Department of Laboratory Medicine, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Key Laboratory of Clinical In Vitro Diagnostic Techniques of Zhejiang Province, Hangzhou, China.
J Clin Lab Anal. 2021 Jan;35(1):e23604. doi: 10.1002/jcla.23604. Epub 2020 Nov 13.
The emergence and rapid spread of the deadly novel coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a swiftly evolving public health crisis worldwide. SARS-CoV-2 infection is characterized by the development and progression of inflammatory responses. Hematological parameters, such as white blood cells (WBCs) and their subpopulations, red cell distribution width, platelet count, mean platelet volume, plateletcrit, and derived markers such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio, are established biomarkers of inflammatory responses. We aimed to investigate associations between hematological parameters and disease severity in patients with SARS-CoV-2 infection.
We retrospectively analyzed data from 68 patients with confirmed SARS-CoV-2 infection. Twenty-two patients had mild illness, and 46 had moderate or severe illness at the time of admission. Univariate and multivariate regression analyses were used to identify correlates of disease severity. The areas under receiver operating characteristic curves were calculated to estimate and compare the predictive values of different diagnostic markers.
Mean lymphocyte and monocyte counts were lower while WBC counts, neutrophil counts, NLR, and PLR were higher in patients with severe disease compared with those with mild disease (all P < .01). Univariate analysis revealed that older age, high WBC counts, high neutrophil counts, high NLR, high PLR, low monocyte counts, and low lymphocyte counts were independent correlates of severe illness. Multivariate analysis identified high NLR as the only independent correlate of severe illness. Receiver operating characteristic curve analysis showed that NLR had the highest area under curve of all hematological parameters.
Among hematological parameters, the NLR showed superior prediction of disease severity in patients with SARS-CoV-2 infection. Thus, the NLR could be a valuable parameter to complement conventional measures for identification of patients at high risk for severe disease.
由严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)引起的致命新型冠状病毒病的出现和迅速传播是全球范围内迅速演变的公共卫生危机。SARS-CoV-2 感染的特征是炎症反应的发展和进展。血液学参数,如白细胞(WBC)及其亚群、红细胞分布宽度、血小板计数、平均血小板体积、血小板压积、衍生标志物如中性粒细胞与淋巴细胞比值(NLR)、血小板与淋巴细胞比值(PLR)和淋巴细胞与单核细胞比值,是炎症反应的既定生物标志物。我们旨在研究 SARS-CoV-2 感染患者的血液学参数与疾病严重程度之间的关联。
我们回顾性分析了 68 例确诊 SARS-CoV-2 感染患者的数据。22 例患者为轻症,46 例患者在入院时为中重度疾病。采用单因素和多因素回归分析来确定疾病严重程度的相关因素。计算接收者操作特征曲线下的面积,以估计和比较不同诊断标志物的预测值。
与轻症患者相比,重症患者的平均淋巴细胞和单核细胞计数较低,而白细胞计数、中性粒细胞计数、NLR 和 PLR 较高(均 P<.01)。单因素分析显示,年龄较大、白细胞计数较高、中性粒细胞计数较高、NLR 较高、PLR 较高、单核细胞计数较低和淋巴细胞计数较低是重症疾病的独立相关因素。多因素分析确定 NLR 是重症疾病的唯一独立相关因素。接收者操作特征曲线分析显示,NLR 在所有血液学参数中具有最高的曲线下面积。
在血液学参数中,NLR 对 SARS-CoV-2 感染患者疾病严重程度的预测具有优势。因此,NLR 可能是补充传统措施以识别高危重症疾病患者的有价值的参数。