A CT-based predictive model incorporating the Cedars-Sinai Index score and sheath-to-femoral artery ratio accurately predicted iliofemoral vascular complications with a C-statistic of 0.942.
Cohort (n=2,989)
No
Can a CT-based anatomical risk model accurately predict iliofemoral vascular complications in patients undergoing transfemoral TAVR?
A novel CT-based anatomical risk score accurately predicts iliofemoral vascular complications in patients undergoing transfemoral TAVR, providing a useful tool for preprocedural planning.
Effect estimate: C-statistic 0.942 (95% CI 0.904-0.980)
p-value: p=<0.0001
Objective Design a predictive risk model for minimizing iliofemoral vascular complications (IVC) in a contemporary era of transfemoral-transcatheter aortic valve replacement (TF-TAVR). Background 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. Methods 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. Results 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). Conclusion 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.
Koren et al. (Thu,) conducted a cohort in Severe symptomatic aortic stenosis (n=2,989). CT-based predictive anatomical model (Cedars-Sinai Index score and SFAR) vs. Standard visual assessment was evaluated on Prediction of iliofemoral vascular complications (IVC) in the validation cohort (C-statistic 0.942, 95% CI 0.904-0.980, p=<0.0001). A CT-based predictive model incorporating the Cedars-Sinai Index score and sheath-to-femoral artery ratio accurately predicted iliofemoral vascular complications with a C-statistic of 0.942.
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