Selection of an Optimal Combination Panel to Better Triage COVID-19 Hospitalized Patients

PURPOSE: 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. PATIENTS AND METHODS: 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. RESULTS: 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%. CONCLUSION: 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.