Quantitative chest CT combined with plasma cytokines predict outcomes in COVID-19 patients.
Quantitative chest CT combined with plasma cytokines predict outcomes in COVID-19 patients.
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定量胸部 CT 结合血浆细胞因子可预测 COVID-19 患者的预后。
DOI：
10.1101/2021.10.11.21264709
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Mera
中科院分区：
文献类型：
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作者：
Carbonell,Guillermo;DelValle,DianeMarie;Gonzalez-Kozlova,Edgar;Marinelli,Brett;Klein,Emma;ElHomsi,Maria;Stocker,Daniel;Chung,Michael;Bernheim,Adam;Simons,NicoleW;Xiang,Jiani;Nirenberg,Sharon;Kovatch,Patricia;Lewis,Sara;Mera
尽管国际社会做出了非凡的努力来抑制传播并了解SARS-CoV-2感染背后的机制，但尚未发现直接适用于临床的可预测生物标志物。最近的研究表明，不同类型的检测对COVID-19结果的预测能力有限。在这里，我们利用胸部CT的预测能力结合血浆细胞因子，使用机器学习方法预测COVID-19患者住院期间的死亡和最大严重程度。纳入了来自纽约西奈山卫生系统的患者（n=152），这些患者在入院后5天内进行了血浆细胞因子评估和胸部CT检查。从电子病历中收集人口统计学、临床和实验室变量，包括血浆细胞因子（IL-6、IL-8和TNF-α）。我们发现胸部CT结合血浆细胞因子是死亡（AUC 0.78）和最大严重程度（AUC 0.82）的良好预测因子，而CT定量在预测严重程度（AUC 0.81 vs 0.70）方面更好，而细胞因子测量更好地预测死亡（AUC 0.70 vs 0.66）。最后，我们提供了一个简单的评分系统，使用血浆IL-6、IL-8、TNF-α、GGO与充气肺的比率和年龄作为新的指标，可用于在住院时监测患者，并帮助医生为COVID-19死亡风险高的患者做出关键决策和考虑。
Despite extraordinary international efforts to dampen the spread and understand the mechanisms behind SARS-CoV-2 infections, accessible predictive biomarkers directly applicable in the clinic are yet to be discovered. Recent studies have revealed that diverse types of assays bear limited predictive power for COVID-19 outcomes. Here, we harness the predictive power of chest CT in combination with plasma cytokines using a machine learning approach for predicting death during hospitalization and maximum severity degree in COVID-19 patients. Patients (n=152) from the Mount Sinai Health System in New York with plasma cytokine assessment and a chest CT within 5 days from admission were included. Demographics, clinical, and laboratory variables, including plasma cytokines (IL-6, IL-8, and TNF-α) were collected from the electronic medical record. We found that chest CT combined with plasma cytokines were good predictors of death (AUC 0.78) and maximum severity (AUC 0.82), whereas CT quantitative was better at predicting severity (AUC 0.81 vs 0.70) while cytokine measurements better predicted death (AUC 0.70 vs 0.66). Finally, we provide a simple scoring system using plasma IL-6, IL-8, TNF-α, GGO to aerated lung ratio and age as novel metrics that may be used to monitor patients upon hospitalization and help physicians make critical decisions and considerations for patients at high risk of death for COVID-19.