ORIGINAL RESEARCH article

Front. Neurol.

Sec. Endovascular and Interventional Neurology

Development and Validation of a Nomogram for Predicting Early Rupture and Rebleeding Risk After Intracranial Aneurysm Embolization

    PD

    Pu Du 1

    FY

    Fen Yu 2

    GC

    Guohao Chen 1

    WX

    Wenbo Xu 1

  • 1. The Sixth Affiliated Hospital of South China University of Technology, Foshan, China

  • 2. The Second People's Hospital of Foshan, Foshan, China

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Abstract

Objective: To construct and validate a nomogram for predicting early rupture rebleeding risk after intracranial aneurysm embolization, providing a precise clinical assessment tool. Methods: Clinical data from 274 patients (March 2022-February 2025) were retrospectively analyzed, divided into a training set (n=192) and validation set (n=82) (7:3 ratio). Univariate/multivariate logistic regression identified independent risk factors. The nomogram's performance was evaluated via ROC curves, calibration curves, and DCA. Results: Multivariate logistic regression analysis revealed that larger aneurysm diameter, wider neck, higher preoperative Hunt-Hess grade, incomplete embolization, and poor postoperative blood pressure control were independent risk factors for early rupture rebleeding after embolization (all P<0.05). The constructed nomogram demonstrated good calibration and discriminative ability in both the training and validation sets, with C-index values of 0.873 and 0.738, respectively. The areas under the ROC curves (AUC) were 0.870 (95%CI: 0.790-0.951) and 0.739 (95%CI: 0.456-1.000) with corresponding sensitivities and specificities of 0.812, 0.840 and 0.667, 0.902, respectively. Decision curve analysis indicated significant clinical utility within specific threshold probability ranges. Conclusion: The multifactor nomogram exhibits strong predictive performance, facilitating early identification of high-risk patients and personalized treatment.

Summary

Keywords

Early rebleeding, endovascular embolization, Intracranial Aneurysm, Nomogram model, Risk factors, Subarachnoid Hemorrhage

Received

18 October 2025

Accepted

16 February 2026

Copyright

© 2026 Du, Yu, Chen and Xu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Pu Du

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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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