Tang Yueting, Li Yirong, Sun Jiayu, Pan Huaqin, Yao Fen, Jiao Xiaoyang
Department of Clinical Laboratory, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, People's Republic of China.
Department of Cell Biology and Genetics, Shantou University Medical College, Shantou, Guangdong, People's Republic of China.
J Inflamm Res. 2020 Oct 27;13:773-787. doi: 10.2147/JIR.S273193. eCollection 2020.
It is difficult to predict the prognosis of COVID-19 patients at the disease onset. This study was designed to add new biomarkers into conventional inflammatory panels to build an optimal combination panel, to better triage patients and predict their outcomes.
Biochemical parameters representing multi-organ functions, cytokines, acute-phase proteins, and other inflammatory markers were measured in COVID-19 patients on hospital admission. Receiver operating characteristic (ROC) curves, logistic regression, event-free survival (EFS), and Cox analyses were performed to screen and compare the predictive capabilities of the new panel in patients with different illness severity and outcome.
This study included 120 patients with COVID-19, consisting of 32 critical, 28 severe, and 60 mild/moderate patients. Initial levels of the selected biomarkers showed a significant difference in the three groups, all of which influenced patient outcome and EFS to varying degrees. Cox proportional hazard model revealed that procalcitonin (PCT) and interleukin 10 (IL-10) were independent risk factors, while superoxide dismutase (SOD) was an independent protective factor influencing EFS. In discriminating the critical and mild patients, a panel combining PCT, IL-6, and neutrophil (NEUT) yielded the best diagnostic performance with an AUC of 0.99, the sensitivity of 90.60% and specificity of 100%. In distinguishing between severe and mild patients, SOD's AUC of 0.89 was higher than any other single biomarker. In differentiating the critical and severe patients, the combination of white blood cell count (WBC), PCT, IL-6, IL-10, and SOD achieved the highest AUC of 0.95 with a sensitivity of 75.00% and specificity of 100%.
The optimal combination panel has a substantial potential to better triage COVID-19 patients on admission. Better triage of patients will benefit the rational use of medical resources.
在疾病发作时很难预测新型冠状病毒肺炎(COVID-19)患者的预后。本研究旨在将新的生物标志物添加到传统炎症指标中,构建一个最佳组合指标,以更好地对患者进行分类并预测其预后。
在COVID-19患者入院时测量代表多器官功能的生化参数、细胞因子、急性期蛋白和其他炎症标志物。进行受试者工作特征(ROC)曲线、逻辑回归、无事件生存(EFS)和Cox分析,以筛选和比较新指标对不同疾病严重程度和预后患者的预测能力。
本研究纳入了120例COVID-19患者,其中包括32例危重症患者、28例重症患者和60例轻/中度患者。所选生物标志物的初始水平在三组中显示出显著差异,所有这些标志物均不同程度地影响患者预后和EFS。Cox比例风险模型显示,降钙素原(PCT)和白细胞介素10(IL-10)是独立危险因素,而超氧化物歧化酶(SOD)是影响EFS的独立保护因素。在区分危重症和轻症患者时,由PCT、IL-6和中性粒细胞(NEUT)组成的指标诊断性能最佳,曲线下面积(AUC)为0.99,灵敏度为90.60%,特异性为100%。在区分重症和轻症患者时,SOD的AUC为0.89,高于任何其他单一生物标志物。在区分危重症和重症患者时,白细胞计数(WBC)、PCT、IL-6、IL-10和SOD的组合AUC最高,为0.95,灵敏度为75.00%,特异性为100%。
最佳组合指标在入院时对COVID-19患者进行更好的分类方面具有巨大潜力。对患者进行更好的分类将有利于医疗资源的合理使用。