SII、NAR与急性脑梗死患者静脉溶栓短期预后的相关性分析
Analysis of the Correlation between SII, NAR and Short-Term Prognosis of Intravenous Thrombolysis in Patients with Acute Cerebral Infarction

目的：分析全身免疫炎症指数(SII)、中性粒细胞与白蛋白比值(NAR)与急性脑梗死静脉溶栓短期预后的相关性。方法：通过收集2021年9月至2023年9月就诊于安徽医科大学第二附属医院卒中中心的199例发病4.5小时内采用阿替普酶静脉溶栓的急性脑梗死患者的临床资料，根据患者3个月的mRS评分，将患者的短期预后分为预后良好组及预后不良组。比较两组一般资料及SII、NAR，并将有统计学差异的单因素分析指标纳入二元Logistic回归分析中探讨影响短期预后的独立因素，并采用ROC曲线探讨SII、NAR对短期预后的预测价值。结果：两组结果相比，心房颤动病史、SII、NAR、白细胞计数、总胆红素、肌酐、甘油三酯均有统计学意义(P < 0.05)。二元Logistic回归分析结果显示SII、NAR是预后不良的独立影响因素(P < 0.05)。ROC曲线分析显示，SII预测不良预后的曲线下面积0.826，95.0%可信区间(0.755~0.898, P < 0.05)，最佳截断值781.16，特异度96.2%，敏感度52.5%；NAR预测预后的曲线下面积0.813，95.0%可信区间(0.735~0.891, P < 0.05)，最佳截断值126.31，特异度83.6%，敏感度67.5%；联合预测曲线下面积0.839，95.0%可信区间(0.769~0.910, P < 0.05)，特异度91.2%，敏感度62.5%。结论：溶栓前高SII及高NAR与急性脑梗死患者静脉溶栓后的短期不良预后独立正相关，并可用于患者预后不良的预测，且预测价值二者联合高于SII，SII高于NAR。
Objective: To analyze the correlation between systemic immune inflammation index (SII), neutrophil to albumin ratio (NAR) and short-term prognosis of intravenous thrombolysis in acute cerebral infarction. Methods: The clinical data of 199 patients with acute cerebral infarction who underwent intravenous thrombolysis with alteplase within 4.5 hours of onset in the stroke center of the Second Affiliated Hospital of Anhui Medical University from September 2021 to September 2023 were collected. According to the mRS score of 3 months, the short-term prognosis of patients was divided into good prognosis group and poor prognosis group. The general data, SII and NAR of the two groups were compared, and the univariate analysis indexes with statistical differences were included in the binary logistic regression analysis to explore the independent factors affecting the short-term prognosis, and the ROC curve was used to explore the predictive value of SII and NAR for short-term prognosis. Results: Compared with the results of the two groups, the history of atrial fibrillation, SII, NAR, white blood cell count, total bilirubin, creatinine and triglyceride were statistically significant (P < 0.05). Binary Logistic regression analysis showed that SII and NAR were independent influencing factors of poor prognosis (P < 0.05). ROC curve analysis showed that the area under the curve of SII predicting poor prognosis was 0.826, 95.0% confidence interval (0.755~0.898, P < 0.05), the best cut-off value was 781.16, the specificity was 96.2%, and the sensitivity was 52.5%. The area under the curve of NAR predicting prognosis was 0.813, 95.0% confidence interval (0.735~0.891, P < 0.05), the best cut-off value was 126.31, the specificity was 83.6%, and the sensitivity was 67.5%. The area under the combined prediction curve was 0.839, 95.0% confidence interval