中国卒中杂志2025，Vol.20Issue(12)：1499-1507,9.DOI:10.3969/j.issn.1673-5765.2025.12.005
症状性颅内动脉中重度狭窄脑梗死患者早期神经功能恶化预测模型的构建与验证
Development and Validation of an Early Neurological Deterioration Prediction Model for Patients with Cerebral Infarction Caused by Moderate-to-Severe Symptomatic Intracranial Arterial Stenosis
摘要
Abstract
Objective To analyze the risk factors for early neurological deterioration(END)in patients with cerebral infarction caused by moderate-to-severe symptomatic intracranial arterial stenosis,and to develop and validate a prediction model for END based on independent risk factors. Methods This was a retrospective study that consecutively enrolled patients with cerebral infarction caused by moderate-to-severe symptomatic intracranial arterial stenosis,who were admitted to the Department of Cerebrovascular Disease,Guangdong Provincial Hospital of Chinese Medicine between January 2019 and December 2023.Patients were divided into the END group and the non-END group based on the occurrence of END within 7 days of onset.Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for END.A nomogram regression prediction model was subsequently constructed based on these factors,and its validity was verified using the Bootstrap resampling method within the original dataset. Results A total of 152 patients were included,with 47 in the END group and 105 in the non-END group.The END group consisted of 47 patients aged 65(57-75)years,including 33 males(70.21％);the non-END group consisted of 105 patients aged 64(54-75)years,including 72 males(68.57％).Univariate and multivariate logistic regression analyses identified acute cerebral watershed infarction,severe stenosis of the responsible vessel,and a higher age,blood pressure,clinical features,duration of symptoms,diabetes,dual transient ischemic attack,ipsilateral carotid stenosis,infarction on diffusion-weighted-imaging(ABCD3-I)score as independent risk factors for END.A nomogram regression prediction model was constructed based on these three factors,with an A UC of 0.85(95％CI 0.78-0.92)and an optimal cut-off value of 0.43.The sensitivity and specificity were 0.77 and 0.79,respectively.Internal validation of the model was performed using the Bootstrap resampling method,yielding an AUC of 0.85(95％CI 0.84-0.89). Conclusions The END prediction model constructed in this study incorporates acute cerebral watershed infarction,severe stenosis of the responsible vessel,and the ABCD3-I score,demonstrating good predictive performance.Internal validation indicates good model stability.关键词
症状性颅内动脉狭窄/早期神经功能恶化/预测模型Key words
Symptomatic intracranial arterial stenosis/Early neurological deterioration/Prediction model分类
医药卫生引用本文复制引用
熊紫妮,彭株丽,王欣迪,刘浩林,陈小龙,白小欣..症状性颅内动脉中重度狭窄脑梗死患者早期神经功能恶化预测模型的构建与验证[J].中国卒中杂志,2025,20(12):1499-1507,9.基金项目
广东省基础与应用基础研究基金项目(2021A1515011480) （2021A1515011480）
