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血管内血栓切除术治疗后前循环串联病变急性缺血性卒中患者的颅内出血预测

Intracranial hemorrhage prediction in acute ischemic stroke patients with anterior circulation tandem lesions following endovascular thrombectomy.

作者信息

Tian Wenqing, Zhou Li, Zhang Yueqi

机构信息

Department of Neurology, Weifang People's Hospital, Shandong Second Medical University, Weifang, China.

School of Clinical Medicine, Shandong Second Medical University, Weifang, China.

出版信息

Front Neurol. 2025 Aug 29;16:1598203. doi: 10.3389/fneur.2025.1598203. eCollection 2025.

Abstract

BACKGROUND

Acute ischemic stroke (AIS) patients with anterior circulation tandem lesions (TL) face a heightened risk of hemorrhage following endovascular thrombectomy (EVT). Predictive models specifically for this complication in the TL population are currently lacking.

METHODS

This retrospective cohort study analyzed 200 AIS patients with anterior circulation TL who underwent EVT. Least Absolute Shrinkage and Selection Operator regression was used for feature selection. Multivariable logistic regression (LR) models predicting intracranial hemorrhage (ICH) and symptomatic intracranial hemorrhage (sICH) risk were developed and visualized as nomograms. Model discrimination was evaluated using the area under the receiver operating characteristic curve (AUC).

RESULTS

After EVT, ICH occurred in 92 patients (46%) and sICH in 24 patients (12%). The LR model for ICH identified diabetes [odd ratio (OR) 2.454, 95% CI 1.137-5.297], drinking history (OR 2.230, 95% CI 1.160-4.288), and lower modified Thrombolysis in Cerebral Infarction (mTICI) score (OR 0.547, 95% CI 0.311-0.961) as significant independent predictors (AUC = 0.712). The LR model for sICH identified lower Glasgow Coma Scale (GCS) score (OR 0.820, 95% CI 0.695-0.968), lower mTICI score (OR 0.398, 95% CI 0.182-0.868), and lower Alberta Stroke Program Early CT Score (ASPECTS) (OR 0.795, 95% CI 0.641-0.984) as significant independent predictors (AUC = 0.830). Nomograms effectively quantified the contribution of predictors to outcome probabilities.

CONCLUSION

In AIS patients with anterior circulation TL undergoing EVT, diabetes, drinking history, and lower mTICI score independently predict ICH risk, while lower GCS score, lower mTICI score, and lower ASPECTS independently predict sICH risk. The nomograms provide practical tools for individualized risk assessment, aiding clinical decision-making and perioperative management in this high-risk cohort.

摘要

背景

患有前循环串联病变(TL)的急性缺血性卒中(AIS)患者在接受血管内血栓切除术(EVT)后发生出血的风险更高。目前缺乏专门针对TL人群中这种并发症的预测模型。

方法

这项回顾性队列研究分析了200例接受EVT的前循环TL的AIS患者。使用最小绝对收缩和选择算子回归进行特征选择。开发了预测颅内出血(ICH)和症状性颅内出血(sICH)风险的多变量逻辑回归(LR)模型,并将其可视化为列线图。使用受试者操作特征曲线(AUC)下的面积评估模型的辨别力。

结果

EVT后,92例患者(46%)发生ICH,24例患者(12%)发生sICH。ICH的LR模型确定糖尿病[比值比(OR)2.454,95%可信区间1.137 - 5.297]、饮酒史(OR 2.230,95%可信区间1.160 - 4.288)和较低的改良脑梗死溶栓(mTICI)评分(OR 0.547,95%可信区间0.311 - 0.961)为显著的独立预测因素(AUC = 0.712)。sICH的LR模型确定较低的格拉斯哥昏迷量表(GCS)评分(OR 0.820,95%可信区间0.695 - 0.968)、较低的mTICI评分(OR 0.398,95%可信区间0.182 - 0.868)和较低的阿尔伯塔卒中项目早期CT评分(ASPECTS)(OR 0.795,95%可信区间0.641 - 0.984)为显著的独立预测因素(AUC = 0.830)。列线图有效地量化了预测因素对结局概率的贡献。

结论

在接受EVT的前循环TL的AIS患者中,糖尿病、饮酒史和较低的mTICI评分独立预测ICH风险,而较低的GCS评分、较低的mTICI评分和较低的ASPECTS独立预测sICH风险。列线图为个体化风险评估提供了实用工具,有助于该高危队列中的临床决策和围手术期管理。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6d12/12426950/16ece084c595/fneur-16-1598203-g001.jpg

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