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目的:探讨炎症标志物对接受血管内治疗的前循环大血管闭塞性卒中患者发生卒中相关性感染（stroke-associated infection, SAI）风险的预测价值。方法:回顾性纳入2016年至2020年期间在南京医科大学附属南京医院接受血管内治疗的前循环大血管闭塞性卒中患者。对SAI组与非SAI组患者的临床资料进行比较。应用多变量n logistic回归分析筛选SAI的独立影响因素，然后根据这些影响因素构建预测列线图并验证其临床应用效能。n 结果:研究期间纳入409例患者，年龄（71.3±11.7）岁，男性250例（61.1%），基线中位美国国立卫生研究院卒中量表（Naitonal Institutes of Health Stroke Scale, NIHSS）评分16分，119例（29.1%）接受静脉溶栓，376例（91.9%）术后血管成功再通，293例（71.6%）发生SAI。单变量分析显示，SAI组年龄、心房颤动比例、入院时NIHSS评分、空腹血糖、甘油三酯、超敏C反应蛋白（high-sensitivity C-reactive protein, hs-CRP）、白细胞计数、中性粒细胞计数、中性粒细胞/淋巴细胞比值（neutrophil-to-lymphocyte ratio, NLR）以及血小板/淋巴细胞比值（platelet-to-lymphocyte ratio, PLR）显著高于非SAI组（n P均<0.05）。多变量logistic回归分析显示，年龄、入院时NIHSS评分、空腹血糖、hs-CRP、白细胞计数、中性粒细胞计数以及NLR是SAI的独立影响因素（n P均<0.05）。ROC曲线分析显示，多种炎症标志物（hs-CRP、白细胞计数、中性粒细胞计数以及NLR）联合预测SAI的价值显著优于单项炎症标志物（n P<0.01），其曲线下面积为0.782（95%置信区间0.719~0.846），预测敏感性和特异性分别为80.6%和64.5%。决策曲线分析显示，与传统指标相比，基于炎症相关指标（hs-CRP、白细胞计数以及NLR）的预测列线图对预测SAI具有更高的净获益能力。n 结论:hs-CRP、白细胞计数以及NLR可用于预测接受血管内治疗的急性缺血性卒中患者发生SAI的风险。“,”Objective:To investigate the predictive value of inflammatory markers for the risk of stroke-associated infection (SAI) in patients with anterior circulation large vessel occlusive stroke who received endovascular therapy.Methods:Patients with anterior circulation large vessel occlusive stroke received endovascular treatment in Nanjing First Hospital, Nanjing Medical University from 2016 to 2020 were retrospectively enrolled. The clinical data of SAI group and non-SAI group were compared. Multivariate n logistic regression analysis was used to screen the independent influencing factors of SAI, and then the predictive nomogram was established according to these influencing factors to verify its clinical application efficiency.n Results:A total of 409 patients were enrolled during the study. Their age was 71.3±11.7 years, and 250 were male (61.1%). The median baseline Naitonal Institutes of Health Stroke Scale (NIHSS) score was 16. One hundred and nineteen patients (29.1%) received intravenous thrombolysis, 376 (91.9%) were successfully recanalized after endovascular therapy, and 293 (71.6%) developed SAI. Univariate analysis showed that age, atrial fibrillation ratio, NIHSS score at admission, fasting blood glucose, triglyceride, high sensitivity C reactive protein (hs-CRP), leukocyte count, neutrophil count, neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) were significantly higher than those in the non-SAI group (all n P<0.05). Multivariaten logistic regression analysis showed that age, NIHSS score at admission, fasting blood glucose, hs-CRP, leukocyte count, neutrophil count and NLR were the independent influencing factors of SAI (n P<0.05). Receiver operating characteristics curve analysis showed that the predictive value of multiple inflammatory markers (hs-CRP, leukocyte count, neutrophil count and NLR) for SAI was significantly better than that of the single inflammatory marker (n P<0.01). The area under the curve was 0.782 (95% confidence interval 0.719-0.846), and the predictive sensitivity and specificity were 80.6% and 64.5% respectively. Decision curve analysis showed that compared with the traditional indicators, the predictive nomogram based on inflammation related indicators (hs-CRP, leukocyte count and NLR) had a higher net profitability for predicting SAI.n Conclusion:The hs-CRP, leukocyte count and NLR can be used to predict the risks of SAI in patients with acute ischemic stroke receiving endovascular therapy.