S. Presutti
Papers
1
Total Citations
2
H-Index
1
About
Dr. S. Presutti is a pioneering surgeon-researcher whose work focuses on the learning curves and clinical outcomes of robotic-assisted surgery, particularly in urological oncology. Their most cited study, "Using cumulative summation analysis for the learning curve of robotic docking time in radical prostatectomy with the HUGO RAS System" (2025), introduces a rigorous statistical method to evaluate surgical proficiency with emerging robotic platforms. This contribution is critical for standardizing training protocols and ensuring patient safety as new systems enter operating rooms. With 2 citations since its recent publication, the work has already sparked discussion on optimizing robotic workflow efficiency. Dr. Presutti’s research addresses the gap between the well-documented benefits of minimally invasive surgery—such as reduced blood loss and shorter hospital stays—and the practical challenges of platform availability and skill acquisition. By quantifying the learning curve, they provide actionable benchmarks for surgeons transitioning to novel robotic systems. Their work stands at the intersection of surgical innovation and evidence-based practice, offering a roadmap for integrating cutting-edge technology into routine clinical care while maintaining high standards of safety and efficacy.
Research Focus
Key Achievements
Top Papers
- 1