Background

The coronavirus disease 2019 (COVID-19) pandemic has led to surges of patients presenting to emergency departments (EDs) and potentially overwhelming health systems.

Objective

We sought to assess the predictive accuracy of host biomarkers at clinical presentation to the ED for adverse outcome.

Methods

Prospective observational study of PCR-confirmed COVID-19 patients in the ED of a Swiss hospital. Concentrations of inflammatory and endothelial dysfunction biomarkers were determined at clinical presentation. We evaluated the accuracy of clinical signs and these biomarkers in predicting 30-day intubation/mortality, and oxygen requirement by calculating the area under the receiver-operating characteristic curve and by classification and regression tree analysis.

Results

Of 76 included patients with COVID-19, 24 were outpatients or hospitalized without oxygen requirement, 35 hospitalized with oxygen requirement, and 17 intubated/died. We found that soluble triggering receptor expressed on myeloid cells had the best prognostic accuracy for 30-day intubation/mortality (area under the receiver-operating characteristic curve, 0.86; 95% CI, 0.77-0.95) and IL-6 measured at presentation to the ED had the best accuracy for 30-day oxygen requirement (area under the receiver-operating characteristic curve, 0.84; 95% CI, 0.74-0.94). An algorithm based on respiratory rate and sTREM-1 predicted 30-day intubation/mortality with 94% sensitivity and 0.1 negative likelihood ratio. An IL-6–based algorithm had 98% sensitivity and 0.04 negative likelihood ratio for 30-day oxygen requirement.

Conclusions

sTREM-1 and IL-6 concentrations in COVID-19 in the ED have good predictive accuracy for intubation/mortality and oxygen requirement. sTREM-1– and IL-6–based algorithms are highly sensitive to identify patients with adverse outcome and could serve as early triage tools.

中文翻译：

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基于sTREM-1和IL-6的急诊科COVID-19风险分层算法

背景

2019年冠状病毒病（COVID-19）大流行导致急诊科（ED）的患者激增，并可能淹没卫生系统。

目的

我们试图评估在临床上向ED呈报不良结局的宿主生物标志物的预测准确性。

方法

在瑞士一家医院的急诊室对PCR确诊的COVID-19患者进行前瞻性观察研究。在临床表现中确定炎症和内皮功能障碍生物标志物的浓度。我们通过计算接受者操作特征曲线下的面积以及分类和回归树分析，评估了临床体征和这些生物标记物在预测30天插管/死亡率和氧气需求方面的准确性。

结果

在76名COVID-19患者中，有24名门诊或无氧住院，有35名有氧住院，有17例经插管/死亡。我们发现，髓样细胞上表达的可溶性触发受体对30天插管/死亡率（接受者操作特征曲线下的面积，0.86； 95％CI，0.77-0.95）和IL-6的预后准确性最高。 ED对30天的需氧量具有最佳的准确性（在接受者操作特征曲线下的面积为0.84； 95％CI为0.74-0.94）。基于呼吸频率和sTREM-1的算法可预测30天插管/死亡率，灵敏度为94％，负似然比为0.1。基于IL-6的算法对于30天的需氧量具有98％的敏感性和0.04的负似然比。

结论

ED中COVID-19中的sTREM-1和IL-6浓度对于插管/死亡率和氧气需求具有良好的预测准确性。基于sTREM-1和IL-6的算法对识别出不良结果的患者非常敏感，可以用作早期分诊工具。