Risk Factors and Clinical Prediction Modeling of Preoperative Asymptomatic Lower Extremity Venous Thrombosis in Patients with Knee Osteoarthritis

Abstract

Background The aim of this study was to develop and validate a prediction model for predicting the risk of preoperative asymptomatic lower extremity venous thrombosis (LEVT) in patients with knee osteoarthritis (KOA). Methods Patients with KOA diagnosed at our hospital between March 2022 and July 2023 were included in this study. Five factors were identified as independent risk factors for the development of preoperative asymptomatic LEVT in patients with KOA by univariate and multivariate logistic regression analysis and a prediction model was constructed by analyzing the results. The performance of the model was evaluated using receiver operating characteristic (ROC) curves. The accuracy of the model and its predictive ability were evaluated using calibration curves. The clinical application value of the prediction model was evaluated using decision curve analysis (DCA). Results A total of 354 patients diagnosed with KOA were included in the study. Multivariate logistic regression analysis revealed HDL 0.55 mg/L ( P = 0.049 ) were the independent risk factors for the occurrence of preoperative asymptomatic LEVT in patients with KOA. The combined-variable ROC curve suggested greater predictability and accuracy (AUC = 0.843, specificity = 90.3%, sensitivity = 71.4%). The calibration curve showed good model agreement and DCA suggested good clinical value of the model. Conclusion Low HDL, high LDL, Na + , Ca 2+ , and D-dimer levels can be used as independent risk factors for the preoperative prediction of asymptomatic LEVT in patients with KOA, and the present study also provides a simple prediction model for clinicians and patients.