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April 1, 2026European Heart Journal Supplements0 citations

Predicting permanent pacemaker implantation after transcatheter aortic valve replacement in self-expandable cohorts

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HKHaitham Abu KhadijaMAMohammad AlneesGJG Jacob

Key Result

A predictive model incorporating inflammatory markers, anatomical factors, and right bundle branch block (OR 4.64) accurately predicted pacemaker implantation after TAVR (AUC 0.8628).

Key Points

  • The aim is to identify predictors of permanent pacemaker implantation (PPI) after transcatheter aortic valve replacement (TAVR) using various clinical and inflammatory markers.
  • Retrospective cohort analysis of 587 patients undergoing TAVR with self-expandable valves.
  • Assessment of clinical, anatomical, and inflammatory parameters, focusing on blood count-derived ratios.
  • Development of multivariable logistic regression models to identify predictors of PPI.
  • Evaluation of predictor accuracy using receiver operating characteristic (ROC) curves.
  • Elevated pre-procedural neutrophil-to-lymphocyte ratio significantly increased PPI risk (OR 1.18; p = 0.008).
  • The systemic immune-inflammation index was also a significant predictor (OR 1.0012; p = 0.001).
  • Anatomical factors like septum thickness and valve size contributed to PPI risk.
  • Post-dilatation was linked to reduced PPI risk (OR 0.54; p = 0.031).
  • The model demonstrated high accuracy for predicting PPI (AUC 0.8628).

Structured PICO

Can clinical, anatomical, and immune-inflammatory markers predict permanent pacemaker implantation in patients undergoing TAVR with self-expandable valves?

P
Population
587 patients undergoing transcatheter aortic valve replacement (TAVR) with self-expandable valves
I
Intervention
Assessment of clinical, anatomical, and immune-inflammatory parameters (NLR, PLR, LMR, SII, ELR) prior to TAVR
O
Outcome
Permanent Pacemaker Implantation (PPI) post-TAVRsafety

A predictive model combining inflammatory markers (NLR, SII), anatomical factors, and procedural details accurately estimates the risk of permanent pacemaker implantation after TAVR with self-expandable valves.

Abstract

Abstract Background Permanent Pacemaker Implantation (PPI) is a common complication following transcatheter aortic valve replacement (TAVR). Identifying predictors, particularly immune-inflammatory markers, can enhance pre-procedural risk stratification. Methods In this retrospective cohort study, we analyzed 587 patients undergoing TAVR with self-expandable valves. We assessed clinical, anatomical, and inflammatory parameters, focusing on five complete blood count-derived ratios: neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), and eosinophil-to-lymphocyte ratio (ELR). Multivariable logistic regression models were developed to identify predictors of PPI. Receiver operating characteristic (ROC) curves evaluated the discriminative ability of these markers. Results In our cohort of 587 patients undergoing TAVR with self-expandable valves, multivariable logistic regression identified several significant predictors for PPI. Elevated pre-procedural NLR was associated with increased PPI risk (odds ratio OR 1.18; p = 0.008), as was the SII (OR 1.0012; p = 0.001). Anatomical and procedural factors also contributed: septum thickness (OR 1.24; p = 0.025), valve size (OR 1.10; p = 0.025), and longer procedure time (OR 1.013; p = 0.003). Post-dilatation was associated with reduced PPI risk (OR 0.54; p = 0.031). Electrical conduction parameters, including QRS duration (OR 1.015; p = 0.018) and presence of right bundle branch block (RBBB) (OR 4.64; p = 0.027), were significant predictors. The model demonstrated strong discriminative ability with an area under the curve (AUC) of 0.8628, indicating high accuracy in distinguishing patients at risk for PPI post-TAVR. Conclusions We developed a predictive equation combining inflammatory, anatomical, and procedural factors to estimate PPI risk after TAVR. This tool demonstrated high accuracy and clinical utility, supporting personalized risk assessment, procedural planning, and improved patient outcomes in TAVR populations.TAVR risk Prediction for PPIFor image description, please refer to the figure legend and surrounding text. ROC CurveFor image description, please refer to the figure legend and surrounding text.

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Cite This Study

Khadija et al. (2026) studied this question. A predictive model incorporating inflammatory markers, anatomical factors, and right bundle branch block (OR 4.64) accurately predicted pacemaker implantation after TAVR (AUC 0.8628).

synapsesocial.com/papers/69ccb69d16edfba7beb88425https://doi.org/10.1093/eurheartjsupp/suag056.067
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