• PPMI
• RITMO score
• stenosi aortica (aortic stenosis)
• TAVI

Background:
Permanent pacemaker implantation (PPMI) is among the most frequent complications following transcatheter aortic valve implantation (TAVI), particularly with self-expanding valves (SEV). Identifying patients at higher risk for PPMI is crucial for optimizing procedural planning and post-operative management.
Methods:
This study aimed to develop and validate a simple and effective risk prediction model, the RITMO score, for estimating the risk of PPMI within 30 days of TAVI. A total of 370 patients who underwent TAVI with SEVs between February 2015 and June 2022 were included in the development cohort (DC). The score was developed via identification of independent predictors of PPMI at multivariate analysis, attributing a score to each predictor based on its  coefficient in the regression model. A validation cohort (VC) of 234 patients treated between July 2022 and June 2024 was then used to test the model.
Results:
PPMI occurred in 19,5% of patients in DC. Multivariate analysis identified right bundle branch block (RBBB), membranous septum length (MSL) <5 mm, and high aortic calcium load (ACL) assessed by an Agatston score ≥1830 HU as independent predictors of 30-day PPMI. To build the RITMO score, RBBB was attributed a score of 2, Agatston score a score of 1, and MSL a score of 1 point if shorter than 5 mm, a score of 0 if between 5 and 10 mm, or a score of -1 if longer than 10 mm. Patients with a RITMO score ≥2 had over a sixfold increased risk of PPMI as compared to patients with RITMO score <2 independently from the height of implant, while patients with RITMO score of -1 had an estimated risk of PPMI of 1,8% vs 87,6% in patients with RITMO score of 4. In the present study, two multivariable models were developed to estimate the 30-day risk of PPMI, using two different methods to assess aortic valve calcification: the Agatston score and calcium volume. The predictive model based on the Agatston score demonstrated good discrimination (C-statistic = 0.714) and strong agreement between predicted and observed risk according to the derived point system (K = 0.89) in DC. In contrast, the model based on calcium volume showed slightly lower discrimination (C-statistic = 0.699) and substantial agreement with the point-based risk estimates (K = 0.71). Given its superior discriminatory performance, the Agatston method for ACL estimation was selected as the foundation for the RITMO score.
Conclusions:
The RITMO score is a simple, reproducible, and clinically useful tool for stratifying the risk of PPMI in patients undergoing TAVI with SEVs. Its implementation could support individualized procedural strategies and enhance patient counseling.