Minimally Invasive and Robot Surgery Center, Toyonaka Keijinkai Hospital, Shoji, Toyonaka-shi, Osaka, Japan.
Department of General and Gastroenterological Surgery, Osaka Medical and Pharmaceutical University, Daigaku-machi, Takatsuki-shi, Osaka, Japan.
Medicine (Baltimore). 2023 Jun 9;102(23):e34010. doi: 10.1097/MD.0000000000034010.
Robotic surgery rates, typified by the use of the da Vinci Surgical System, have increased in recent years. However, robotic surgery is mostly performed in large hospitals and has not been fully implemented in small hospitals. Therefore, we aimed to verify the feasibility of robotic surgery in small hospitals and verify the number of cases in which perioperative preparation for robotic surgery is stable by creating a learning curve in small hospitals. Forty robot-assisted rectal cancer surgeries performed in large and small hospitals by a surgeon with extensive experience in robotic surgery were validated. Draping and docking times were recorded as perioperative preparation times. Unexpected surgical interruptions, intraoperative adverse events, conversion to laparoscopic or open surgery, and postoperative complications were recorded. Cumulative sum analysis was used to derive the learning curve for perioperative preparation time. Draping times were significantly longer in the small hospital group (7 vs 10 minutes, P = .0002), while docking times were not significantly different (12 vs 13 minutes, P = .098). Surgical interruptions, intraoperative adverse events, and conversions were not observed in either group. There were no significant differences in the incidence of severe complications (25% [5/20] vs 5% [1/20], P = .184). In the small hospital group, phase I of the draping learning curve was completed in 4 cases, while phase I of the docking learning curve was completed in 7 cases. Robotic surgery is feasible for small hospitals, and the preoperative preparation time required for robotic surgery stabilizes relatively early.
机器人手术的比例在近年来有所增加,其代表为达芬奇手术系统的使用。然而,机器人手术主要在大型医院进行,尚未在小型医院全面实施。因此,我们旨在验证在小型医院中进行机器人手术的可行性,并通过在小型医院中创建学习曲线来验证机器人手术的围手术期准备的稳定病例数。验证了一位在机器人手术方面经验丰富的外科医生在大型和小型医院进行的 40 例机器人辅助直肠癌手术。记录了覆盖和对接时间作为围手术期准备时间。记录了意外的手术中断、术中不良事件、转为腹腔镜或开放手术以及术后并发症。使用累积和分析得出围手术期准备时间的学习曲线。小型医院组的覆盖时间明显更长(7 分钟与 10 分钟,P=0.0002),而对接时间无显著差异(12 分钟与 13 分钟,P=0.098)。两组均未观察到手术中断、术中不良事件和转换。严重并发症的发生率无显著差异(25%[5/20]与 5%[1/20],P=0.184)。在小型医院组中,覆盖学习曲线的第 I 阶段完成了 4 例,而对接学习曲线的第 I 阶段完成了 7 例。机器人手术对小型医院来说是可行的,并且机器人手术所需的术前准备时间相对较早稳定。