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Abstract <p>This study aimed to create a personalized risk assessment model for asymptomatic intracerebral hemorrhage (aICH) following endovascular thrombectomy (ET) to aid clinical decision-making.&#xa0;Between 2019 and 2023, 469 inpatients with acute ischemic stroke (AIS) who received ET treatment within 24&#xa0;h of onset were recruited from three centers. Patients were randomly assigned to either a training or validation cohort. Univariate and multivariate logistic regression analyses were conducted to identify independent factors for aICH. A nomogram-based model was developed for personalized risk assessment for aICH following ET. The model’s usability was evaluated using the receiver operating characteristic (ROC) curve, and a calibration curve was plotted to compare predicted probabilities with actual occurrences. The feasibility of the model for practical clinical application was assessed using decision curve analysis.&#xa0;Four independent risk factors for aICH in patients with AIS following ET were identified: preoperative Alberta Stroke Program Early Computed Tomography score [odds ratio (OR) = 0.686, 95% confidence interval (CI): 0.581–0.811], time from onset to surgery completion (OR = 1.186, 95% CI: 1.097–1.282), intraoperative arterial thrombolysis (OR = 2.405, 95% CI: 1.289–4.487), and Careggi collateral score (OR = 0.560, 95% CI: 0.422–0.743). ROC analysis indicated that the model demonstrated excellent accuracy and discrimination with area under the curve values of 0.812 (95% CI: 0.763–0.861) and 0.896 (95% CI, 0.843–0.949) for the training and validation cohorts, respectively.&#xa0;This nomogram-based model is a reliable personalized tool for evaluating the risk of aICH in patients with AIS after ET.</p>

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A nomogram-based model for predicting asymptomatic intracerebral hemorrhage in acute ischemic stroke patients following endovascular thrombectomy

  • 期刊论文

  • 发表日期：

    2025年5月24日

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  • Bang Luo,
  • Qing Ye,
  • Liang Chen,
  • Shengjiao Liang,
  • Kai Liu,
  • Binling He,
  • Gang Chen,
  • Chunlan Huang,
  • Lei Zhang,
  • Lin Chen,
  • Zongze Li,
  • Mei Yuan

摘要

Abstract

This study aimed to create a personalized risk assessment model for asymptomatic intracerebral hemorrhage (aICH) following endovascular thrombectomy (ET) to aid clinical decision-making. Between 2019 and 2023, 469 inpatients with acute ischemic stroke (AIS) who received ET treatment within 24 h of onset were recruited from three centers. Patients were randomly assigned to either a training or validation cohort. Univariate and multivariate logistic regression analyses were conducted to identify independent factors for aICH. A nomogram-based model was developed for personalized risk assessment for aICH following ET. The model’s usability was evaluated using the receiver operating characteristic (ROC) curve, and a calibration curve was plotted to compare predicted probabilities with actual occurrences. The feasibility of the model for practical clinical application was assessed using decision curve analysis. Four independent risk factors for aICH in patients with AIS following ET were identified: preoperative Alberta Stroke Program Early Computed Tomography score [odds ratio (OR) = 0.686, 95% confidence interval (CI): 0.581–0.811], time from onset to surgery completion (OR = 1.186, 95% CI: 1.097–1.282), intraoperative arterial thrombolysis (OR = 2.405, 95% CI: 1.289–4.487), and Careggi collateral score (OR = 0.560, 95% CI: 0.422–0.743). ROC analysis indicated that the model demonstrated excellent accuracy and discrimination with area under the curve values of 0.812 (95% CI: 0.763–0.861) and 0.896 (95% CI, 0.843–0.949) for the training and validation cohorts, respectively. This nomogram-based model is a reliable personalized tool for evaluating the risk of aICH in patients with AIS after ET.