Awale Rupali B, Singh Ashutosh, Mishra Prabhaker, Bais Prateek S, Vansh Khare, Shamim Rafat, Ghatak Tanmoy, Hashim Zia, Gupta Devendra, Nath Alok, Singh Ratinder K, Singh Chandrakanta, Pande Shantanu
Department of Laboratory Medicine, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
Department of Biostatistics and Health Informatics, Sanjay Gandhi Institute of Medical Sciences, Lucknow, Uttar Pradesh, India.
J Family Med Prim Care. 2022 Jul;11(7):3423-3429. doi: 10.4103/jfmpc.jfmpc_2453_21. Epub 2022 Jul 22.
Our understanding of the pathophysiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is still evolving and is limited for prognostication. The study was performed to predict severity and mortality based on hematology parameters in coronavirus disease (COVID-19).
The study was a single-center retrospective analysis of 240 patients with COVID-19. The hematological parameters were compared between different grades of severity. The receiver operating characteristics (ROC) curve along with the Classification and Regression Trees (CART) methods were used for the analysis.
The total leukocyte count, absolute neutrophil count, neutrophil-lymphocyte ratio (NLR), and neutrophil-monocyte ratio (NMR) were increasing along with an increase in severity; while the absolute lymphocyte count and lymphocyte-monocyte ratio (LMR) were decreasing ( < 0.001). For prediction of severity and mortality on admission, the NLR, NMR, and LMR were significant ( < 0.001). The NLR, NMR, and LMR had an area under the receiver operating characteristics curve (AUROC) of 0.86 (95% CI of 0.80-0.91), 0.822 (95% CI of 0.76-0.88), and 0.69 (95% CI of 0.60-0.79), respectively, for severity. While the NLR, NMR, and LMR had an AUROC value of 0.85 (95% CI of 0.79-0.92), 0.83 (95% CI of 0.77-0.89), and 0.67 (95% CI of 0.57-0.78), respectively, for mortality.
With the increase in severity there was an increase in the total leukocyte count and absolute neutrophil count while the absolute lymphocyte count decreased. On admission, the cut-off value of NLR >5.2, NMR >12.1, while LMR <2.4 may predict severity and mortality in COVID-19.
我们对严重急性呼吸综合征冠状病毒2（SARS-CoV-2）感染的病理生理学的理解仍在不断发展，且在预后判断方面存在局限性。本研究旨在基于冠状病毒病（COVID-19）的血液学参数预测疾病严重程度和死亡率。
本研究是对240例COVID-19患者进行的单中心回顾性分析。比较了不同严重程度等级之间的血液学参数。采用受试者工作特征（ROC）曲线以及分类与回归树（CART）方法进行分析。
随着严重程度的增加，白细胞总数、绝对中性粒细胞计数、中性粒细胞与淋巴细胞比值（NLR）以及中性粒细胞与单核细胞比值（NMR）均升高；而绝对淋巴细胞计数和淋巴细胞与单核细胞比值（LMR）则降低（P<0.001）。对于入院时严重程度和死亡率的预测，NLR、NMR和LMR具有显著性（P<0.001）。对于严重程度，NLR、NMR和LMR的受试者工作特征曲线下面积（AUROC）分别为0.86（95%CI为0.80 - 0.91）、0.822（95%CI为0.76 - 0.88）和0.69（95%CI为0.60 - 0.79）。而对于死亡率，NLR、NMR和LMR的AUROC值分别为0.85（95%CI为0.79 - 0.92）、0.83（95%CI为0.77 - 0.89）和0.67（95%CI为0.57 - 0.78）。
随着严重程度的增加，白细胞总数和绝对中性粒细胞计数升高，而绝对淋巴细胞计数降低。入院时，NLR>5.2、NMR>12.1以及LMR<2.4的临界值可能预测COVID-19的严重程度和死亡率。
