Department of Nephrology, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Education and Research Hospital, Istanbul, Turkey.
Department of Nephrology, University of Health Sciences, Bakirkoy Dr. Sadi Konuk Education and Research Hospital, Istanbul, Turkey.
Nefrologia (Engl Ed). 2022 Sep-Oct;42(5):549-558. doi: 10.1016/j.nefroe.2021.09.009.
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.
患有慢性肾脏病（CKD）的患者易感染严重急性呼吸综合征冠状病毒 2（SARS-CoV-2），且更易发展为重症疾病。了解不良结局的预测因素对于优化治疗策略很重要。
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。记录并比较了两组患者的人口统计学、临床特征、血液学指标和结局数据。入院时计算中性粒细胞与淋巴细胞比值（NLR）、血小板与淋巴细胞比值（PLR）、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）和淋巴细胞与 C 反应蛋白比值（LCR），并确定这些标志物与 CKD 患者疾病死亡率的相关性。
与非 CKD 患者相比，CKD 患者发生重症疾病和死亡的风险更高（72%比 50.5%，p=0.003；36.6%比 10.8%，p<0.001），且更可能具有更高的免疫炎症指数（白细胞计数、中性粒细胞、NLR、SII 和 C 反应蛋白等）和较低的淋巴细胞和 LCR 水平。此外，与存活患者相比，死亡的 CKD 患者的 NLR、SII、PLR 水平更高，而 LCR 水平更低。在受试者工作特征曲线分析中，NLR、SII、PLR 和 LCR 对 CKD 患者住院死亡率的曲线下面积分别为 0.830、0.811、0.664 和 0.712。在所有参数中，NLR 和 SII 能够更好地区分死亡风险较高的患者。基于 1180.5 的截断值，SII 预测住院死亡率的灵敏度和特异性分别为 67.5%和 79.6%。NLR 的截断值为 5.1 时，灵敏度和特异性分别为 85.2%和 66.1%。向前逐步逻辑回归分析表明，NLR（≥5.1）、SII（≥1180.5）和 LCR（≤9）是住院死亡率的预测因素。
我们首次报告 SII 能够区分 COVID-19 感染的 CKD 患者的生存情况更差，且其在这方面与 NLR 同样有效。由于 SII 可以从血液样本数据中轻松定量，因此它可能有助于早期识别和及时管理生存情况更差的 CKD 患者。
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