摘要
目的探讨CTP定量分析脑低灌注区体积、缺血核心体积、缺血组织可恢复比率(PRR)与急性缺血性脑卒中(AIS)预后的关系。方法选取2019年4月至2024年1月淮安市第一人民医院196例AIS患者,根据患者治疗后30天的改良Rankin评分量表(mRS)评分分为预后良好组(n=72)和不良组(n=124),收集两组CTP定量参数和其他临床指标,利用Logistic回归模型分析各指标与AIS预后关系,利用列线图进行可视化展示,绘制受试者工作特征(ROC)曲线分析各指标预测AIS预后的价值。结果结果显示低灌注区体积、缺血核心体积、缺血组织可恢复比率(PRR)、治疗前NIHSS评分、mRS评分在预后良好组和不良组之间差异有统计学意义(P<0.05)。经过递归消除法(RFE)进行变量筛选,Logistic模型纳入治疗前NIHSS评分(OR=2.227,P=0.002)、缺血核心体积(OR=1.780,P<0.001)、PRR(OR=1.208,P=0.006),预测模型的交叉验证AUC为0.901。结论AIS患者缺血核心体积、PRR、治疗前NIHSS评分为AIS预后的独立预测因子,并与患者预后明显相关,在预判预后中具有重要价值。
Objective To explore the relationship between CTP quantitative analysis of cerebral hypoperfusion volume,ischemic core volume,ischemic tissue recoverable ratio(PRR)and prognosis of acute ischemic stroke(AIS).Methods A total of 196 patients with AIS from Huai'an First People's Hospital from April 2019 to January 2024 were selected and divided into a good prognosis group(n=72)and a poor group(n=124)according to the modified Rankin Rating Scale(mRS)score 30 days after treatment.Two groups of CTP quantitative parameters and other clinical indicators were collected.Logistic regression model was used to explore the relationship between each indicator and the prognosis of AIS.The nomogram was used for visual display,and the receiver operating characteristic(ROC)curve was drawn to analyze the value of each indicator in predicting the prognosis of AIS.Results The results showed that the volume of hypoperfusion area,ischemic core volume,PRR,NIHSS score before treatment,and mRS score before treatment were significantly different between the good prognosis group and the poor prognosis group(P<0.05).After recursive elimination(RFE)for variable filtering,logistic model included NIHSS score before treatment(OR=2.227,P=0.002),PRR(OR=1.208,P=0.006),AUC=0.901,ischemic core volume(OR=1.780,P<0.001).Conclusion The ischemic core volume,PRR,and admission NIHSS score of AIS patients were independent predictors of prognosis prediction in acute ischemic stroke,and were significantly correlated with patient prognosis,which were of great value in predicting prognosis.
作者
颜龙
谢丽响
沈伟
黄敏
胡春峰
YAN Long;XIE Li-xiang;SHEN Wei;HUANG Min;HU Chun-feng(Department of Radiology,the Affiliated Hospital of Xuzhou Medical University,Xuzhou 221002,Jiangsu Province,China;Department of Imaging,Huai'an People's Hospital of Hongze District,Huai'an 223400,Jiangsu Province,China;Philips(China)Investment Co.,Ltd,Hangzhou 310000,Zhejiang Province,China;Huai'an First People's Hospital,Huai'an 223399,Jiangsu Province,China)
出处
《中国CT和MRI杂志》
2024年第11期1-3,共3页
Chinese Journal of CT and MRI
基金
淮安卫生健康科研项目(HAWJZ202105)。