Dataset Information

Endovascular management of chronic upper extremity deep vein thrombosis and superior vena cava syndrome.

ABSTRACT: Chronic upper extremity deep vein thrombosis (UEDVT) and superior vena cava syndrome (SVCS) are important and underdiagnosed entities that are associated with significant morbidity, and both are becoming increasingly common due to the use of indwelling catheters and implantable central venous access devices. Currently, as many as 25% of patients with an indwelling catheter are diagnosed with chronic UEDVT or venous stenosis. SVCS is most commonly seen in the setting of malignancy, especially lung cancer and lymphoma. Endovascular management of chronic UEDVT and SVCS is accepted as an important first-line treatment given its high overall success rate and low morbidity as compared with medical and surgical treatments. In this article, the indications for treatment, complications, and success rates of the endovascular management of UEDVT and SVCS are reviewed. Relevant findings on presentation and physical exam as well as various imaging modalities and imaging findings are evaluated. Details of preprocedure evaluation, relevant anatomy, and avoidance of potential complications are discussed.

SUBMITTER: Warren P

PROVIDER: S-EPMC3140250 | biostudies-other | 2011 Mar

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:BackgroundInferior vena cava filter (IVCF) thrombosis is an uncommon complication of IVCF utilization. The aims of this study were to investigate inferior vena cava (IVC) venography before filter retrieval to determine the incidence relative to filter dwell time and risk factors of IVCF thrombosis based on the clinical data and imaging findings in patients with lower extremity deep vein thrombosis (LEDVT).MethodsThe clinical data from a multicenter randomized trial conducted between October 2017 and March 2019 were reviewed to determine the incidence of IVCF thrombosis in preretrieval venography and the associated risk factors. The correlation between filter dwell times (within 90 days) and incidence was assessed. Baseline demographics, LEDVT presentation, laboratory examination, thrombus characteristics, concurrent pulmonary embolism (PE), comorbidities and risk factors for LEDVT, and IVCF-relevant information were analyzed using the independent samples t-test, chi-squared test, Fisher exact test, and regression analysis to determine the univariable and multivariable associations in assessing the risk factors of IVCF thrombosis.ResultsA total of 178 eligible patients were included, of whom 58 were in the IVCF thrombosis group and 120 were in the IVCF nonthrombosis group, and the mean filter dwell time was 22.07±27.91 days (range, 4-190 days). The overall incidence of IVCF thrombosis in patients with LEDVT who received IVCFs was 32.58% (58/178). The incidence of IVCF thrombosis was 35.25% (49/139) in the first 30 days after the IVCF placement and decreased to 22.73% (5/22) between 30 to 60 days of dwell time and to 18.18% (2/11) between 60 and 90 days of dwell time, indicating a decreasing trend within the first 90 days. The risk factors for the occurrence of IVCF thrombosis were concurrent PE [odds ratio (OR) =2.59; 95% confidence interval (CI): 1.27-5.28; P=0.01], rheumatic diseases of the immune system (OR =14.42; 95% CI: 1.52-136.41; P=0.02), IVC:filter radial ratio >0.587 (OR =0.25; 95% CI: 0.10-0.65; P<0.01), and percutaneous angioplasty (PTA) (OR =2.50; 95% CI: 1.09-5.70; P=0.03).ConclusionsThe incidence of IVCF thrombosis at the time of filter retrieval appears to decrease with dwell time within 90 days. Concurrent PE, rheumatic diseases of the immune system, and PTA were taken into account as risk factors. An IVC:filter radial ratio of 0.587 was a protective factor against developing IVCF thrombosis. These findings require further validation in a well-designed study since the present study lacked a close follow-up.

Dataset Information

Endovascular management of chronic upper extremity deep vein thrombosis and superior vena cava syndrome.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets