Xu H M, Liu J, Gu C G, Zhang J D, Liu M R, Yuan F L, Liu S Y
Department of Laboratory Medicine, the Third Central Hospital of Tianjin, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases,Artificial Cell Engineering Technology Research Center, Tianjin Institute of Hepatobiliary Disease, Tianjin 300170, China.
Department of Laboratory Medicine, Tianjin Jinnan Hospital, Tianjin 300350, China.
Zhonghua Yu Fang Yi Xue Za Zhi. 2021 Jul 6;55(7):890-895. doi: 10.3760/cma.j.cn112150-20200705-00973.
To provide new ideas for clinical diagnosis and treatment of coronavirus disease 2019 (COVID-19), this study explore the expression level and prognostic value of platelet parameters in mild, moderate and severe COVID-19. This is a retrospective analysis. From January to May 2020, a total of 69 patients who were diagnosed with COVID-19 in the Third Central Hospital and the Jinnan Hospital (both situated in Tianjin) were enrolled in the disease group. According to the severity, these patients were divided into mild group (15 cases), moderate group (46 cases), and severe group (8 cases). In the same period, 70 non-infected patients were enrolled in control group. The level of white blood cell count (WBC), absolute neutrophil count (NEU#), absolute lymphocyte count (LY#), neutrophil-lymphocyte ratio (NLR), red blood cell count (RBC), hemoglobin (Hb), platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), and platelet-large contrast ratio (P-LCR) before and after treatment were analyzed. Binary logistic regression analysis is used to establish a mathematical model of the relationship between these indexes and the outcome of severe COVID-19 patients. The receiver operating characteristic(ROC) curve is used to further explore the prognosis value of MPV, P-LCR, NLR separately and jointly in COVID-19 patients. Compare to the control group, WBC and NE# increase (=-5.63, <0.01;=-9.19,<0.01) and LY# decrease (=-9.34, <0.01) in the severe group; NLR increase with the aggravation of the disease, there is significant difference between groups (=17.61, <0.01); PLT, PDW, MPV and P-LCR decrease with the aggravation of the disease, there is significant difference between groups (=9.47, <0.01; =11.41, <0.01; =16.76, <0.01; =13.97, <0.01). Binary logistic regression analysis shows MPV, P-LCR and NLR have predictive value for severe COVID-19 patients. There is a negative correlation between MPV, P-LCR and severe COVID-19 patients (=1.004, =0.034; =1.097, =0.046). There is a positive correlation between NLR and severe COVID-19 patients (=1.052, =0.016). MPV and P-LCR of patients with good prognosis after treatment were significantly higher than those before treatment (=-6.47, <0.01; =-5.36, <0.01). NLR was significantly lower than that before treatment (=-8.13, <0.01). MPV and P-LCR in poor prognosis group were significantly lower than those before treatment (=-9.46, <0.01; =-6.81, <0.01). NLR was significantly higher than that before treatment (=-3.24, <0.01). There were significant differences between good and poor prognosis groups before and after treatment in MPV, P-LCR and NLR (<0.01). Combination of these three indexes, ROC shows the AUC is 0.931, the sensitivity is 91.5%, the specificity is 94.1%, the positive predictive value is 88.9%, and the negative predictive value is 87.4%, which is better than any of these indexes separately. Changes in these parameters are closely related to clinical stage of COVID-19 patients. MPV, P-LCR and NLR are of great value in the prediction and prognosis of severe COVID-19 patients.
为了给2019冠状病毒病（COVID-19）的临床诊断和治疗提供新思路，本研究探讨了血小板参数在轻度、中度和重度COVID-19中的表达水平及预后价值。这是一项回顾性分析。2020年1月至5月，共有69例在天津市第三中心医院和津南医院被诊断为COVID-19的患者纳入疾病组。根据病情严重程度，这些患者被分为轻症组（15例）、中症组（46例）和重症组（8例）。同期，70例未感染患者纳入对照组。分析治疗前后白细胞计数（WBC）、中性粒细胞绝对值（NEU#）、淋巴细胞绝对值（LY#）、中性粒细胞与淋巴细胞比值（NLR）、红细胞计数（RBC）、血红蛋白（Hb）、血小板计数（PLT）、平均血小板体积（MPV）、血小板分布宽度（PDW）和血小板大型比率（P-LCR）水平。采用二元逻辑回归分析建立这些指标与重症COVID-19患者预后关系的数学模型。采用受试者工作特征（ROC）曲线进一步探讨MPV、P-LCR、NLR单独及联合对COVID-19患者的预后价值。与对照组相比，重症组WBC和NE#升高（=-5.63，<0.01；=-9.19，<0.01），LY#降低（=-9.34，<0.01）；NLR随病情加重而升高，组间差异有统计学意义（=17.61，<0.01）；PLT、PDW、MPV和P-LCR随病情加重而降低，组间差异有统计学意义（=9.47，<0.01；=11.41，<0.01；=16.76，<0.01；=13.97，<0.01）。二元逻辑回归分析显示，MPV、P-LCR和NLR对重症COVID-19患者有预测价值。MPV、P-LCR与重症COVID-19患者呈负相关（=1.004，=0.034；=1.097，=0.046）。NLR与重症COVID-19患者呈正相关（=1.052，=0.016）。治疗后预后良好患者的MPV和P-LCR显著高于治疗前（=-6.47，<0.01；=-5.36，<0.01）。NLR显著低于治疗前（=-8.13，<0.01）。预后不良组的MPV和P-LCR显著低于治疗前（=-9.46，<0.01；=-6.81，<0.01）。NLR显著高于治疗前（=-3.24，<0.01）。MPV、P-LCR和NLR在预后良好组和预后不良组治疗前后差异有统计学意义（<0.01）。这三个指标联合，ROC曲线显示AUC为0.931，灵敏度为91.5%，特异度为94.1%，阳性预测值为88.9%，阴性预测值为87.4%，优于任何一个单独指标。这些参数的变化与COVID-19患者的临床分期密切相关。MPV、P-LCR和NLR对重症COVID-19患者的预测和预后具有重要价值。
