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Updated: May 22, 2026

Point-Of-Care Ultrasound Screening for Proximal Lower Extremity Deep Venous Thrombosis
Published on: February 10, 2023
Development and evaluation of a risk prediction model for preoperative lower extremity deep vein thrombosis in
Cuiqing Liu1, Ruihua Huang2, Jie Hong3
1Department of Surgery, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China. cuiqingliu@jnu.edu.cn.
Background:
Lower extremity deep vein thrombosis (LEDVT) is a common and serious complication among patients undergoing orthopedic surgery. However, effective tools for preoperative risk assessment are still lacking. In this retrospective study, we analyzed 525 patients who underwent orthopedic surgery at a tertiary hospital between January 2022 and June 2024.
Methods:
Using least absolute shrinkage and selection operator (LASSO) regression followed by multivariate logistic regression, we screened 66 clinical variables encompassing demographic characteristics, comorbidities, laboratory results, and imaging findings. Six independent predictors were identified: history of constipation, history of deep vein thrombosis, recent major surgery, absolute lymphocyte count, albumin level, and D-dimer level.
Results:
A nomogram was developed based on these predictors to estimate the risk of preoperative LEDVT. The model showed good discriminative ability, with an area under the ROC curve (AUC) of 0.756 in the training cohort and 0.766 in the validation cohort, along with satisfactory calibration. Net reclassification improvement (NRI)and integrated discrimination improvement (IDI) analyses confirmed significant gains in risk reclassification, while decision curve analysis (DCA) indicated a greater net clinical benefit compared with a simplified reference model.
Conclusion:
These findings suggest that the proposed nomogram provides a concise and practical tool for individualized risk prediction, enabling clinicians to identify high-risk patients and optimize perioperative management strategies. Although further validation in large, multicenter prospective studies is warranted, this model has the potential to improve clinical decision-making and patient outcomes by facilitating early recognition and prevention of LEDVT in orthopedic populations.
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