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

doi:10.3969/j.issn.1673-5765.2025.12.008

中国卒中杂志 ›› 2025, Vol. 20 ›› Issue (12): 1527-1538.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

杨志超^1，2，黄正千¹，赵宜坤¹，孙勇¹

1 连云港 222000 徐州医科大学附属连云港医院神经外科
2 灌南县第一人民医院神经外科

收稿日期:2025-01-17 修回日期:2025-12-10 接受日期:2025-12-12 出版日期:2025-12-20 发布日期:2025-12-20
通讯作者: 孙勇 sunyong@njmu.edu.cn
基金资助:
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）

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

YANG Zhichao^1,2, HUANG Zhengqian¹, ZHAO Yikun¹, SUN Yong¹

1 Department of Neurosurgery, The Affiliated Lianyungang Hospital of Xuzhou Medical University, Lianyungang 222000, China
2 Department of Neurosurgery, The First People’s Hospital of Guannan County, Lianyungang 222500, China

Received:2025-01-17 Revised:2025-12-10 Accepted:2025-12-12 Online:2025-12-20 Published:2025-12-20
Contact: SUN Yong, E-mail: sunyong@njmu.edu.cn

摘要/Abstract

摘要： 目的探讨前循环大血管闭塞性急性缺血性卒中（acute ischemic stroke，AIS）患者血管内取栓治疗（endovascular thrombectomy，EVT）再通后发生症状性颅内出血（symptomatic intracranial hemorrhage，sICH）的危险因素，建立列线图预测模型并进行验证。
方法回顾性纳入2021年1月—2024年12月在徐州医科大学附属连云港医院神经介入科接受EVT并成功再通的前循环大血管闭塞性AIS患者，收集其临床资料并随访至治疗后36 h。根据术后是否发生sICH，将患者分为sICH组和非sICH组。将2021年1月—2023年12月纳入的患者作为训练集，用来构建预测模型；将2024年1—12月纳入的患者作为验证集，用来评估模型性能。在训练集中，经单因素分析后，将P＜0.05的变量纳入最小绝对值压缩和选择算子（least absolute shrinkage and selection operator，LASSO）回归和多因素logistic回归分析，最终筛选出前循环大血管闭塞性AIS患者EVT再通后发生sICH的独立危险因素，用于构建列线图预测模型。采用ROC曲线的AUC、决策曲线分析（decision curve analysis，DCA）及校准曲线在验证集中对模型的预测性能进行评估。
结果共纳入316例前循环大血管闭塞性AIS患者，其中训练集224例，验证集92例。训练集中有37例（16.52%）发生了sICH，单因素分析后共12个变量（P＜0.05）纳入LASSO回归，最终筛选出6个变量：应激性高血糖比值、中性粒细胞与淋巴细胞比值、支架回收次数、糖尿病病史、NIHSS评分及责任血管为颈内动脉。多因素logistic回归分析显示，较高的应激性高血糖比值（OR 20.24，95%CI 4.76～86.08，P＜0.001）、较多的支架回收次数（OR 1.78，95%CI 1.18～2.67，P=0.005）和有糖尿病病史（OR 4.64，95%CI 1.63～13.19，P=0.004）是前循环大血管闭塞性AIS患者EVT再通后发生sICH的独立危险因素。ROC曲线分析显示训练集和验证集的AUC分别为0.86和0.76，校准曲线显示预测值与实际值一致性较好，DCA显示模型在较宽的风险阈值范围内具有较好的净获益。
结论本研究所构建的列线图预测模型能够较好地预测前循环大血管闭塞性AIS患者EVT再通后发生sICH的风险。

文章导读： 前循环大血管闭塞性急性缺血性卒中患者血管内取栓治疗再通后发生症状性颅内出血的危险因素较多，本研究基于患者既往史、血管内取栓治疗情况及实验室检查等临床资料，构建了列线图预测模型。该模型有较好的区分能力和校准效能，能够为临床医师提供直观、全面的诊疗决策依据，有助于实施有效的预防措施，从而降低症状性颅内出血的发生风险。

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

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.

Key words: Acute ischemic stroke; Symptomatic intracranial hemorrhage; Risk factor; Prediction model

中图分类号:

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.

YANG Zhichao, HUANG Zhengqian, ZHAO Yikun, SUN Yong. 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[J]. Chinese Journal of Stroke, 2025, 20(12): 1527-1538.

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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

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