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Abstract
OBJECTIVE: Rates of inferior vena cava (IVC) filter retrieval have remained suboptimal, in part because of poor follow-up. The goal of our study was to determine demographic and clinical factors predictive of IVC filter follow-up care in a university hospital setting. METHODS: We reviewed 250 consecutive patients who received an IVC filter placement with the intention of subsequent retrieval between March 2009 and October 2010. Patient demographics, clinical factors, and physician specialty were evaluated. Multivariate logistic regression analysis was performed to identify variables predicting follow-up care. RESULTS: In our cohort, 60.7% of patients received follow-up care; of those, 93% had IVC filter retrieval. Major indications for IVC filter placement were prophylaxis for high risk surgery (53%) and venous thromboembolic event with contraindication and/or failure of anticoagulation (39%). Follow-up care was less likely for patients discharged to acute rehabilitation or skilled nursing facilities (P < .0001), those with central nervous system pathology (eg, cerebral hemorrhage or spinal fracture; P < .0001), and for those who did not receive an IVC filter placement by a vascular surgeon (P < .0001). In a multivariate analysis, discharge home (odds ratio [OR], 4.0; 95% confidence interval [CI], 1.99-8.2; P < .0001), central nervous system pathology (OR, 0.46; 95% CI, 0.22-0.95; P = .04), and IVC filter placement by the vascular surgery service (OR, 4.7; 95% CI, 2.3-9.6; P < .0001) remained independent predictors of follow-up care. Trauma status and distance of residence did not significantly impact likelihood of patient follow-up. CONCLUSIONS: Service-dependent practice paradigms play a critical role in patient follow-up and IVC filter retrieval rates. Nevertheless, specific patient populations are more prone to having poorer rates of follow-up. Such trends should be factored into institutional quality control goals and patient-centered care.
View details for DOI 10.1016/j.jvs.2012.12.085
View details for Web of Science ID 000322759500029