Wilson-Smith Ashley R, Anning Naomi, Muston Benjamin, Eranki Aditya, Williams Michael L, Wilson-Smith Christian J, Rivas Diego G, Yan Tristan D
The Chris O'Brien Lifehouse Center, Sydney, Australia.
The Collaborative Research Group (CORE), Sydney, Australia.
Ann Cardiothorac Surg. 2023 Jan 31;12(1):1-8. doi: 10.21037/acs-2022-urats-14. Epub 2023 Jan 14.
Early studies have illustrated the robotic lobectomy to be safe, oncologically effective, and economically feasible as a therapeutic modality in the treatment of thoracic malignancies. The 'challenging' learning curve seemingly associated with the robotic approach, however, continues to be an often-cited factor to its ongoing uptake, with the overwhelming volume of these surgeries being performed in centers of excellence where extensive experience with minimal access surgery is the norm. An exact quantification of this learning curve challenge, however, has not been made, begging the question of whether this is an outdated assumption, versus fact. This systematic review and meta-analysis sort to clarify the learning curve for robotic-assisted lobectomy based on the existing literature.
An electronic search of four databases was performed to identify relevant studies outlining the learning curve of robotic lobectomy. The primary endpoint was a clear definition of operator learning (e.g., cumulative sum chart, linear regression, outcome-specific analysis, etc.) which could be subsequently aggregated or reported. Secondary endpoints of interest included post-operative outcomes and complication rates. A meta-analysis using a random effects model of proportions or means was applied, as appropriate.
The search strategy identified twenty-two studies relevant for inclusion. A total of 3,246 patients (30% male) receiving robotic-assisted thoracic surgery (RATS) were identified. The mean age of the cohort was 65.3±5.0 years. Mean operative, console and dock time was 190.5±53.8, 125.8±33.9 and 10.2±4.0 minutes, respectively. Length of hospital stay was 6.1±4.6 days. Technical proficiency with the robotic-assisted lobectomy was achieved at a mean of 25.3±12.6 cases.
The robotic-assisted lobectomy has been illustrated to have a reasonable learning curve profile based on the existing literature. Current evidence on the oncologic efficacy and purported benefits of the robotic approach will be bolstered by the results of upcoming randomized trials, which will be critical in supporting RATS uptake.
早期研究表明，机器人辅助肺叶切除术作为一种治疗胸部恶性肿瘤的治疗方式，具有安全性、肿瘤学有效性和经济可行性。然而，机器人手术方法似乎存在“具有挑战性”的学习曲线，这仍然是其广泛应用的一个经常被提及的因素，这些手术绝大多数是在具备广泛的微创外科经验的卓越中心进行的。然而，尚未对这种学习曲线挑战进行精确量化，这引发了一个问题，即这是一个过时的假设还是事实。本系统评价和荟萃分析旨在根据现有文献阐明机器人辅助肺叶切除术的学习曲线。
对四个数据库进行电子检索，以识别概述机器人肺叶切除术学习曲线的相关研究。主要终点是对术者学习的明确定义（例如，累积和图、线性回归、特定结果分析等），随后可对其进行汇总或报告。感兴趣的次要终点包括术后结果和并发症发生率。根据情况，采用比例或均值的随机效应模型进行荟萃分析。
检索策略确定了22项相关纳入研究。共纳入3246例接受机器人辅助胸外科手术（RATS）的患者（30%为男性）。该队列的平均年龄为65.3±5.0岁。平均手术时间、控制台操作时间和对接时间分别为190.5±53.8分钟、125.8±33.9分钟和10.2±4.0分钟。住院时间为6.1±4.6天。平均25.3±12.6例手术可达到机器人辅助肺叶切除术的技术熟练程度。
根据现有文献，机器人辅助肺叶切除术已被证明具有合理的学习曲线。即将开展的随机试验结果将支持机器人辅助肺叶切除术在肿瘤学疗效和所谓益处方面的现有证据，这对于支持RATS的应用至关重要。
