Giroletti Laura, Brembilla Valentina, Graniero Ascanio, Albano Giovanni, Villari Nicola, Roscitano Claudio, Parrinello Matteo, Grazioli Valentina, Lanzarone Ettore, Agnino Alfonso
Division of Robotic and Minimally Invasive Cardiac Surgery, Humanitas Gavazzeni Hospital, 24125 Bergamo, Italy.
Department of Management, Information and Production Engineering, University of Bergamo, 24044 Dalmine (Bg), Italy.
Medicina (Kaunas). 2023 Aug 29;59(9):1568. doi: 10.3390/medicina59091568.
Renewed interest in robot-assisted cardiac procedures has been demonstrated by several studies. However, concerns have been raised about the need for a long and complex learning curve. In addition, the COVID-19 pandemic in 2020 might have affected the learning curve of these procedures. In this study, we investigated the impact of COVID-19 on the learning curve of robotic-assisted mitral valve surgery (RAMVS). The aim was to understand whether or not the benefits of RAMVS are compromised by its learning curve. Between May 2019 and March 2023, 149 patients underwent RAMVS using the Da Vinci X Surgical System at the Humanitas Gavazzeni Hospital, Bergamo, Italy. The selection of patients enrolled in the study was not influenced by case complexity. Regression models were used to formalize the learning curves, where preoperative data along with date of surgery and presence of COVID-19 were treated as the input covariates, while intraoperative and postoperative data were analyzed as output variables. The age of patients was 59.1 ± 13.3 years, and 70.5% were male. In total, 38.2% of the patients were operated on during the COVID-19 pandemic. The statistical analysis showed the positive impact of the learning curve on the trend of postoperative parameters, progressively reducing times and other key indicators. Focusing on the COVID-19 pandemic, statistical analysis did not recognize an impact on postoperative outcomes, although it became clear that variables not directly related to the intervention, especially ICU hours, were strongly influenced by hospital logistics during COVID-19. Understanding the learning curve of robotic surgical procedures is essential to ensure their effectiveness and benefits. The learning curve involves not only surgeons but also other health care providers, and establishing a stable team in the early stage, as in our case, is important to shorten the duration. In fact, an exogenous factor such as the COVID-19 pandemic did not affect the robotic program despite the fact that the pandemic occurred early in the program.
多项研究表明,人们对机器人辅助心脏手术重新产生了兴趣。然而,对于是否需要漫长而复杂的学习曲线,人们也提出了担忧。此外,2020年的新冠疫情可能影响了这些手术的学习曲线。在本研究中,我们调查了新冠疫情对机器人辅助二尖瓣手术(RAMVS)学习曲线的影响。目的是了解RAMVS的益处是否因其学习曲线而受到损害。2019年5月至2023年3月期间,149例患者在意大利贝加莫的乌玛尼塔斯·加瓦泽尼医院使用达芬奇X手术系统接受了RAMVS。纳入该研究的患者选择不受病例复杂性的影响。使用回归模型来确定学习曲线,将术前数据以及手术日期和是否感染新冠作为输入协变量,同时将术中及术后数据作为输出变量进行分析。患者年龄为59.1±13.3岁,70.5%为男性。总共有38.2%的患者在新冠疫情期间接受了手术。统计分析表明,学习曲线对术后参数趋势有积极影响,逐渐减少了手术时间和其他关键指标。聚焦于新冠疫情,统计分析未发现其对术后结果有影响,尽管很明显与干预无直接关系的变量,尤其是重症监护病房(ICU)时长,在新冠疫情期间受到医院后勤的强烈影响。了解机器人手术程序的学习曲线对于确保其有效性和益处至关重要。学习曲线不仅涉及外科医生,还涉及其他医疗保健提供者,正如我们的案例所示,在早期建立一个稳定的团队对于缩短手术时长很重要。事实上,尽管新冠疫情在该项目早期发生,但像这样的外部因素并未影响机器人手术项目。