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腹主动脉瘤风险预测模型的开发与验证:一项基于全国人群的队列研究。

Development and validation of a risk prediction model for abdominal aortic aneurysm: a nationwide population-based cohort study.

作者信息

Cho Hyung-Jin, Kim Mi-Hyeong, Ko Kyung-Jai, Jun Kang-Woong, Han Kyung-do, Hwang Jeong-Kye

机构信息

Division of Vascular and Transplant Surgery, Department of Surgery, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 1021, Tongil-ro, Eunpyeong-gu, Seoul, 03312, Korea.

Department of Surgery, Kangdong Sacred Heart Hospital, Seoul, Korea.

出版信息

Sci Rep. 2025 Jul 21;15(1):26417. doi: 10.1038/s41598-025-11956-1.

Abstract

Abdominal aortic aneurysm (AAA) is characterized by irreversible localized dilatation of the abdominal aorta. It poses a significant health risk. As AAA size tends to increase over time, there is a heightened risk of rupture, resulting in a substantially high mortality rate. Although AAA screening programs targeting specific demographics are available, there is room for improvement in terms of inclusivity and cost-effectiveness. This study aimed to develop a predictive model for AAA occurrence utilizing seven years of data from the Korean National Health Insurance Service database (NHIS). This study utilized NHIS data from 2009 to 2020. A total of 4,234,415 individuals who underwent health examinations in 2009 were identified. After applying exclusion criteria, a total of 3,937,535 individuals were selected. Of them, 70% were used for model development and 30% were used for validation. The mean follow-up duration was 10.11 ± 1.29 years, during which 2,836 cases of AAA were identified among 1,181,131 (2.4%) participants in the validation cohort. The model incorporated a set of 10 variables, encompassing age, sex, obesity, smoking, drinking, diabetes (DM), hypertension (HTN), dyslipidemia, chronic kidney disease (CKD), and cardiocerebrovascular disease (CVD). Evaluation of the model's predictive performance revealed an area under the curve (AUC) of 0.807 (95% CI: 0.80-0.81) when it was applied to the development cohort. The AUC remained high at 0.803 (95% CI: 0.79-0.81) when the model was applied to the validation cohort, indicating its effectiveness in forecasting AAA occurrence. A multivariable risk model for predicting the onset of AAA was successfully developed, showcasing an excellent performance with an AUC value of 0.807, surpassing traditional screening methods. This model has the potential to selectively identify high-risk patients from a slightly broader pool than current screening approaches. Priority should be given to proactive screening efforts targeting individuals at elevated risk for AAA, with the goal of reducing AAA-related mortality.

摘要

腹主动脉瘤(AAA)的特征是腹主动脉出现不可逆的局限性扩张。它对健康构成重大风险。由于AAA的大小往往会随着时间的推移而增加,破裂风险随之升高,导致死亡率极高。尽管有针对特定人群的AAA筛查项目,但在包容性和成本效益方面仍有改进空间。本研究旨在利用韩国国民健康保险服务数据库(NHIS)的七年数据开发一个AAA发生的预测模型。本研究使用了2009年至2020年的NHIS数据。共识别出2009年接受健康检查的4234415人。应用排除标准后,共选择了3937535人。其中,70%用于模型开发,30%用于验证。平均随访时间为10.11±1.29年,在此期间,在验证队列的1181131名参与者(2.4%)中识别出2836例AAA病例。该模型纳入了一组10个变量,包括年龄、性别、肥胖、吸烟、饮酒、糖尿病(DM)、高血压(HTN)、血脂异常、慢性肾脏病(CKD)和心脑血管疾病(CVD)。对模型预测性能的评估显示,当应用于开发队列时,曲线下面积(AUC)为0.807(95%CI:0.80 - 0.81)。当模型应用于验证队列时,AUC保持在较高水平,为0.803(95%CI:0.79 - 0.81),表明其在预测AAA发生方面的有效性。成功开发了一个预测AAA发病的多变量风险模型,其AUC值为0.807,表现出色,超过了传统筛查方法。该模型有可能从比当前筛查方法略大的人群中选择性地识别高危患者。应优先针对AAA高危个体进行积极的筛查工作,以降低与AAA相关的死亡率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4322/12279962/1e567b4dc71a/41598_2025_11956_Fig1_HTML.jpg

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