Prof. Dr. med. Georg Nickenig
Medical Clinic II for Cardiology, Angiology and Pneumology
georg.nickenig@ukbonn.de View member: Prof. Dr. med. Georg Nickenig
Vascular pharmacology
OBJECTIVES: Several models have been evaluated for the prediction of transcatheter aortic valve replacement (TAVR)-related cerebrovascular accidents (CVA). The HOSTILE registry recently investigated TAVR outcomes in patients with severe peripheral artery disease (PAD), assessed using a multi-parameter score (HOSTILE score). Among patients treated with transfemoral access (TFA), higher HOSTILE score was associated with higher rates of CVA. We sought to assess the efficacy of different modalities of risk estimation for TAVR-related CVA prediction in a population with severe PAD.
METHODS: The predictive ability of the risk assessment modalities was compared using the area under the receiving-operator characteristic (ROC) curve and Harrell's C-statistic. The pre-defined outcome was any CVA occurring within 30 days after TAVR.
RESULTS: The study population consisted of 1707 patients, 518 (30.3%) treated via TFA and 1189 treated via transthoracic and trans-axillary routes. The CHADS-VASc and the HOSTILE score showed fair performance only in the TFA cohort (AUC 0.68, 95% CI 0.53-0.83, and 0.68, 95% CI 0.55-0.81, respectively); values of CHADS-VASc >5 and HOSTILE >6 exhibited the best discriminatory ability. The highest risk group (CHADS-VASc >5 and HOSTILE >6) showed a five-fold higher incidence of CVA as compared to the other groups (incidence 6.7%; HR: 5.38, CI95%: 1.80-16.01; p = 0.003).
CONCLUSIONS: In a population of patients with severe PAD treated with TAVR via TFA, the integration of a clinical score (CHADS-VASc score) with a purely anatomical one (HOSTILE score) increased the discriminative ability towards 30-day CVA. Further analyses are needed in order to prospectively evaluate this strategy in different cohorts.
Copyright © 2026. Published by Elsevier Inc.
PMID: 42372999
Medical Clinic II for Cardiology, Angiology and Pneumology
georg.nickenig@ukbonn.de View member: Prof. Dr. med. Georg Nickenig