We evaluated simple laboratory variables to discriminate COVID-19 from bacterial pneumonia or influenza and for the prospective grading of COVID-19. Multivariate logistic regression and receiver operating characteristic curve were used to estimate the diagnostic performance of the significant discriminating variables. A comparative analysis was performed with different severity. The leukocytosis (P = 0.017) and eosinopenia (P = 0.001) were discriminating variables between COVID-19 and bacterial pneumonia with area under the curve (AUC) of 0.778 and 0.825. Monocytosis (P = 0.003), the decreased lymphocyte-to-monocyte ratio (P < 0.001), and the increased neutrophil-to-lymphocyte ratio (NLR) (P = 0.028) were predictive of influenza with AUC of 0.723, 0.895, and 0.783, respectively. Serum amyloid protein, lactate dehydrogenase, CD3⁺ cells, and the fibrinogen degradation products had a good correlation with the severity of COVID-19 graded by age (≥50) and NLR (≥3.13). Simple laboratory variables are helpful for rapid diagnosis on admission and hierarchical management of COVID-19 patients.

我们评估了简单的实验室变量，以区分COVID-19与细菌性肺炎或流行性感冒以及COVID-19的预期分级。使用多元逻辑回归和接收者操作特征曲线来估计重要区分变量的诊断性能。进行了不同严重程度的比较分析。白细胞增多（P  = 0.017）和嗜酸性粒细胞减少（P  = 0.001）是区分COVID-19和细菌性肺炎的变量，曲线下面积（AUC）为0.778和0.825。单 核细胞增多症（P = 0.003），淋巴细胞与单核细胞比率降低（P  <0.001）和嗜中性白细胞与淋巴细胞比率（NLR）增加（P = 0.028）可预测流感的AUC分别为0.723、0.895和0.783。血清淀粉样蛋白，乳酸脱氢酶，CD3 ⁺细胞和纤维蛋白原降解产物与按年龄（≥50）和NLR（≥3.13）分级的COVID-19的严重程度具有良好的相关性。简单的实验室变量有助于快速诊断COVID-19患者的入院和分级管理。