Coco Danilo, Leanza Silvana
Department of General Surgery, Giglio Hospital Foundation, Cefalu', Italy.
J Robot Surg. 2025 Sep 10;19(1):582. doi: 10.1007/s11701-025-02470-7.
The adoption of robotic pancreatectomy has grown significantly in recent years, driven by its potential advantages in precision, minimally invasive access, and improved patient recovery. However, mastering these complex procedures requires overcoming a substantial learning curve, and the role of structured mentoring in facilitating this transition remains underexplored. This systematic review and meta-analysis aimed to comprehensively evaluate the number of cases required to achieve surgical proficiency, assess the impact of mentoring on skill acquisition, and analyze how outcomes evolve throughout the learning process. Following PRISMA guidelines, we conducted a thorough literature search across PubMed, Embase, and the Cochrane Library, encompassing studies published from the inception of robotic pancreatic surgery up to 2025. We included studies that explicitly reported on learning curves, mentoring interventions, or skill progression in robotic pancreatic resections. Meta-analytical methods were employed to synthesize data on operative time, intraoperative blood loss, conversion rates, and postoperative complications. After screening 1,234 records, 25 studies met our inclusion criteria. Our findings indicate that achieving proficiency in robotic distal pancreatectomy typically requires 20-30 cases, with operative time stabilizing around 180 min beyond this threshold. In contrast, robotic pancreatoduodenectomy, being more technically demanding, necessitated 40-60 cases before surgeons reached consistent performance levels. Notably, surgeons who underwent formal mentoring programs demonstrated a shortened learning curve, requiring approximately 10-15 fewer cases to achieve comparable outcomes. Furthermore, mentored surgeons exhibited significantly lower complication rates (OR 0.62, 95% CI 0.45-0.85) and reduced operative times (mean difference - 45 min, 95% CI - 60 to - 30).These results underscore the importance of structured training and mentorship in robotic pancreatic surgery. The integration of standardized learning pathways, simulation-based training, and proctored early cases may optimize skill acquisition and improve patient outcomes. Future research should focus on defining universal benchmarks for proficiency and evaluating long-term benefits of mentorship programs.
近年来，由于机器人胰腺切除术在精准度、微创入路及改善患者恢复方面具有潜在优势，其应用显著增加。然而，掌握这些复杂手术需要克服相当大的学习曲线，而结构化指导在促进这一转变过程中的作用仍未得到充分探索。本系统评价和荟萃分析旨在全面评估达到手术熟练程度所需的病例数，评估指导对技能获取的影响，并分析在整个学习过程中结果是如何演变的。按照PRISMA指南，我们对PubMed、Embase和Cochrane图书馆进行了全面的文献检索，涵盖从机器人胰腺手术开展至2025年发表的研究。我们纳入了明确报告机器人胰腺切除术学习曲线、指导干预或技能进展的研究。采用荟萃分析方法综合手术时间、术中失血量、中转率及术后并发症的数据。在筛选1234条记录后，25项研究符合我们的纳入标准。我们的研究结果表明，要熟练掌握机器人远端胰腺切除术通常需要20 - 30例手术，超过这个阈值后手术时间稳定在180分钟左右。相比之下，机器人胰十二指肠切除术技术要求更高，外科医生在达到稳定的手术表现水平之前需要40 - 60例手术。值得注意的是，接受正规指导计划的外科医生学习曲线缩短，达到可比结果所需的病例数大约少10 - 15例。此外，接受指导的外科医生并发症发生率显著更低（OR 0.62，95% CI 0.45 - 0.85），手术时间缩短（平均差异 - 45分钟，95% CI - 60至 - 30）。这些结果强调了结构化培训和指导在机器人胰腺手术中的重要性。标准化学习路径、基于模拟的培训以及有指导的早期病例的整合可能会优化技能获取并改善患者预后。未来的研究应专注于确定熟练程度的通用基准，并评估指导计划的长期益处。
