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Background

Predicting Vascular Complications During Transfemoral Transcatheter Aortic Valve Replacement Using Computed Tomography.

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Background

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  1. Predicting Vascular Complications During Transfemoral Transcatheter Aortic Valve Replacement Using Computed Tomography Akhil Parashar MD; Shikhar Agarwal MD MPH; Dhruv Modi MD; Kanhaiya Poddar MD; Lars Svensson MD PhD; Eric Roselli MD; Paul Schoenhagen MD; E Murat Tuzcu MD; Samir R Kapadia MD; Amar Krishnaswamy MD Heart and Vascular Institute, Cleveland Clinic

  2. Background • Thorough pre-procedural evaluation of patients is key to the success of Transcatheter Aortic Valve Replacement (TAVR). • Studies evaluating ilio-femoral access and predictors of complication have relied primarily on 2D angiography • There is limited data demonstrating CT-derived parameters for the screening of patients for TF-TAVR.

  3. Aim and Methods • Aim: Establish computed tomography (CT) imaging predictors of vascular complication in patients undergoing transfemoral TAVR (TF-TAVR). • All patients who underwent an attempted TF-TAVR using the Edwards SAPIEN balloon-expandable TAVR prosthesis at the Cleveland Clinic were included. • All iliofemoral CT angiograms were reviewed for this study. • Threshold values to predict vascular complications were determined using receiver operating characteristic curve (ROC) analysis. • A stepwise logistic regression analysis was performed to assess the predictive efficacy of various factors.

  4. Figure 1 : CT-analysis of the iliofemoral system for TAVR. (A) Virtual reconstruction demonstrating tortuosity (arrow); (B) Center-line reconstruction of the iliofemoral system to ensure measurements of vessel diameter and area (C & D) perpendicular to the axis of the vessel.

  5. Results Table 1: Baseline Characteristics

  6. Figure 2: Proportion of patients (red) with vascular complications out of total patients stratified by year.

  7. Table 2: Comparison of mean Sheath: femoral artery diameter ratio (SFAR) and mean sheath to femoral artery area ratio (SFAAR) between two groups. Table 3: Comparison of patient populations stratified by mean sheath to femoral artery area ratio (SFAAR)

  8. ROC Analysis Figure 4. Receiver-operating curve analysis demonstrating the SFAR and SFAAR cut-points of 1.45 and 1.35 to predict vascular complications.

  9. Step-wise logistic regression Panel A Panel B Figure 5: Step-wise logistic regression models predicting the occurrence of vascular complication in our patient population. Note that two separate models were constructed for SFAR (Panel A) and SFAAR (Panel B) due to mutual collinearity.

  10. Conclusions • Vessel-area analysis of CT images is an important predictor of vascular complications. • Utilization of CTA-based area indices (SFAAR) may provide a more accurate screen for patients undergoing TF-TAVR • Future studies should evaluate a prospective application of this method to assess its efficacy in reducing vascular complications.

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