Deep vein thrombosis (DVT) is a common complication after trauma and mostly without specific symptoms. Timely diagnosis and early appropriate treatment measures can prevent further development of thrombosis for patients with traumatic lower extremity fractures. Although extracellular vesicles (EVs) are confirmed as promising disease biomarkers, little is known about the role of altered levels and composition in the diagnosis of post-traumatic DVT.The levels of circulating EVs subgroups were measured using flow cytometry. Isolated EVs were characterized and subjected to proteomics analysis to screen for differentially expressed proteins (DEPs) between DVT and non-DVT patients. Regularized logistic regression analysis based on L2 penalty terms using R's caret package was applied to build a model for DVT diagnosis.Compared to non-DVT patients, DVT patients had higher circulating hepatocyte-derived EVs (hEVs) with good predictive value for post-traumatic DVT diagnosis. The results of the proteomic analysis showed that differentially expressed proteins (DEPs) of circulating EVs between the DVT group and non-DVT group were enriched in the complement and coagulation cascade. Finally, an integrated model of five biomarkers including SERPING1, C8G, CFH, FIX, and hEVs level was established for post-traumatic DVT diagnosis with robust identification of the traumatic patients with and without DVT (AUC 0.972).Post-traumatic DVT patients had changed levels and composition of circulating EVs compared to non-DVT patients and healthy controls. Circulating EVs may acquire pathological protein signatures and become potential biomarkers for identifying subjects' post-traumatic DVT.Copyright © 2024. Published by Elsevier B.V.