Clinical Predictors of New Significant Conduction System Abnormalities in Patients After Transcatheter Aortic Valve Implantation

Yafim Brodov Cardiology and diagnistic imaging, Leviev Heart Center, Tel Hashomer, Ramat Gan, None, Israel Eli Konen Cardiology and diagnistic imaging, Leviev Heart Center, Tel Hashomer, Ramat Gan, None, Israel Mattia Di Segni Cardiology and diagnistic imaging, Leviev Heart Center, Tel Hashomer, Ramat Gan, None, Israel David Samooha Cardiology and diagnistic imaging, Leviev Heart Center, Tel Hashomer, Ramat Gan, None, Israel Israel Barbash Cardiology and diagnistic imaging, Leviev Heart Center, Tel Hashomer, Ramat Gan, None, Israel Ehud Raanani Cardiology and diagnistic imaging, Leviev Heart Center, Tel Hashomer, Ramat Gan, None, Israel Victor Guetta Cardiology and diagnistic imaging, Leviev Heart Center, Tel Hashomer, Ramat Gan, None, Israel Amit Segev Cardiology and diagnistic imaging, Leviev Heart Center, Tel Hashomer, Ramat Gan, None, Israel Paul Fefer Cardiology and diagnistic imaging, Leviev Heart Center, Tel Hashomer, Ramat Gan, None, Israel Orly Goitein Cardiology and diagnistic imaging, Leviev Heart Center, Tel Hashomer, Ramat Gan, None, Israel

Background. The risk of conduction system abnormalities (CSA) following transcatheter aortic valve implantation (TAVI) remains high.

Objectives. We aimed to evaluate the impact of different clinical and imaging parameters on the development of CSA after TAVI.

Methods. Consecutive patients (n = 168), with severe aortic valve stenosis, without prior CSA, underwent CT - TAVI followed by CoreValve® (n = 72) and SAPIEN® (n = 96) implantation. MAC, AoV and LVOT Ca++ scores were quantitated from non-contrast ECG-gated chest CT using Agatston method. The primary end points were CLBBB or high degree AV block. Backward stepwise logistic regression was used to analyze the predictive value of Ca++ scores of different locations.

Results. The primary end point was documented in 62 % of Q4 MAC score (> 2700) patients as compared with 31% in the Q1 (< 140); p = 0.003. For primary end point logistic regression demonstrated MAC score as independent predictor either continuous variable – OR: 1.02, 95% [CI]: 1.00 – 1.03, p = 0.021; or quartile cut-offs, while Q4 was an independent predictor – OR: 3.69, 95% [CI]: 1.37 – 9.95, p = 0.010. BMI and valve size were another independent predictors of primary end point OR: 1.12, 95% [CI]: 1.04 – 1.22, p = 0.004, and OR: 1.41, 95% [CI]: 1.10 – 1.80, p = 0.006, respectively. Another clinical covariates such as older age, incomplete BBB, renal failure as well as AoV Ca++ and LVOT Ca++ scores have not reached statistical significance.

Conclusions. In patients undergoing TAVI with no preexisting CSA, MAC was found to be an independent predictor of CSA, while the score > 2700 and the score < 140 were considered as a highest and the lowest risk, respectively. Another significant predictors have been found the higher BMI and bigger implanted valve size.

Yafim Brodov

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