Department of Emergency, Faculty of Medicine, University of Health Sciences, Ankara, Turkey.
Department of Internal Medicine, Ankara City Hospital, Ankara, Turkey.
Turk J Med Sci. 2021 Dec 13;51(6):2810-2821. doi: 10.3906/sag-2008-6.
BACKGROUND/AIM: Coronavirus 2019 disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a pandemic infectious disease that causes morbidity and mortality. As a result of high mortality rate among the severe COVID-19 patients, the early detection of the disease stage and early effective interventions are very important in reducing mortality. Hence, it is important to differentiate severe and nonsevere cases from each other. To date, there are no proven diagnostic or prognostic parameters that can be used in this manner. Due to the expensive and not easily accessible tests that are performed for COVID-19, researchers are investigating some parameters that can be easily used. In some recent studies, hematological parameters have been evaluated to see if they can be used as predictive parameters.
In the current study, almost all hematological parameters were used, including the neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, monocyte/lymphocyte ratio, mean platelet volume to lymphocyte ratio, mean platelet volume to platelet ratio, plateletcrit, and D-dimer/fibrinogen ratio, neutrophil/lymphocyte/platelet scoring system, and systemic immune-inflammation index. A total of 750 patients, who were admitted to Ankara City Hospital due to COVID-19, were evaluated in this study. The patients were classified into 2 groups according to their diagnosis (confirmed or probable) and into 2 groups according to the stage of the disease (nonsevere or severe).
The values of the combinations of inflammatory markers and other hematological parameters in all of the patients with severe COVID-19 were calculated, and the predicted values of these parameters were compared. According to results of the study, nearly all of the hematological parameters could be used as potential diagnostic biomarkers for subsequent analysis, because the area under the curve (AUC) was higher than 0.50, especially for the DFR and NLR, which had the highest AUC among the parameters.
Our findings indicate that, the parameters those enhanced from complete blood count, which is a simple laboratory test, can help to identify and classify COVID-19 patients into non-severe to severe groups.
背景/目的：由严重急性呼吸系统综合征冠状病毒 2（SARS-CoV-2）引起的 2019 年冠状病毒病（COVID-19）是一种具有较高发病率和死亡率的大流行传染性疾病。由于重症 COVID-19 患者的死亡率较高，因此早期发现疾病阶段并进行早期有效干预对于降低死亡率非常重要。因此，将重症和非重症患者区分开来非常重要。迄今为止，尚无经过验证的诊断或预后参数可用于此目的。由于 COVID-19 进行的昂贵且不易获得的测试，研究人员正在研究一些易于使用的参数。在一些最近的研究中，评估了血液学参数，以查看它们是否可用作预测参数。
在本研究中，几乎使用了所有的血液学参数，包括中性粒细胞/淋巴细胞比、血小板/淋巴细胞比、单核细胞/淋巴细胞比、平均血小板体积与淋巴细胞比、平均血小板体积与血小板比、血小板比容、D-二聚体/纤维蛋白原比、中性粒细胞/淋巴细胞/血小板评分系统和全身免疫炎症指数。共有 750 名因 COVID-19 入住安卡拉城市医院的患者在本研究中进行了评估。根据诊断（确诊或疑似）和疾病阶段（非重症或重症）将患者分为 2 组。
计算了所有重症 COVID-19 患者的炎症标志物和其他血液学参数组合的值，并比较了这些参数的预测值。根据研究结果，几乎所有的血液学参数都可以作为潜在的诊断生物标志物进行进一步分析，因为曲线下面积（AUC）高于 0.50，尤其是 DFR 和 NLR，它们在参数中的 AUC 最高。
我们的研究结果表明，从全血细胞计数中增强的参数（这是一种简单的实验室测试）可以帮助识别和分类 COVID-19 患者为非重症和重症组。
