目的:新生颅内动脉瘤(IA)是第二个,在与最初检测到IA的位置相距较远的IA患者中发展的新IA。本研究旨在识别从头IA形成的风险因素,并建立和外部验证从头IA的多中心风险预测模型。
方法:对现有的从头IA队列进行系统评价和荟萃分析,以形成衍生队列。计算各危险因素的风险比和95%CI。此外,模型中包含的风险评分是根据具有统计学意义的危险因素及其权重计算的.然后在中国患者的多中心外部队列中验证了该模型,接收器工作特性和校准曲线,决策曲线分析,和Kaplan-Meier曲线用于评估模型。
结果:对9351名患者进行了19项研究,其中304例(3.25%)患者从头IAs,包括在推导队列中。在3.3-18.8年的总随访期间,这些患者在2.5-18.5年发生了从头IAs。有统计学意义的危险因素是年龄<60岁,女性性别,吸烟史,IAs的家族史,初始诊断时的多个IAs,和大脑中动脉的初始IAs,风险评分分别为4、5、2、6、3和3。然后,由776名患者组成的多中心外部队列,其中45例(5.80%)患者从头IAs,包括在验证队列中。在平均随访6.19年期间,这些患者的从头IAs平均形成时间为5.25年。模型曲线下面积为0.804,灵敏度为0.667,特异性为0.900,截止值为13。校正曲线,决策曲线分析,Kaplan-Meier曲线也表明了模型的良好性能。
结论:该预测模型是一种方便,直观的工具,用于识别从头IAs的高风险患者。该模型的合理使用不仅有助于临床决策,而且在一定程度上对动脉瘤性蛛网膜下腔出血的预防起到积极作用。
OBJECTIVE: A de novo intracranial aneurysm (IA) is a second, new IA that develops in patients with IAs distant from where the initial IA was detected. This study aimed to identify risk factors for de novo IA formation and establish and externally validate a multicenter risk prediction model for de novo IAs.
METHODS: A systematic
review and meta-analysis of existing de novo IA cohorts was conducted to form the derivation cohort. The risk ratios and 95% CIs of each risk factor were calculated. In addition, risk scores included in the model were calculated based on the statistically significant risk factors with their weightings. Then the model was validated in a multicenter external cohort of Chinese patients, and receiver operating characteristic and
calibration curves, decision curve analysis, and Kaplan-Meier curves were used to evaluate the model.
RESULTS: Nineteen studies with 9351 patients, of whom 304 patients (3.25%) developed de novo IAs, were included in the derivation cohort. These patients developed de novo IAs at 2.5-18.5 years during a total follow-up of 3.3-18.8 years. The statistically significant risk factors were age < 60 years, female sex, smoking history, family history of IAs, multiple IAs at initial diagnosis, and initial IAs in the middle cerebral artery, with risk scores of 4, 5, 2, 6, 3, and 3, respectively. Then, a multicenter external cohort comprising 776 patients, of whom 45 patients (5.80%) developed de novo IAs, was included in the validation cohort. De novo IAs formed in these patients at a mean of 5.25 years during a mean follow-up of 6.19 years. The area under the curve of the model was 0.804, with a sensitivity of 0.667 and specificity of 0.900, at a cutoff value of 13. The
calibration curve, decision curve analysis, and Kaplan-Meier curves also indicated good performance of the model.
CONCLUSIONS: This prediction model is a convenient and intuitive tool for identifying high-risk patients with de novo IAs. Reasonable use of the model can not only aid in clinical decision-making but also play a positive role in the prevention of aneurysmal subarachnoid hemorrhage to a certain extent.