ArticleStructural heart : the journal of the Heart Team2025
Preprocedural CT and ECG Markers for Predicting Post-TAVR Pacemaker Requirement in High-Risk Patients.
Article in Structural heart : the journal of the Heart Team, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Machine Learning-Driven Probability of Permanent Pacemaker Implantation After Transcatheter Aortic Valve Replacement.Diagnostics (Basel, Switzerland) · 2026Article
- Conduction Abnormalities After Transcatheter Aortic Valve Replacement: Comprehensive Review of Current Literature, Guidelines, and Clinical Practices.Reviews in cardiovascular medicine · 2026Review
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Authors and funding
11 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Background: Need for permanent pacemaker implantation (PPI) following transcatheter aortic valve replacement (TAVR) remains a common complication. We aimed to assess computed tomography (CT)-based anatomical and electrocardiogram (ECG)-based parameters in a predictive model for PPI following TAVR. Methods: We assessed CT-based parameters, including the predicted course of the conduction axis from atrioventricular node to left bundle branch origin relative to the aortic virtual basal ring. Electrophysiological variables were combined in assessing a model to predict post-TAVR PPI. Results: Among 433 patients (mean age 82.0 [9.0] years, 54.0% female), 90 (21.0%) required PPI. Multiple binary logistic modeling demonstrated a shallower position of the membranous septum inferior margin midpoint increased the odds of PPI by 20% for every 1 mm (adjusted odds ratio [aOR]: 1.20) adjusted for the CT assessment phase. Increasing aortic root rotational angle associated with lower PPI odds (odds ratio [OR]: 0.98; 95% CI [0.95-1.00]), while an angle between the membranous septum midpoint and noncoronary leaflet nadir associated with increased PPI odds (OR: 1.04; 95% CI [1.01-1.08]). Preprocedural right bundle branch block and first-degree atrioventricular block associated with increased odds for PPI (OR: 3.76; 95% CI [1.71-8.21]; and OR: 1.84; 95% CI [1.06-3.18], respectively). The model had an area under the curve of 0.73 (95% CI [0.67-0.79]), sensitivity of 0.74 (95% CI [0.47-0.93]), and specificity of 0.65 (95% CI [0.40-0.87]) for predicting PPI requirement. Conclusions: A predictive model for determining the risk of PPI following TAVR is reported, combining comprehensive conduction-specific anatomical measurements relative to the aortic root and electrical measurements with clinical parameters. This model requires prospective application to understand its performance in the real-world.
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