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

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.