Can aortic valve calcium score predict a need for permanent pacemaker implantation after transcatheter aortic valve implantation?

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  Figure 1. Flow chart of the selection process of the study population. During the study period, 1487 patients were admitted to our centre for TAVI. Among them, 726 patients were excluded from the study: 89 patients had valve-in-valve procedures, 181 patients had prior PPM, 447 patients had a CT scan that was not performed in our centre or that was not useable for AVCS and 9 patients underwent TAVI for pure aortic regurgitation. Our study, therefore, included a total of 761 patients. AVCS, aortic valve calcium score; PPM, permanent pacemaker; TAVI, transcatheter aortic valve implantation.

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  Figure 2. Pacemaker implantation rate according to AVCS quartiles for the overall population (n=761). This histogram represents the distribution of PPM according to AVCS quartiles. PPM rates were similar in the first three quartiles and ranged between 12% and 15%. However, we observed a significant increase in PPM rate in patients with AVCS>4510 AU (26%, p<0.001). AU, arbitrary unit; AVCS, aortic valve calcium score; PPM, permanent pacemaker.

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  Figure 3. Pacemaker implantation rate according to AVCS quartiles. (A) In patients with or without preprocedural RBBB. (B) In patients with SEV or with BEV. This histogram represents the distribution of PPM according to AVCS quartiles in patients with or without preprocedural RBBB and according to valve type. In patients with preprocedural RBBB, PPM rates were very high, but we did not observe a significant impact of AVCS (p=0.5). Yet, patients without preprocedural RBBB and with AVCS>4510 AU had a significant increase in PPM (p<0.001). In patients with SEV, we did not observe a significant impact of AVCS (p=0.069). Conversely, patients with BEV and AVCS>4510 AU had a significant increase in PPM rate (p=0.007). ANOVA, analysis of variance; AU, arbitrary unit; AVCS, aortic valve calcium score; BEV, balloon-expandable valve; PPM, permanent pacemaker; RBBB, right bundle branch block; SEV, self-expanding valve.

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  Figure 4. (A) Receiver-operating characteristic (ROC) curve analysis for AVCS to predict PPM implantation. (B) ROC curve for AVCS to predict PPM implantation in patients without RBBB. (C) ROC curve for AVCS to predict PPM implantation in patients with SEV. (D) ROC curve for AVCS to predict PPM implantation in patients with BEV. Graphical representation of the relationship between the sensitivity and specificity of AVCS to predict the risk of PPM. The area under the ROC curve was 60.3% (95% CI 54.7% to 65.9%), indicating poor predictive performance of PPM risk after TAVI. Graphical representation of the relationship between the sensitivity and specificity of AVCS to predict the risk of PPM in patients without RBBB. The area under the ROC curve was 63.5% (95% CI 56.7% to 70.4%). Graphical representation of the relationship between the sensitivity and specificity of AVCS to predict the risk of PPM in patients with SEV. The area under the ROC curve was 61% (95% CI 51.3% to 70.7%). Graphical representation of the relationship between the sensitivity and specificity of AVCS to predict the risk of PPM in patients with BEV. The area under the ROC curve was 58.9% (95% CI 51.7% to 66.1%). AUC, area…

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  Figure 5. Analysis of the incremental discriminative value of AVCS. Histogram representing the AICs of two logistic regression models. The AIC of model 1 (age, male sex, initial AV block, initial RBBB, SEV, deep prosthesis implantation, prosthesis area to annulus area ratio, postdilatation, extension of calcifications to the LVOT) was 464. The AIC of model 2 (age, male sex, initial AV block, initial RBBB, SEV, deep prosthesis implantation, prosthesis area to annulus area ratio, postdilatation, extension of calcifications to the LVOT and AVCS>4510 AU) was 459. Model 2 had a significantly greater incremental value (LR test p=0.036) with c-indexes of 0.77 for model 1 and 0.79 for model 2. AIC, Akaike information criterion; AU, arbitrary unit; AV, atrioventricular; AVCS, aortic valve calcium score; LR, likelihood ratio; LVOT, left ventricular outflow tract; RBBB, right bundle branch block; SEV, self-expanding valve.

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  Figure 6. Proposal of a preprocedural algorithm to assess the risk of PPM implantation after TAVI. Proposal of a preprocedural algorithm to assess the risk of PPM post-TAVI, considering the presence of RBBB, AVCS and the type of valve. This algorithm allows the identification of three populations: very high risk, high risk and low risk of PPM. AVCS, aortic valve calcium score; BEV, balloon expanding valve; PPM, permanent pacemaker; RBBB, right bundle branch block; SEV, self-expanding valve; TAVI, transcatheter aortic valve implantation.