Neurosurgical review · 2025
Development and validation of a nomogram model for predicting infarction after superficial temporal artery‒middle cerebral artery bypass in patients with intracranial atherosclerotic stenosis.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод в очереди
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Sun Tao, Huang Lixin, Zhao Yibo, Sun Jun, Wu Zhimin, Zhang Baoyu, Ling Cong, Chen Chuan, Wang Hui
Аннотация
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.
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.