Development and validation of a nomogram model for predicting infarction after superficial temporal artery‒middle cerebral artery bypass in patients with intracranial atherosclerotic stenosis.

IF 2.5 3区 医学 Q2 CLINICAL NEUROLOGY
Tao Sun, Lixin Huang, Yibo Zhao, Jun Sun, Zhimin Wu, Baoyu Zhang, Cong Ling, Chuan Chen, Hui Wang
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引用次数: 0

Abstract

Objective: This study aimed to develop and validate a nomogram model for predicting cerebral infarction risk after superficial temporal artery-middle cerebral artery (STA-MCA) bypass in patients with intracranial atherosclerotic stenosis (ICAS).

Methods: Patients with ICAS who received STA-MCA bypass were enrolled in this study. The independent risk factors for post bypass infarction were identified using univariate and multivariate logistic regression analyses. A nomogram model was developed and subsequently evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

Results: Eventually, 316 patients with ICAS were included in the study. Diabetes, smoking, and high triglyceride and total cholesterol levels were identified as the independent risk factors, and a nomogram model was developed. The model achieved areas under the curve (AUCs) of 0.88 (95% confidence interval [CI] = 0.79-0.97) in the training cohort and 0.84 (95% CI = 0.72-0.97) in the validation cohort. Moreover, the calibration curves matched well, and the DCA indicated favorable clinical utility of the model.

Conclusions: We develop a nomogram model for infarction after STA-MCA bypass in patients with ICAS, which could assess the risk of infarction quickly. The model could significantly guide clinical decisions and reduce the incidence of infarction.

Clinical trial number: Not applicable.

颅内动脉粥样硬化性狭窄患者颞浅动脉-大脑中动脉搭桥术后脑梗死的nomogram预测模型的建立与验证。
目的:本研究旨在建立并验证一种预测颅内动脉粥样硬化性狭窄(ICAS)患者颞浅动脉-大脑中动脉(STA-MCA)搭桥术后脑梗死风险的nomogram模型。方法:ICAS患者行STA-MCA搭桥术。通过单因素和多因素logistic回归分析确定搭桥后梗死的独立危险因素。建立了nomogram模型,并随后使用受试者工作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)进行评估。结果:最终,316例ICAS患者被纳入研究。将糖尿病、吸烟、高甘油三酯和总胆固醇水平确定为独立危险因素,并建立了nomogram模型。该模型在训练队列中的曲线下面积(auc)为0.88(95%置信区间[CI] = 0.79-0.97),在验证队列中的auc为0.84 (95% CI = 0.72-0.97)。此外,校正曲线吻合良好,DCA表明该模型具有良好的临床应用价值。结论:我们建立了ICAS患者STA-MCA搭桥后梗死的nomogram模型,可以快速评估梗死的风险。该模型可显著指导临床决策,降低梗死发生率。临床试验号:不适用。
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来源期刊
Neurosurgical Review
Neurosurgical Review 医学-临床神经学
CiteScore
5.60
自引率
7.10%
发文量
191
审稿时长
6-12 weeks
期刊介绍: The goal of Neurosurgical Review is to provide a forum for comprehensive reviews on current issues in neurosurgery. Each issue contains up to three reviews, reflecting all important aspects of one topic (a disease or a surgical approach). Comments by a panel of experts within the same issue complete the topic. By providing comprehensive coverage of one topic per issue, Neurosurgical Review combines the topicality of professional journals with the indepth treatment of a monograph. Original papers of high quality are also welcome.
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