目的:慢性肾脏病(CKD)患者易感染SARS-CoV-2,更容易发生严重疾病。重要的是要了解不良结果的预测因素,以优化护理策略。
方法:本研究纳入了93例CKD患者和93例年龄性别匹配的无CKD患者。人口统计数据,临床特征,记录并比较两组之间的血液学指标和结局。嗜中性粒细胞与淋巴细胞比率(NLR),血小板与淋巴细胞比率(PLR),在入住时计算全身免疫炎症指数(SII)(血小板计数×中性粒细胞计数/淋巴细胞计数)和淋巴细胞-CRP比值(LCR),并确定这些标志物与CKD患者疾病死亡率的相关性.
结果:CKD患者患严重疾病的风险更高,和死亡率与非CKD患者相比(72%vs50.5%,p=0.003,36.6%对10.8%,p<0.001,分别)和更可能有更高的免疫炎症指标值(白细胞计数,中性粒细胞,NLR,SII和C反应蛋白,等。)和较低水平的淋巴细胞和LCR。此外,更高水平的NLR,SII,与康复患者相比,死亡的CKD患者的PLR和LCR水平较低。在接收器工作特性曲线分析中,NLR,SII,CKD患者住院死亡率曲线下的PLR和LCR面积分别为0.830、0.811、0.664和0.712。在所有参数中,NLR和SII为我们提供了区分死亡风险较高的患者的最佳能力。根据临界值1180.5,SII预测住院死亡率的敏感性和特异性分别为67.5%和79.6%,分别。NLR的敏感性和特异性分别为85.2%和66.1%,分别,在5.1的截止值。正向逐步Logistic回归分析显示,NLR(≥5.1),SII(≥1180.5)和LCR(≤9)是住院死亡率的预测因子。
结论:我们首次报道,SII能够区分COVID-19感染的CKD患者的生存率较差,在这方面与NLR一样强大。因为SII很容易从血样数据中量化,它可能有助于早期识别和及时治疗生存率较差的CKD患者.
Patients with chronic kidney disease (CKD) are susceptible to SARS-CoV-2 infection and more prone to develop severe disease. It is important to know predictors of poor outcomes to optimize the strategies of care.
93 patients with CKD and 93 age-sex matched patients without CKD were included in the study. Data on demographic, clinical features, hematological indices and outcomes were noted and compared between the groups. Neutrophile to lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune inflammation index (SII) (platelet counts×neutrophil counts/lymphocyte counts) and lymphocyte-to-CRP ratio (LCR) were calculated on admission and the association of these markers with disease mortality in CKD patients was identified.
CKD patients had higher risk of severe disease, and mortality compared to non-CKD patients (72% vs 50.5%, p=0.003, 36.6% vs 10.8%, p<0.001, respectively) and were more likely to have higher values of immuno-inflammatory indices (leukocyte count, neutrophil, NLR, SII and C-reactive protein, etc.) and lower level of lymphocyte and LCR. Also, higher levels of NLR, SII, PLR and lower level of LCR were seen in CKD patients who died compared to those recovered. In a receiver operating characteristic curve analysis, NLR, SII, PLR and LCR area under the curve for in-hospital mortality of CKD patients were 0.830, 0.811, 0.664 and 0.712, respectively. Among all parameters, NLR and SII gave us the best ability to distinguish patients with higher risk of death. Based on the cut-off value of 1180.5, the sensitivity and specificity of the SII for predicting in-hospital mortality were found to be 67.5% and 79.6%, respectively. The corresponding sensitivity and specificity of the NLR were 85.2% and 66.1%, respectively, at the cut-off value of 5.1. Forward stepwise logistic regression analysis showed that NLR (≥5.1), SII (≥1180.5) and LCR (≤9) were predictors for in-hospital mortality.
We report for the first time that SII is able to distinguish COVID-19 infected CKD patients of worse survival and it is as powerful as NLR in this regard. As SII is easily quantified from blood sample data, it may assist for early identification and timely management of CKD patients with worse survival.