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    全身免疫炎症指数对急性缺血性脑卒中患者发生卒中相关性肺炎的预测价值

    Predictive value of systemic immune-inflammation index for stroke-associated pneumonia in patients with acute ischemic stroke

    • 摘要: 目的 探讨全身免疫炎症指数(SII)对急性缺血性脑卒中(AIS)患者发生卒中相关性肺炎(SAP)的预测价值。方法 回顾性纳入2020年1月—2020年12月徐州医科大学附属医院收治的发病24 h内的305例AIS患者,依据是否发生SAP将患者分为SAP组及非SAP组。收集患者的一般资料,包括性别、年龄及病史。记录患者入院时急性脑梗死牛津郡社区卒中项目(OCSP)分型、美国国立卫生院卒中量表(NIHSS)评分及有无吞咽困难、鼻饲治疗、使用制酸剂、预防性使用抗生素等资料。记录患者入院后24 h之内外周静脉血实验室检查指标,包括血常规、血生化资料,计算SII。采用单因素及多因素Logistic回归分析确定SII与SAP的独立相关性,应用受试者工作特征(receiver operating characteristic, ROC)曲线评价SII对SAP的预测价值。结果 305例AIS患者中发生SAP有39例(12.79%),未发生SAP 266例(87.21%)。单因素分析结果显示,SAP组SII高于非SAP组,差异有统计学意义(P<0.05)。Logistic回归分析显示,SII为SAP的独立危险因素。ROC曲线分析显示,SII预测SAP的曲线下面积为0.843(95%CI:0.798~0.882),当SII为最佳截断值885.05时,其预测AIS患者发生SAP的灵敏度为79.5%,特异度85.0%。结论 SII是AIS患者发生SAP的潜在独立危险因素,对SAP的发生有一定的预测价值。

       

      Abstract: Objective To explore the predictive value of systemic immune-inflammation index (SII) for stroke-associated pneumonia (SAP) in patients with acute ischemic stroke (AIS). Methods A total of 305 AIS patients who were admitted to the Affiliated Hospital of Xuzhou Medical University from January 2020 to December 2020 were retrospectively enrolled. According to the presence of SAP, the patients were divided into two groups: an SAP group and a non-SAP group. Their general information was collected, including gender, age, and disease history. Their OCSP classification of acute cerebral infarction and NIHSS score at admission, as well as the presence of dysphagia, nasal feeding, the use of antacids, and preventive use of antibiotics were recorded. The laboratory indexes of their peripheral venous blood were recorded within 24 h after admission, including blood routine and blood biochemical test, so as to calculate SII. Univariate and multivariate logistic regression analyses were used to assess the independent correlation between SII and SAP. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of SII to SAP. Results Among 305 AIS patients, there were 39 patients (12.79%) who developed SAP, and 266 patients (87.21%) without SAP. According to univariate analysis, the SAP group presented a higher SII than the non-SAP group (P<0.05). Logistic regression analysis showed that SII was an independent risk factor for SAP. According to ROC curve analysis, the area under the curve of SII to predict SAP was 0.843 (95% CI: 0.798-0.882). When the cut-off value of SII in predicting SAP in AI patients was set as 885.05, the sensitivity was 79.5% and the specificity was 85.0%. Conclusions SII is a potential independent risk factor for SAP in AIS patients, which has certain predictive value.

       

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