Sorce Gabriele, Paciotti Marco, Würnschimmel Christoph, Wenzel Mike, Bravi Carlo Andrea, De Groote Ruben, Dell'Oglio Paolo, Di Maida Fabrizio, Tappero Stefano, Moschovas Marcio Covas, Piramide Federico, Turri Filippo, Andras Iulia, Joseph Danny Darlington Carbin, Eraky Ahmed, Liakos Nikolaos, Gallagher Anthony, Veneziano Domenico, Brouwers Ton, Liatzikos Evangelos, Russo Giorgio Ivan, Breda Alberto, Larcher Alessandro
Department of Oncology, Urologic Section, AOU G. Martino, Messina, Italy.
ORSI Academy, Melle, Belgium.
J Robot Surg. 2025 Jun 25;19(1):325. doi: 10.1007/s11701-025-02413-2.
The increasing use of robotic systems in urologic surgery necessitates standardized training curricula to ensure novice surgeons acquire essential skills. This study developed and validated performance metrics for two dry-lab models-a proficiency-based progression (PBP)-based orange model for dissection, suturing, and knot-tying and a catheter-balloon model for vesicourethral anastomosis. An international expert group from the Young Academic Urologists Robotics and the European Robotic Urology Section utilized a Delphi-based consensus process to develop and refine procedural steps, errors, and critical errors for the two models. The orange model simulated dissection, suturing, and knot-tying, while the catheter-balloon model simulated vesicourethral anastomosis during radical prostatectomy. The Delphi rounds ensured > 80% agreement on steps and critical and non-critical errors for each task, refining the models' performance metrics to maximize their educational value. Consensus was achieved on the performance metrics for both models. For the orange model, the procedure was divided into three steps-dissection, suturing, and knot-tying-identifying nine, 13, and five non-critical errors, respectively, with three critical errors recognized. The catheter-balloon model included two steps-suturing and knot-tying-identifying 13 and five non-critical errors, respectively, with three critical errors recognized, including anastomosis leakage. The developed performance metrics for the orange and catheter-balloon models offer a structured and accessible approach to training novice surgeons in essential robotic surgical skills. These models can be easily integrated into various training settings and form a core component of a PBP curriculum, ensuring the safe and effective training of future robotic surgeons.
机器人系统在泌尿外科手术中的使用日益增加，因此需要标准化的培训课程，以确保新手外科医生掌握基本技能。本研究针对两种干式实验室模型开发并验证了性能指标，一种是基于熟练度进阶（PBP）的橙色模型，用于解剖、缝合和打结；另一种是导管球囊模型，用于膀胱尿道吻合术。来自青年学术泌尿外科机器人学组和欧洲机器人泌尿外科分会的一个国际专家小组采用基于德尔菲法的共识过程，为这两种模型制定并完善了操作步骤、错误和关键错误。橙色模型模拟解剖、缝合和打结，而导管球囊模型在根治性前列腺切除术中模拟膀胱尿道吻合术。德尔菲轮次确保了每项任务的步骤以及关键和非关键错误的一致性超过80%，完善了模型的性能指标，以最大限度地提高其教育价值。两种模型的性能指标均达成了共识。对于橙色模型，该操作分为三个步骤——解剖、缝合和打结，分别识别出9个、13个和5个非关键错误，同时识别出3个关键错误。导管球囊模型包括两个步骤——缝合和打结，分别识别出13个和5个非关键错误，同时识别出3个关键错误，包括吻合口漏。为橙色模型和导管球囊模型开发的性能指标为培训新手外科医生掌握基本机器人手术技能提供了一种结构化且易于操作的方法。这些模型可以轻松融入各种培训环境，并构成PBP课程体系的核心组成部分，确保未来机器人外科医生得到安全有效的培训。
