Objective <p>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).</p> Methods <p>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).</p> Results <p>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.</p> Conclusions <p>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.</p> Clinical trial number <p>Not applicable.</p>

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

  • Tao Sun,
  • Lixin Huang,
  • Yibo Zhao,
  • Jun Sun,
  • Zhimin Wu,
  • Baoyu Zhang,
  • Cong Ling,
  • Chuan Chen,
  • Hui Wang

摘要

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.