ArticleFrontiers in neurology
Determination of patient prognosis based on unruptured basilar artery aneurysm morphology using a novel dynamic prediction model.
Article in Frontiers in neurology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Artificial Intelligence for Cerebral Aneurysm Management: Integrating Imaging, Hemodynamics, and Clinical Decision Support.Journal of imaging informatics in medicine · 2026Review
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Authors and funding
7 authors.
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Abstract
Introduction: The study aimed to develop a novel predictive system to assess the clinical survival of patients with basilar artery aneurysms (BAAs) following endovascular embolization by analyzing aneurysm and peripheral vessel morphologies. Methods: Fifty-eight BAA patients who underwent endovascular embolization were retrospectively studied, with a median follow-up of 17.5 months. A total of nine deaths (15.5%) occurred during the follow-up period. Due to the limited number of outcome events, we adopted a conservative modeling strategy that involved using the least absolute shrinkage and selection operator (LASSO)-penalized Cox regression for variable selection, followed by multivariable Cox regression to construct the prognostic model. An online dynamic nomogram was developed to predict survival. Model discrimination was evaluated using the concordance index (C-index) and time-dependent receiver operating characteristic (ROC) curves. Internal validation was performed using bootstrap resampling with calibration curves, and clinical utility was assessed using decision curve analysis (DCA). Results: LASSO-penalized Cox regression identified two independent prognostic factors-basilar artery (BA) diameter and aneurysm neck-which were subsequently confirmed by multivariable Cox regression (BA: HR = 2.12, 95% CI: 1.01-4.45, Conclusion: This morphology-based, online, dynamic nomogram serves as a practical tool for predicting survival in BAA patients after endovascular embolization. However, given the limited sample size and the number of events, the findings should be considered exploratory, and external validation in larger cohorts is warranted.
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