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Preprocedural CT and ECG Markers for Predicting Post-TAVR Pacemaker Requirement in High-Risk Patients
Justin T Tretter1, Mackram F Eleid2, Francesco Bedogni3
1Hobart Healthcare Research Institute, London, UK.
Insights
A new model predicts permanent pacemaker implantation (PPI) after transcatheter aortic valve replacement (TAVR) using CT and ECG data. This tool helps identify patients at higher risk for PPI, improving procedural planning.
Area of Science:
- Cardiology
- Medical Imaging
- Biomedical Engineering
Background:
- Permanent pacemaker implantation (PPI) is a frequent complication after transcatheter aortic valve replacement (TAVR).
- Accurate prediction of PPI risk is crucial for patient management and procedural optimization.
Purpose of the Study:
- To develop and evaluate a predictive model for PPI following TAVR.
- To integrate computed tomography (CT)-based anatomical and electrocardiogram (ECG)-based parameters for enhanced prediction accuracy.
Main Methods:
- Assessed CT-derived anatomical parameters, focusing on the conduction axis relative to the aortic virtual basal ring.
- Combined electrophysiological variables with anatomical data to build a predictive model for post-TAVR PPI.
- Utilized multiple binary logistic regression to identify significant predictors and assess model performance (AUC, sensitivity, specificity).
Main Results:
- The predictive model identified several key factors associated with increased PPI risk, including membranous septum position and specific preprocedural ECG findings (right bundle branch block, first-degree AV block).
- A shallower membranous septum inferior margin midpoint increased PPI odds by 20% per millimeter.
- The model achieved an area under the curve (AUC) of 0.73, indicating moderate predictive capability.
Conclusions:
- A novel predictive model combining anatomical and electrical parameters can estimate PPI risk after TAVR.
- This model offers a valuable tool for risk stratification and procedural planning in TAVR patients.
- Further prospective validation is necessary to confirm the model's real-world clinical utility and performance.
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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