AUTHOR=Koren Ofir , Patel Vivek , Tamir Yuval , Koseki Keita , Kaewkes Danon , Sanders Troy , Naami Robert , Naami Edmund , Cheng Daniel Eugene , Natanzon Sharon Shalom , Shechter Alon , Gornbein Jeffrey , Chakravarty Tarun , Nakamura Mamoo , Cheng Wen , Jilaihawi Hasan , Makkar Raj R. 

TITLE=Predicting the risk of iliofemoral vascular complication in complex transfemoral-TAVR using new generation transcatheter devices

JOURNAL=Frontiers in Cardiovascular Medicine

VOLUME=10

YEAR=2023

URL=https://www.frontiersin.org/journals/cardiovascular-medicine/articles/10.3389/fcvm.2023.1167212

DOI=10.3389/fcvm.2023.1167212

ISSN=2297-055X

ABSTRACT=<sec><title>Objective</title><p>Design a predictive risk model for minimizing iliofemoral vascular complications (IVC) in a contemporary era of transfemoral-transcatheter aortic valve replacement (TF-TAVR).</p></sec><sec><title>Background</title><p>IVC remains a common complication of TF-TAVR despite the technological improvement in the new-generation transcatheter systems (NGTS) and enclosed poor outcomes and quality of life. Currently, there is no accepted tool to assess the IVC risk for calcified and tortuous vessels.</p></sec><sec><title>Methods</title><p>We reconstructed CT images of 516 propensity-matched TF-TAVR patients using the NGTS to design a predictive anatomical model for IVC and validated it on a new cohort of 609 patients. Age, sex, peripheral artery disease, valve size, and type were used to balance the matched cohort.</p></sec><sec><title>Results</title><p>IVC occurred in 214 (7.2%) patients. Sheath size (<italic>p</italic> = 0.02), the sum of angles (SOA) (<italic>p</italic> &lt; .0001), number of curves (NOC) (<italic>p</italic> &lt; .0001), minimal lumen diameter (MLD) (<italic>p</italic> &lt; .001), and sheath-to-femoral artery diameter ratio (SFAR) (<italic>p</italic> = 0.012) were significant predictors for IVC. An indexed risk score (CSI) consisting of multiplying the SOA and NOC divided by the MLD showed 84.3% sensitivity and 96.8% specificity, when set to &gt;100, in predicting IVC (C-stat 0.936, 95% CI 0.911–0.959, <italic>p</italic> &lt; 0.001). Adding SFAR &gt; 1.00 in a tree model increased the overall accuracy to 97.7%. In the validation cohort, the model predicted 89.5% of the IVC cases with an overall 89.5% sensitivity, 98.9% specificity, and 94.2% accuracy (C-stat 0.842, 95% CI 0.904–0.980, <italic>p</italic> &lt; .0001).</p></sec><sec><title>Conclusion</title><p>Our CT-based validated-model is the most accurate and easy-to-use tool assessing IVC risk and should be used for calcified and tortuous vessels in preprocedural planning.</p></sec>