ObjectiveTo evaluate the efficacy and safety of intracavitary treatment for iliac vein compression syndrome（IVCS）with acute lower extremity deep venous thrombosis (DVT).MethodsThe clinical data of 57 patients with IVCS and lower extremity DVT, who undergoing with stent implantation, balloon expansion and Angiojet rheolytic thrombectomy from June 2015 to June 2018, were retrospectively analyzed. The effect of treatment was evaluated by the changes of thigh circumference difference between the affected side and the healthy side, and the thrombosis clearance rate in the operating. In addition, the incidence of post-thrombotic syndrome (PTS) and stent patency rate were analyzed after long-term follow-up based on the change of Villaita scale score and ultrasound examination of lower extremity veins.ResultsThe success rate of surgical technique was 100%, and there was no pulmonary embolism during operating and postoperative. Lower extremity deep vein thrombosis clearance levels Ⅲ 48 cases (84.2%), Ⅱ 9 cases (15.8%), the changes of thigh circumference difference between the affected side and the healthy side from preoperative (5.8±1.7) cm to (3.7±1.0) cm. One year follow-up after operation, the primary patency rate of stent was 86.0% and PTS occurred in 8 patients (14.0%).ConclusionStent implantation, balloon expansion and Angiojet rheolytic thrombectomy for IVCS with acute lower extremity DVT is a safe, effective with low incidence of complications and efficient thrombus clearance.
ObjectiveTo systematically evaluated the efficacy of AngioJet mechanical thrombectomy and catheter-directed thrombolysis (CDT) in the treatment of acute lower extremity deep venous thrombosis (LEDVT).MethodsAccording to the retrieval strategy of Cochrane collaboration network, the relevant literatures in CNKI, WangFang, VIP, CBM, PubMed, Embase, Cochrane Library, Web of Science at home and abroad up to March 25, 2020 were collected, and the meta analysis was performed by using Review Manager 5.3 software.ResultsA total of 20 observational studies were included in the meta analysis. The total number of patients was 1 566, which 799 cases in the AngioJet group and 767 cases in the CDT group. The results showed that the AngioJet group had a higher patency rate of deep vein ［MD=11.34, 95%CI (6.16, 16.51), P<0.000 1］, lower or shorter Villalta score ［MD=–1.90, 95%CI (–2.71, –1.10), P<0.000 01］, incidence of post-thrombotic syndrome［PTS, OR=0.42, 95%CI (0.23, 0.77), P=0.005］, rate of clot reduction grade Ⅰ events ［OR=0.40, 95%CI (0.24, 0.67), P=0.000 5］, incidence of bleeding complication ［OR=0.32, 95%CI (0.21, 0.49), P<0.000 01］, and hospital stay ［MD=–2.96, 95%CI (–3.69, –2.22), P<0.000 01］.ConclusionsIn the early efficacy, AngioJet mechanical thrombectomy has better patency rate of deep vein and thrombolysis, shorter hospital stay, and lower risk of bleeding than CDT. In the mid-term effect, AngioJet mechanical thrombectomy could reduce the incidence and the severity of PTS.
Objective The purpose of this study was 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 between December 2017 and 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 Xuzhou Tumor 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 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.