中国卒中杂志2025，Vol.20Issue(12)：1527-1538,12.DOI:10.3969/j.issn.1673-5765.2025.12.008
前循环大血管闭塞性急性缺血性卒中血管内取栓治疗再通后症状性颅内出血列线图预测模型的建立与验证
Establishment and Validation of a Nomogram Prediction Model for Symptomatic Intracranial Hemorrhage after Recanalization with Endovascular Thrombectomy in Anterior Circulation Large Vessel Occlusive Acute Ischemic Stroke
摘要
Abstract
Objective To investigate the risk factors for symptomatic intracranial hemorrhage(sICH)after recanalization with endovascular thrombectomy(EVT)in patients with anterior circulation large vessel occlusive acute ischemic stroke(AIS),and to establish and validate a nomogram prediction model. Methods Patients with anterior circulation large vessel occlusive AIS who underwent EVT and achieved successful recanalization at the Department of Neurointervention,the Affiliated Lianyungang Hospital of Xuzhou Medical University from January 2021 to December 2024 were retrospectively enrolled.Their clinical data were collected and patients were followed up until 36 hours post-treatment.Patients were divided into the sICH group and the non-sICH group based on the occurrence of sICH after EVT.Patients enrolled from January 2021 to December 2023 were assigned to the training set for model development,while those enrolled from January to December 2024 comprised the validation set for model performance evaluation.In the training set,variables with P＜0.05 in univariate analysis were included in the least absolute shrinkage and selection operator(LASSO)regression and multivariate logistic regression analysis.Independent risk factors for sICH after recanalization with EVT in patients with anterior circulation large vessel occlusive AIS were identified and used to construct a nomogram prediction model.The predictive performance of the model was evaluated in the validation set using the ROC curve,decision curve analysis(DCA),and calibration curve. Results A total of 316 patients with anterior circulation large vessel occlusive AIS were included,including 224 in the training set and 92 in the validation set.In the training set,37 patients(16.52％)developed sICH.After univariate analysis,twelve variables(P＜0.05)were initially included in the LASSO regression analysis,and six variables were ultimately identified:stress hyperglycemia ratio,neutrophil-to-lymphocyte ratio,number of stent retriever passes,history of diabetes mellitus,NIHSS score,and internal carotid artery as the responsible vessel.Multivariate logistic regression analysis showed that a higher stress hyperglycemia ratio(OR 20.24,95％CI 4.76-86.08,P＜0.001),a greater number of stent retriever passes(OR 1.78,95％CI 1.18-2.67,P=0.005),and a history of diabetes mellitus(OR 4.64,95％CI 1.63-13.19,P=0.004)were independent risk factors for sICH after EVT recanalization in patients with anterior circulation large vessel occlusive AIS.The ROC curve analysis revealed that the AUC values of the training set and the validation set were 0.86 and 0.76,respectively.The calibration curve demonstrated good consistency between predicted and observed values,and the DCA indicated that the prediction model yielded a favorable net benefit across a wide range of risk thresholds. Conclusions The nomogram prediction model constructed in this study demonstrates a good ability to predict the risk of sICH after recanalization with EVT in patients with anterior circulation large vessel occlusive AIS.关键词
急性缺血性卒中/症状性颅内出血/危险因素/预测模型Key words
Acute ischemic stroke/Symptomatic intracranial hemorrhage/Risk factor/Prediction model分类
医药卫生引用本文复制引用
杨志超,黄正千,赵宜坤,孙勇..前循环大血管闭塞性急性缺血性卒中血管内取栓治疗再通后症状性颅内出血列线图预测模型的建立与验证[J].中国卒中杂志,2025,20(12):1527-1538,12.基金项目
2023年度连云港市老龄健康科研项目(L202301)2023年度连云港市第一人民医院博士科研启动基金(BS202314) （L202301）
