Stefano Lunghetti
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Stefano Lunghetti has a total of 9 co-authors. Here are the top co-authors by number of shared publications:
- Alessia Petrini
Department of Biotechnologies, University of Siena, Viale Bracci 11, 53100 Siena, Italy
1 shared publication - Amato Santoro
Azienda Ospedaliera Universitaria Senese Siena Italy
1 shared publication - C B Claudia Baiocchi
Division of Interventional Cardiology, Azienda Ospedaliera Universitaria Senese, Viale Bracci 11, 53100 Siena, Italy
1 shared publication - Francesco Morrone
Department of Medical Biotechnologies, Division of Cardiology, Ospedale “S. Maria alle Scotte”, University of Siena, Viale Mario Bracci, 16, 53100 Siena, Italy
1 shared publication - Laura Spaccaterra
Department of Medical Biotechnologies, Division of Cardiology, University of Siena, 53100 Siena, Italy
1 shared publication - Massimo Fineschi
Interventional Cardiology Azienda Ospedaliera Universitaria Senese Siena Italy
1 shared publication
Latest Publications
- Open Access
- 8 December 2025
- Published by MDPI AG in Journal of Clinical Medicine
- Vol. 14 (24) , 8684
Assessing the Learning Curve in Conduction System Pacing Implantation
Background: Conduction system pacing (CSP) has emerged as an alternative to biventricular pacing (BiVp), but its implantation requires a specific learning curve. Early experience was dominated by His bundle pacing (HBP) with lumenless leads (LLL), whereas the subsequent adoption of left bundle branch area pacing (LBBAP) and the increasing procedural standardization led to a simplification of the technique and greater uniformity in its execution. This study evaluated the learning curve for CSP by analyzing the first consecutive implants of two electrophysiologists (operator 1: OP1 and operator 2: OP2). Methods: The first 55 CSP procedures performed by each operator (n = 110) were retrospectively analyzed. Implantation and fluoroscopy times were assessed in blocks of five cases. Univariate and multivariable linear regression were used to identify independent predictors of procedural complexity. Results: A total of 110 CSP implants (55 per electrophysiologist) were analyzed. Implantation time progressively decreased with experience, reaching a stable plateau after ~45 cases per operator, when inter-operator curves completely overlapped and differences were no longer significant. Fluoroscopy time stabilized earlier and showed no consistent differences between electrophysiologists. In the univariate analysis, longer procedural times were associated with larger left ventricular end-diastolic diameters (LVEDD: r: 0.43; p < 0.001), LLL (r: 0.25; p < 0.01) and earlier implant numbers (r: 0.36; p < 0.001). In the multivariable models, only LVEDD and implant number (IN) remained independent predictors of procedure duration (LVEDD: β: 2.04, p: 0.04; and IN: β: 3.26, p < 0.04). Conclusions: CSP implantation follows a distinct learning curve, with procedure duration stabilizing after approximately 45 cases per operator. Procedural complexity is mainly determined by patient factors (LVEDD) and operator-related factors, whereas differences between LLL and SL reflect historical experience rather than intrinsic technical characteristics.
- 8 December 2025
- Published by MDPI AG in Journal of Clinical Medicine
- Vol. 14 (24) , 8684
Open AccessAssessing the Learning Curve in Conduction System Pacing Implantation
Background: Conduction system pacing (CSP) has emerged as an alternative to biventricular pacing (BiVp), but its implantation requires a specific learning curve. Early experience was dominated by His bundle pacing (HBP) with lumenless leads (LLL), whereas the subsequent adoption of left bundle branch area pacing (LBBAP) and the increasing procedural standardization led to a simplification of the technique and greater uniformity in its execution. This study evaluated the learning curve for CSP by analyzing the first consecutive implants of two electrophysiologists (operator 1: OP1 and operator 2: OP2). Methods: The first 55 CSP procedures performed by each operator (n = 110) were retrospectively analyzed. Implantation and fluoroscopy times were assessed in blocks of five cases. Univariate and multivariable linear regression were used to identify independent predictors of procedural complexity. Results: A total of 110 CSP implants (55 per electrophysiologist) were analyzed. Implantation time progressively decreased with experience, reaching a stable plateau after ~45 cases per operator, when inter-operator curves completely overlapped and differences were no longer significant. Fluoroscopy time stabilized earlier and showed no consistent differences between electrophysiologists. In the univariate analysis, longer procedural times were associated with larger left ventricular end-diastolic diameters (LVEDD: r: 0.43; p < 0.001), LLL (r: 0.25; p < 0.01) and earlier implant numbers (r: 0.36; p < 0.001). In the multivariable models, only LVEDD and implant number (IN) remained independent predictors of procedure duration (LVEDD: β: 2.04, p: 0.04; and IN: β: 3.26, p < 0.04). Conclusions: CSP implantation follows a distinct learning curve, with procedure duration stabilizing after approximately 45 cases per operator. Procedural complexity is mainly determined by patient factors (LVEDD) and operator-related factors, whereas differences between LLL and SL reflect historical experience rather than intrinsic technical characteristics.