PAEDIATRIC ROBOTIC SURGERY: LESSONS LEARNED AND FUTURE PERSPECTIVES AFTER 10 YEARS

Aim of the study: Providing insights into future perspectives for robotic pediatric surgery while reporting the experience of a single center, considering the main demographic and intraoperative data, as well as short- and long-term outcomes. Furthermore, evaluating the difference in learning curve between younger and older surgeons was performed, together with comparison of outcomes between surgeries performed using da Vinci  Xi versus da Vinci Si model were secondary focuses. Methods: A retrospective single center study was performed, which included 73 robot assisted surgeries performed in period of February 2014 – May 2024 on infants, children, and adolescents under the age of 18. Results: Average age of patients was 10.1 years (+/- 4.5), average weight 39.4 kg(+/-21.8), average height 136.3 cm (+/- 29.2). 35 surgeries were performed in urological area, 20 in gastrointestinal, 17 in gynecological and 2 in thoracic area. Rate of complications was low for both early (15%, all Clavien Dindo grade I) and late (1.4%, Clavien Dindo grade 3b) complications. Intraoperative times were on average 157.1 minutes (+/- 73.2). None of the patients required a redo surgery. Surgeries performed using da Vinci  Xi model had shorter operative times, lower rate of conversion (9.3% versus 2.4%) and lower rate of complications (14.6% versus 15.6% for early and 3.1% versus 0% for late complications). Younger surgeon group had shorter average operative times among all districts: 97.5 versus 205.8 minutes for gastrointestinal area, 183.5 versus 209.3 for urological area, 81.7 versus 99.7 for gynecological area. Conclusions: Da Vinci system can safely be used in young and older children with successful outcomes for different districts: urology, abdominal surgery, gynecology. Thoracic surgery has not been as successful. Da Vinci Xi model has shown as superior compared to Si model for application in pediatric surgery. Younger surgeons seem to have a faster learning curve compared to their older colleagues.