颅内动脉支架置入术术后并发高灌注综合征的影响因素分析-现代医学

颅内动脉支架置入术术后并发高灌注综合征的影响因素分析

单位：邢台市中心医院神内三病区, 河北邢台 054000

分类号：R743.3

出版年·卷·期（页码）：2025·53·第九期（1414-1420）

摘要：

目的： 分析颅内动脉支架置入术术后并发高灌注综合征(HPS)的高危因素，并建立列线图预测模型。方法： 纳入2020年1月至2021年12月在本院行颅内动脉支架置入术的200例患者为研究对象，依据术后患者是否并发HPS分为并发HPS组(94例)和未并发HPS组(106例)，采用Lasso和二元Logistic回归分析颅内动脉支架置入术术后并发HPS的影响因素。基于以上结果构建颅内动脉支架置入术术后并发HPS高危风险列线图模型，运用受试者工作特征曲线下面积(AUC)评价模型预测效能。结果： 单因素分析显示，两组患者年龄、高血压史、糖尿病史、颈动脉狭窄程度、颅内侧支循环、术后脑血流量比较，差异均有统计学意义(均P<0.05)。将上述6项行Lasso单因素筛选后均为可疑影响因素。Logistic回归分析显示，年龄≥70岁、高血压史、糖尿病史、重度颈动脉狭窄、颅内侧支循环不良、术后脑血流量异常均是颅内动脉支架置入术术后并发HPS危险因素(P<0.05)。颅内动脉支架置入术术后并发HPS风险列线图预测模型的AUC为0.963(95%CI：0.940~0.987)，灵敏度为0.915，特异度为0.883。采用Bootstrap方法对颅内动脉支架置入术术后并发HPS预测模型执行内部验证，经偏差校正后预测曲线接近理想状态，C-index值为0.927，显示出模型具有较高预测效能，阈值概率为0~1，该模型均能实现正净收益，并且其性能超越了用作对比2条无效线。结论： 年龄≥70岁、高血压史、糖尿病史、重度颈动脉狭窄、颅内侧支循环不良、术后脑血流量异常均是颅内动脉支架置入术术后并发HPS高危因素，临床护理应重点关注并加强防范。

Objective: To analyze the risk factors of hyperperfusion syndrome(HPS) after intracranial artery stent implantation and establish a nomogram prediction model. Methods: A total of 200 patients who underwent intracranial artery stent implantation in our hospital from January 2020 to December 2021 were selected as the research subjects. Based on the occurrence of postoperative HPS, patients were categorized into two groups: the HPS group(n=94) and the non-HPS group(n=106). Lasso and binary Logistic regression analyses were employed to identify the influencing factors for HPS following intracranial artery stenting. A nomogram model for predicting HPS was constructed based on these findings, and the predictive performance of the model was evaluated using the area under the receiver operating characteristic curve(AUC). Results: Univariate analysis revealed statistically significant differences between the two groups in terms of age, history of hypertension, history of diabetes, degree of carotid artery stenosis, intracranial collateral circulation, and postoperative cerebral blood flow(all P<0.05). These six variables were identified as potential influencing factors following Lasso regression screening. Logistic regression analysis demonstrated that age ≥70 years, history of hypertension, history of diabetes, severe carotid artery stenosis, poor intracranial collateral circulation, and abnormal postoperative cerebral blood flow were all independent risk factors for HPS after intracranial artery stenting(all P<0.05). The AUC of the nomogram prediction model for HPS was 0.963(95% CI 0.940-0.987), with a sensitivity of 0.915 and a specificity of 0.883. Internal validation of the HPS prediction model was performed using the Bootstrap method. The bias-corrected prediction curve closely approximated the ideal curve, with a C-index of 0.927, indicating high predictive performance. Across the threshold probability range of 0 to 1, the model consistently demonstrated a positive net benefit, and its performance surpassed that of both comparative null lines. Conclusion: Age ≥70 years, history of hypertension, history of diabetes, severe carotid artery stenosis, poor intracranial collateral circulation, and abnormal postoperative cerebral blood flow are high-risk factors for HPS following intracranial artery stenting. Clinical care should focus on and strengthen preventive measures targeting these factors.

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