

Coronavirus disease 2019 (COVID19) is a life-threatening infection with uncertain progression and outcome. Assessing the severity of the disease for worsening patients is of importance in making decisions related to supportive mechanical ventilation and aggressive treatments. This was a prospective, non-randomized study that included hospitalized patients diagnosed with COVID19. Pro-inflammatory cytokines were assessed during hospitalization, and we calculated a prediction paradigm for 30-day mortality based on the serum levels of interleukin1β (IL1β), interleukin6 (IL6), interleukin8 (IL8), and tumor necrosis factor alpha (TNFα) measured by next-generation ELISA. Data of 71 COVID19 patients, mean age 62 years, SD13.8, 50 males, 21 females, were analyzed. Twelve (16.9%) patients died within 7-39 days of their first COVID19 positive nasopharyngeal test. Levels of IL6 and TNFα were significantly higher in patients that did not survive. IL6 predicted mortality at the cut-off value of 163.4 pg/ml, with a sensitivity of 91.7% and specificity of 57.6%. Our findings demonstrate that IL6 expression is significant for the prediction of 30-day mortality in hospitalized COVID19 patients and, therefore, may assist in treatment decisions.

摘要

新型冠状病毒病 2019(COVID19)是一种危及生命的感染,其进展和结果不确定。评估病情恶化患者的严重程度对于与支持性机械通气和积极治疗相关的决策非常重要。这是一项前瞻性、非随机研究,纳入了住院诊断为 COVID19 的患者。在住院期间评估促炎细胞因子,我们根据下一代 ELISA 测量的血清白细胞介素 1β(IL1β)、白细胞介素 6(IL6)、白细胞介素 8(IL8)和肿瘤坏死因子α(TNFα)水平计算了 30 天死亡率的预测模型。分析了 71 例 COVID19 患者的数据,平均年龄 62 岁,标准差 13.8,男性 50 例,女性 21 例。12 例(16.9%)患者在首次 COVID19 阳性鼻咽拭子检测后 7-39 天内死亡。未存活患者的 IL6 和 TNFα 水平显著升高。IL6 在截断值 163.4pg/ml 时预测死亡率,敏感性为 91.7%,特异性为 57.6%。我们的研究结果表明,IL6 表达对住院 COVID19 患者 30 天死亡率的预测具有重要意义,因此可能有助于治疗决策。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/35e1/7351379/7c6e02ab85cd/gr1_lrg.jpg

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