Bijlenga Philippe, Spinner Georg Ralph, Scutari Marco, Delucchi Matteo, Hirsch Sven
Department of Neurosurgery, Department of Clinical Neurosciences, Geneva University Hospital, Faculty of Medicine, Geneva University, Geneva, Switzerland.
Centre of Computational Health, Institute of Computational Life Sciences, Zurich University of Applied Sciences (ZHAW), Wädenswil, Zurich, Switzerland.
Acta Neurochir Suppl. 2025;136:19-26. doi: 10.1007/978-3-031-89844-0_3.
Intracranial aneurysms (IAs) are critical vascular defects potentially leading to subarachnoid hemorrhage. A Bayesian framework assists clinicians in assessing IA risks by evaluating multiple factors, including sex, due to its higher prevalence in women.
This study adopted the Bayesian theorem to quantify IA prevalence and the incidence of subsequent hemorrhage, examining sex as a pivotal risk factor for IA rupture stratification.
The Bayesian analysis revealed a greater incidence of IAs among women yet indicated that sex does not have a significant impact on the rupture risk in diagnosed patients. This finding suggests the necessity of considering other cofactors in risk evaluation.
Bayesian approaches provide clinicians with refined tools for IA risk assessment, emphasizing the complex interplay of various risk factors beyond sex. Acknowledging the limited influence of sex on rupture probability is crucial in guiding IA management. Continuous research is warranted to advance Bayesian methods, improving their clinical applicability and enhancing patient treatment outcomes.
颅内动脉瘤（IAs）是严重的血管缺陷，可能导致蛛网膜下腔出血。贝叶斯框架通过评估包括性别在内的多个因素，帮助临床医生评估颅内动脉瘤风险，因为女性中颅内动脉瘤的患病率更高。
本研究采用贝叶斯定理来量化颅内动脉瘤的患病率和随后出血的发生率，将性别作为颅内动脉瘤破裂分层的关键风险因素进行研究。
贝叶斯分析显示女性颅内动脉瘤的发病率更高，但表明性别对已确诊患者的破裂风险没有显著影响。这一发现表明在风险评估中考虑其他辅助因素的必要性。
贝叶斯方法为临床医生提供了用于颅内动脉瘤风险评估的精细工具，强调了除性别之外各种风险因素之间的复杂相互作用。认识到性别对破裂概率的影响有限对于指导颅内动脉瘤的管理至关重要。有必要持续开展研究以推进贝叶斯方法，提高其临床适用性并改善患者治疗效果。
