Abstract / Summary
Abstract Training in minimally invasive liver surgery (MILS) usually encompasses prior laparoscopic liver resection (LLR) experience before moving to robotic liver resections (RLR). We analyzed the risk-adjusted learning curve of MILS within the transition from LLR to RLR. Consecutive LLR and RLR from a surgeon trained sequentially in the two techniques were reviewed. Multiple regression analysis was used to adjust for patient- and hepatectomy-related confounders. The cumulative sum (CUSUM) analysis of the risk-adjusted operative time, blood loss, and comprehensive complication index (CCI) was used to estimate the learning curves based on competency, proficiency and mastery phases. One-hundred-ninety-seven consecutive MILS were reviewed (LLR = 97; RLR = 100). The first RLR was case 74, after which the use of LLR decreased sharply. A steady improvement of adjusted operative time and blood loss continued while introducing RLR. For the whole body of MILS, competency was obtained after 90 and 111 cases based on the adjusted operative time and blood loss respectively, proficiency followed after a similar number of cases. The separate analysis of LLR and RLR showed earlier phase transition for RLR: adjusted operative time and blood loss dropped after 38 and 45 LLRs, while they improved earlier after 19 and 29 RLRs. Risk-adjusted CCI improved later in the mastery phase in both groups. A shorter learning curve was observed for RLR following prior LLR experience. Risk-adjusted improvements occurred earlier in operative time (after 38 LLR vs. 19 RLR) and blood loss (45 LLR vs. 29 RLR) than for postoperative morbidity. Careful stepwise introduction of RLR did not deteriorate the surgical performance while transitioning from LLR to RLR.