Objective To establish and validate a risk prediction model for post-thrombotic syndrome (PTS) in patients after interventional treatment for acute lower extremity deep vein thrombosis (LEDVT). MethodsA retrospective study was conducted to collect data from 234 patients with acute LEDVT who underwent interventional treatment at Xuzhou Central Hospital from December 2017 to June 2022, serving as the modeling set. Factors influencing the occurrence of PTS were analyzed, and a nomogram was developed. An additional 98 patients from the same period treated at the Xuzhou Cancer Hospital were included as an external validation set to assess the reliability of the model. ResultsAmong the patients used to establish the model, the incidence of PTS was 25.2% (59/234), while in the validation set was 31.6% (31/98). Multivariate logistic regression analysis of the modeling set identified the following factors as influencing PTS: age (OR=1.076, P=0.001), BMI (OR=1.163, P=0.004), iliac vein stent placement (OR=0.165, P<0.001), history of varicose veins (OR=5.809, P<0.001), and preoperative D-dimer level (OR=1.341, P<0.001). These 5 factors were used to construct the risk prediction model. The area under the receiver operating characteristic (ROC) curve (AUC) of the model was 0.869 [95%CI (0.819, 0.919)], with the highest Youden index of 0.568, corresponding to a sensitivity of 79.7% and specificity of 77.1%. When applied to the validation set, the AUC was 0.821 [95%CI (0.734, 0.909)], with sensitivity of 77.4%, specificity of 76.1%, and accuracy of 76.6%. ConclusionsThe risk prediction model for PTS established in this study demonstrates good predictive performance. The included parameters are simple and practical, providing a useful reference for clinicians in the preliminary screening of high-risk PTS patients.