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Design a predictive risk model for minimizing iliofemoral vascular complications (IVC) in a contemporary era of transfemoral-transcatheter aortic valve replacement (TF-TAVR).

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.

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.

IVC occurred in 214 (7.2%) patients. Sheath size (p = 0.02), the sum of angles (SOA) (p < .0001), number of curves (NOC) (p < .0001), minimal lumen diameter (MLD) (p < .001), and sheath-to-femoral artery diameter ratio (SFAR) (p = 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 >100, in predicting IVC (C-stat 0.936, 95% CI 0.911–0.959, p < 0.001). Adding SFAR > 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, p < .0001).

Our CT-based validated-model is the most accurate and easy-to-use tool assessing …