Exploring Risk Factors for Lower Extremity Deep Vein Thrombosis Patients with Co-existing Pulmonary Embolism Based on Multiple Logistic Regression Model

Author:

Zu Jiahong1ORCID,Yang Tao2ORCID

Affiliation:

1. School of Public Health, Shanxi Medical University, Taiyuan, China

2. General Surgery Department, Third Hospital of Shanxi Medical University, Taiyuan, China

Abstract

Valuable data on deep vein thrombosis (DVT) patients with coexisting pulmonary embolism (PE) is scarce. This study aimed to identify risk factors associated with these patients and develop logistic regression models to select high-risk DVT patients with coexisting PE. We retrospectively collected data on 150 DVT patients between July 15, 2022, and June 15, 2023, dividing them into groups based on the presence of coexisting PE. Univariate and multivariate logistic regression analyses were performed to identify significant risk factors and construct predictive models. Discrimination and calibration statistics evaluated the validation and accuracy of the developed models. Of the 130 patients analyzed, 40 (30.77%) had coexisting PE. Univariate analysis revealed four significant predictors of DVT patients with coexisting PE: sex (OR 3.83, 95% CI: [1.76; 8.59], P = 0.001), body mass index (BMI) (OR 1.50, 95% CI: [1.28; 1.75], P < 0.001), chronic disease (OR 5.15, 95% CI: [2.32; 11.8], P < 0.001), and high-density lipoprotein (HDL) (OR 0.03, 95% CI: [0.01; 0.20], P < 0.001). Additionally, BMI > 24 kg/m2 (OR 9.70, 95% CI: [2.70; 67.5], P < 0.001) and BMI > 28 kg/m2 (OR 4.80, 95% CI: [2.15; 11.0], P < 0.001) were associated with concurrent PE. Three multiple regression models were constructed, with areas under the receiver-operating characteristic curves of 0.925 (95% CI: [0.882; 0.968]), 0.908 (95% CI: [0.859; 0.957]), and 0.890 (95% CI: [0.836; 0.944]), respectively. Sex, BMI, chronic disease, and HDL levels are significant predictors of DVT patients with coexisting PE.

Publisher

SAGE Publications

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3