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开发和验证腹腔大动脉动脉瘤风险预测模型:全国性基于人口的队列研究

Hyung-Jin Cho¹, Mi-Hyeong Kim¹, Kyung-Jai Ko²

¹Division 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.

Scientific reports

|July 21, 2025

概括

一个新的预测模型可以使用健康数据识别患腹腔大动脉瘤 (AAA) 高风险的个体. 该工具旨在通过更有效地针对风险人群来提高查包容性和减少AAA相关的死亡率.

科学领域:

心血管医学心血管医学
公共卫生公共卫生
医疗信息学医疗信息学

背景情况:

腹腔大动脉瘤 (AAA) 是一种局部的大动脉扩张,具有高破裂风险和死亡率.
目前的AAA选计划在包容性和成本效益方面存在局限性.
预测建模为改善AAA风险分层提供了一个潜在的途径.

研究的目的:

开发和验证腹腔大动脉动脉瘤 (AAA) 发生的多变量风险预测模型.
用一个大型的国家医疗保险数据库来开发和验证模型.
加强对超出当前查标准的AAA高风险个体的识别.

主要方法:

利用了韩国国家健康保险服务 (NHIS) 七年 (2009-2020) 的数据.
排除后包括3,937,535个个体,其中70%用于开发,30%用于验证.
开发了一个包含10个变量的模型:年龄,性别,肥胖,吸烟,饮酒,糖尿病 (DM),高血压 (HTN),脂质不良,慢性病 (CKD) 和心脑血管疾病 (CVD).

主要成果:

开发的AAA预测模型在开发队列中实现了0.807的曲线下面面积 (AUC),在验证队列中达到0.803.
该模型表现出强大的预测性能,表明其在预测AAA发病时的有效性.
在验证队列中的1,181,131名参与者中确定了2,836例AAA病例,平均随访时间为10.11年.

结论:

成功开发了一种可靠的多变量风险模型来预测AAA发作,其预测性能很好 (AUC为0.807).
这种模型超越了传统的查方法,可以从更广泛的人群中识别高风险个体.
建议通过这种模型识别的高风险个体进行主动查,以减少AAA相关的死亡率.

关键词:

在腹部,腹部.一个大动脉动脉瘤.诺莫格拉姆斯 (Nomograms) 是一个名字.

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