Improved removal rates for retrievable inferior vena cava filters with the use of a 'filter registry'

Am Surg. 2012 Jan;78(1):94-7. doi: 10.1177/000313481207800143.


The American Association for the Surgery of Trauma challenged the trauma community to improve a 22 per cent average removal rate for retrievable inferior vena cava filters (r-IVCFs). Since 2006, we maintained a "filter registry" documenting all IVCFs placed in trauma patients. Our goal was to improve removal rates for r-IVCF. Patients receiving an IVCF before implementation of filter registry, 2003-2005, comprised the control group. Patients receiving an IVCF after implementation of filter registry, 2006-2009, comprised the study group. Data obtained included age, gender, Injury Severity Score (ISS), length of stay (LOS), mortality, filter inserted, placement indication, removal rates, and reasons why removal did not occur. Fisher exact test and chi square were used for nominal variables. Stepwise logistic regression analysis was used to define predictors of removing and not removing an IVCF. Three hundred seven patients received an IVCF, 142 preregistry and 165 postregistry. No significant difference existed between groups in age, gender, ISS, placement indication, or mortality. A significant difference existed between groups in LOS and presence of deep vein thrombosis (DVT) and pulmonary embolism. A total of 98.2 per cent of postregistry patients received a Günther Tulip filter and all retrievals were performed by Interventional Radiology. Retrieval rates improved, 15.5 to 31.5 per cent post registry (P < 0.001). No differences existed in lost to follow-up (LTF) between groups. Univariate analysis identified age, IVC clot, DVT, and LTF as predictors for not removing a filter. Stepwise logistic regression revealed the filter registry independently predicts the removal of an r-IVCF. A filter registry is effective in improving rates of removal for r-IVCFs.

MeSH terms

  • Case-Control Studies
  • Chi-Square Distribution
  • Device Removal / mortality
  • Device Removal / statistics & numerical data*
  • Female
  • Hospital Mortality
  • Humans
  • Injury Severity Score
  • Length of Stay / statistics & numerical data
  • Logistic Models
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Radiography, Interventional
  • Registries*
  • Risk Factors
  • Vena Cava Filters*