全身免疫炎症指数与急性缺血性卒中出血转化及预后的相关性分析

Correlation Analysis of Systemic Immune-Inflammation Index with Hemorrhagic Transformation and Prognosis of Acute Ischemic Stroke

摘要: 目的：探讨全身免疫炎症指数(Systemic Immune-Inflammation Index, SII)对出血转化(Hemorrhagic Transformation, HT)和急性缺血性卒中患者发病90天后的神经功能预后的预测价值。方法：本研究筛选2020年8月至2021年8月烟台毓璜顶医院急诊内科收治的首次发病24小时内的脑梗死患者的临床资料进行回顾性分析。根据患者发病1周内是否发生HT将患者分为HT组、非HT组。根据入院3小时内完成的NIHSS评分分为轻度组(NIHSS ≤ 5)、中重度组(NIHSS ≥ 6)，根据AIS患者发病90天后的改良Rankin量表评分分别将轻度组与中重度组患者分为预后良好组(mRS评分 ≤ 2分)和预后不良组(mRS评分 ≥ 3分)。通过单因素及多因素Logistic回归分析AIS患者发生HT及患者发病90 d预后的独立危险因素，使用ROC曲线评估SII对HT及预后不良的预测价值。结果：1) 多因素Logistic回归分析显示，在校正性别、年龄等混杂因素后，SII (OR = 1.874. 95% CI 1.126~1.438, P = 0.013)是AIS患者发生HT的独立危险因素。2) 多因素Logistic回归分析显示，在校正了性别、年龄等混杂因素后，在轻度卒中患者中，SII (OR = 1.009. 95% CI 1.002~1.023, P = 0.012)是AIS患者预后不良的独立危险因素。在中重度卒中患者中，SII (OR = 1.001. 95% CI 0.982~1.001, P = 0.042)同样是AIS患者预后不良的独立危险因素。3) 构建ROC曲线发现SII、NLR、PLR预测HT的AUC值为0.857、0.832、0.848 (P < 0.001)，且差异有统计学意义(P < 0.05)。SII、NLR、PLR预测患者预后不良的AUC值为0.750、0.704、0.747 (P < 0.001)，SII与NLR的差异有统计学意义(P < 0.05)，与PLR的差异无统计学意义(P > 0.05)。结论：SII是首次脑梗死患者发生HT及90 d预后的危险因素，且SII在预测脑梗死发生HT较NLR及PLR更加准确，SII在预测发病90天预后方面与PLR准确性基本相同，两者均比NLR更加准确。

Abstract: Objective: To investigate the predictive value of Systemic Immune-inflammation Index (SII) for hemorrhagic transformation (HT) and neurological prognosis 90 days after the onset of acute ischemic stroke. Methods: The clinical data of patients with cerebral infarction who were admitted to the emergency medicine department of Yantai Yuhuangding Hospital within 24 hours of the first onset from August 2020 to August 2021 were retrospectively selected and analyzed. The patients were divided into HT group and non-HT group according to whether HT occurred within 1 week of onset. According to the NIHSS score completed within 3 hours of admission, they were divided into mild group (NIHSS ≤ 5) and moderate-severe group (NIHSS ≥ 6). According to the modified Rankin Scale scores after 90 days onset of AIS, the patients in the mild group and the moderate-severe group were divided into a good prognosis group (mRS score ≤ 2 points) and a poor prognosis group (mRS score ≥ 3 points). Univariate and multivariate Logistic regression was used to analyze the independent risk factors of HT in AIS patients and the prognosis of patients at 90 days after onset. The receiver operating characteristic curve (ROC) was used to evaluate the predictive value of SII for HT and poor prognosis. Results: 1) Multivariate Logistic regression analysis showed that after adjusting for confounding factors such as gender and age, SII (OR = 1.874. 95% CI 1.126~1.438, P = 0.013) was an independent risk factor for HT in AIS patients. 2) Multivariate Logistic regression analysis showed that after adjusting for confounding factors such as gender and age, among patients with mild stroke, SII (OR = 1.009. 95% CI 1.002~1.023, P = 0.012) was an independent risk factor for poor prognosis of AIS patients. Among patients with moderate to severe stroke, SII (OR = 1.001. 95% CI 0.982~1.001, P = 0.042) were also independent risk factors of poor prognosis in AIS patients. 3) The ROC curve was constructed and it was found that the AUC values of SII, NLR, and PLR for predicting HT were 0.857, 0.832, and 0.848 (P < 0.001), and the differences were statistically significant (P < 0.05). The AUC values of SII, NLR, and PLR for predicting poor prognosis of patients were 0.750, 0.704, and 0.747 (P < 0.001). It was found that SII in predicting poor prognosis was more accurate than NLR (P < 0.05), but there was no statistical difference between the accuracy of PLR (P > 0.05). Conclusion: SII is a risk factor for HT and 90-day prognosis in patients with first cerebral infarction, and SII is more accurate than NLR and PLR in predicting HT in cerebral infarction. SII is basically the same as PLR in predicting 90-day prognosis, and both are more accurate than NLR more precise.