Objective To establish a nomogram model which is used for predicting lower extremity deep venous thrombosis(DVT)after interventional treatment of lower extremity arteriosclerosis obliterans(LEASO),and to make an external validation of the model.Methods A total of 434 LEASO patients receiving intraluminal therapy between January 2020 and December 2022,who were retrieved from the database of patients with limb ischemia(JCLIMB)established by the Japanese Society of Vascular Surgery,were collected and used as modeling group,and other 60 LEASO patients,who received interventional treatment at the Hefei Binhu Hospital of China between January 2020 and May 2023,were collected and used as validation group.Through the electronic medical record system,the clinical data of the patients were obtained,which included gender,age,coexisting diabetes mellitus,coexisting hypertension,coexisting coronary heart disease,body mass index(BMI),Fontaine stage,D-dimer,prothrombin time(PT),activated partial thromboplastin(APTT),platelet lymphocyte ratio(PLR),and neutrophil-to-lymphocyte ratio(NLR).The nomogram model was established by using R software,and the prediction model was evaluated by the calibration curve,the decision curve analysis(DCA)and the receiver operating characteristic(ROC)curve.Results The differences in BMI,Fontaine stage,D-dimer,PLR and NLR between DVT patients and non-DVT patients were statistically significant(P＜0.05).Multivariate logistic regression analysis showed that BMI,Fontaine stage,D-dimer,PLR and NLR were the independent influencing factors for DVT in LEASO patients(P＜0.05).The nomogram model was established based on the results of the logistic regression analysis.The calibration curve analysis showed that the predicted values of the model was basically consistent with the actual values,indicating that this nomogram model carried a good accuracy.Taking the net income as the ordinate and the threshold as the abscissa,the none line represented that DVT would not occur in all LEASO patients.The nomogram model represented the actual curve of DVT,and the threshold range was 0.09-1.00,indicating that using this model for decision-making had good clinical benefits,suggesting the clinical utility of this model.ROC analysis revealed that using this nomogram model,which was established in this study,to predict the area under the DVT curve(AUC)of LEASO patients,the AUC in the modeling group and in the validation group was 0.912 and 0.834 respectively,the sensitivity was 96.50 and 99.20 respectively,and the specificity was 76.60 and 66.70 respectively.Conclusion The prediction model of DVT in LEASO patients that is established on the BMI,Fontaine stage,D-dimer,PLR and NLR has a good predictive value for the occurrence of DVT,therefore,this model is worth popularizing in clinical practice.