Authors
Tao Sun, Lixin Huang, Yibo Zhao, Jun Sun, Zhimin Wu, Baoyu Zhang, Cong Ling, Chuan Chen, Hui Wang
Published in
Neurosurgical review. Volume 48. Issue 1. Pages 682. Oct 07, 2025. Epub Oct 07, 2025.
Abstract
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).
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).
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.
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.
Not applicable.
PMID:
41055752
Bibliographic data and abstract were imported from PubMed on 07 Oct 2025.
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