St John's College, University of Cambridge, Cambridge, UK.
BJU Int. 2012 Apr;109(7):1074-80. doi: 10.1111/j.1464-410X.2011.10665.x. Epub 2011 Oct 28.
Structured mentor-led training programmes permit the safe introduction of novice trainees to robotic-assisted laparoscopic prostatectomy (RALP). We outline the first description of parallel learning curves for individual surgical steps and quantify the relative difficulty of each step to propose an order of training in our structured mentoring programme.
A prospective ethically approved database was used to evaluate the operating times of each individual surgical step, in the first 150 RALP cases performed independently by a robotic-naive laparoscopic surgeon. Linear regression analysis was used to quantify the effect of surgeon experience on the operating time for each individual surgical step.
Univariate linear regression analysis revealed significant reductions in operating time over the first 150 cases for all of the RALP steps, with the exception of the Rocco stitch. Multivariate linear regression analysis compensated for confounding variables and led to the identification of five surgical steps in which the operating time of each was significantly influenced by experience of the procedure. The most substantial improvement in operating time was seen in the bladder take down step. After taking into account the multivariate regression model, standardized univariate coefficients allowed an order of training to be identified for future RALP novices, of increasing complexity rather than order of surgery, beginning with the bladder take down step and ending with the vesico-urethral anastomosis.
We can begin the training of new robotic-naive surgeons at simpler surgical steps, in which the greatest gains in expediency are made. We anticipate that identifying the more challenging surgical steps from this study and targeting training towards them may expedite our future trainees' proficiency at RALP.
结构化导师指导培训计划允许将新手学员安全引入机器人辅助腹腔镜前列腺切除术（RALP）。我们概述了单个手术步骤的平行学习曲线的首次描述，并量化了每个步骤的相对难度，以在我们的结构化指导计划中提出培训顺序。
前瞻性伦理批准的数据库用于评估第一位机器人新手腹腔镜外科医生独立完成的前 150 例 RALP 中每个手术步骤的手术时间。线性回归分析用于量化每个手术步骤的手术时间随外科医生经验的变化。
单变量线性回归分析显示，在 150 例 RALP 手术中，所有手术步骤的手术时间都显著缩短，除了 Rocco 缝合。多变量线性回归分析补偿了混杂变量，并确定了五个手术步骤，其中每个步骤的手术时间都受到手术经验的显著影响。膀胱切除步骤的手术时间改善最为显著。在考虑到多变量回归模型后，标准化单变量系数可以确定未来 RALP 新手的培训顺序，从简单到复杂，而不是按照手术顺序，从膀胱切除步骤开始，最后进行膀胱颈吻合术。
我们可以从更简单的手术步骤开始对新的机器人新手外科医生进行培训，在这些步骤中可以更快地提高效率。我们预计，从这项研究中确定更具挑战性的手术步骤并将培训重点放在这些步骤上，可以加快我们未来学员在 RALP 方面的熟练程度。
