RESUMEN
BACKGROUND: The ergonomic advantages and potential challenges that robotic surgery poses to the well-being of surgeons are mainly unexplored. The most recent surgical robot introduced on the European market is the Hugo™ RAS System by Medtronic. This study aims to evaluate the ergonomic benefits of the Hugo™ RAS System, which is available in our training laboratory, CeMIT (Center for Medical Innovation and Technology Cologne). METHODS AND PROCEDURES: Using the previously established Cologne Ergonomic Measurement Setup for Robotic Surgery (CEMRobSurg), we measured three parameters related to ergonomic posture from subjects with different levels of surgical expertise (laypeople, medical students, surgical residents, and expert robotic surgeons). The heart rate was measured continuously using a polar band. The noise level was measured while using the Hugo™ RAS System, and automated photographs using our locally developed methodology were captured of the participant every 2 s to assess body posture. The ergonomic measurements were conducted while the subject performed the same standardized robotic training exercises (Peg Board, Rope Walk, and Ring Walk). RESULTS: A total of 53 participants were enrolled in this study. The average noise level during all measurements was 54.87 dB. The highest stress level was measured in surgical residents with a sympathetic nervous system index (SNS index) of 1.15 (min - 1.43, max 3.56). The lowest stress level was measured in robotic experts with an SNS index of 0.23 (min - 0.18, max 0.91). We observed a risk-prone positioning of the neck and elbow in medical students (mean 39.6° and 129.48°, respectively). Robotic experts showed a risk positioning in the knee and hip region (mean 107.89° and 90.31°, respectively). CONCLUSION: This is the first study to analyze and objectify the ergonomic posture of medical students, surgical trainees, surgeons, and laypeople using the open console, modular Hugo™ RAS System. Our findings offer recommendations for operating surgeons and allow for a comparative analysis between the different robotic systems. Further evaluations in real-time operative scenarios will follow.
RESUMEN
BACKGROUND: Robotic-assisted minimally invasive esophagectomy (RAMIE) was first introduced in 2003 and has since then shown to significantly improve the postoperative course. Previous studies have shown that a structured training pathway based on proficiency-based progression using individual skill levels as measures of reach of competence can enhance surgical performance. The aim of this study was to evaluate and help understand our pathway to reach surgical expert levels using a proficiency-based approach introducing RAMIE at our German high-volume center. METHODS: All patients undergoing RAMIE performed by two experienced surgeons for esophageal cancer since the introduction of the robotic technique in 2017 was included in this analysis. Intraoperative outcomes and postoperative outcomes were included in the analysis. The cumulative sum method was used to analyze how many cases are needed to reach expert levels for different performance characteristics and skill sets during robotic-assisted minimally invasive esophagectomy. RESULTS: From 06/2017 to 03/2022, a total of 154 patients underwent RAMIE at our facility and were included in the analysis. An advancement in performance level was observed for total operating time after 70 cases and for thoracic operative time after 79 cases. Lymph node yield showed an increase up until case 60 in the CUSUM analysis. Length of hospital stay stabilized after case 55. The CCI score inflection point was at case 55 in both CUSUM and regression analyses. Anastomotic leak rate stabilized at case 38 and showed another inflection point after case 83. CONCLUSION: Our data and analysis showed the progression from proficient to expert performance levels during the implementation of RAMIE at a European high-volume center. Further analysis of surgeons, especially with a different training status has yet to reveal if the caseloads found in this study are universally applicable. However, skill acquisition and respective measures of such are diverse and as a great range of number of cases was observed, we believe that the learning curve and ascent in performance levels cannot be defined by one parameter alone.