Culligan Patrick, Gurshumov Emil, Lewis Christa, Priestley Jennifer, Komar Jodie, Salamon Charbel
From the Department of Urogynecology, Atlantic Health System, Morristown, NJ; and †Department of Mathematics, Kennesaw State University, Kennesaw, GA.
Female Pelvic Med Reconstr Surg. 2014 Jan-Feb;20(1):48-51. doi: 10.1097/SPV.0000000000000045.
Robotic surgery simulation may provide a way for surgeons to acquire specific robotic surgical skills without practicing on live patients.
Five robotic surgery experts performed 10 simulator skills to the best of their ability, and thus, established expert benchmarks for all parameters of these skills. A group of credentialed gynecologic surgeons naive to robotics practiced the simulator skills until they were able to perform each one as well as our experts. Within a week of doing so, they completed robotic pig laboratory training, after which they performed supracervical hysterectomies as their first-ever live human robotic surgery. Time, blood loss, and blinded assessments of surgical skill were compared among the experts, novices, and a group of control surgeons who had robotic privileges but no simulator exposure. Sample size estimates called for 11 robotic novices to achieve 90% power to detect a 1 SD difference between operative times of experts and novices (α = 0.05).
Fourteen novice surgeons completed the study-spending an average of 20 hours (range, 9.7-38.2 hours) in the simulation laboratory to pass the expert protocol. The mean operative times for the expert and novices were 20.2 (2.3) and 21.7 (3.3) minutes, respectively (P = 0.12; 95% confidence interval, -1.7 to 4.7), whereas the mean time for control surgeons was 30.9 (0.6) minutes (P < 0.0001; 95% confidence interval, 6.3-12.3). Comparisons of estimated blood loss (EBL) and blinded video assessment of skill yielded similar differences between groups.
Completing this protocol of robotic simulator skills translated to expert-level surgical times during live human surgery. As such, we have established predictive validity of this protocol.
机器人手术模拟可为外科医生提供一种在不活体患者身上练习的情况下获得特定机器人手术技能的方法。
五名机器人手术专家尽其所能执行10项模拟技能,从而为这些技能的所有参数建立了专家基准。一组对机器人技术不熟悉的有资质的妇科外科医生练习模拟技能,直到他们能够像我们的专家一样出色地完成每一项技能。在这样做的一周内,他们完成了机器人猪实验室训练,之后他们进行了首次活体人类机器人手术——次全子宫切除术。比较了专家、新手以及一组拥有机器人手术权限但未接触过模拟器的对照外科医生之间的手术时间、失血量和对手术技能的盲法评估。样本量估计需要11名机器人手术新手,以达到90%的检验效能来检测专家和新手手术时间之间1个标准差的差异(α = 0.05)。
14名新手外科医生完成了研究——在模拟实验室平均花费20小时(范围为9.7 - 38.2小时)以通过专家方案。专家和新手的平均手术时间分别为20.2(2.3)分钟和21.7(3.3)分钟(P = 0.12;95%置信区间为 - 1.7至4.7),而对照外科医生的平均时间为30.9(0.6)分钟(P < 0.0001;95%置信区间为6.3 - 12.3)。估计失血量(EBL)和技能的盲法视频评估在组间产生了类似的差异。
完成这套机器人模拟技能方案可转化为活体人类手术中专家级别的手术时间。因此,我们确立了该方案的预测效度。