Concomitant training in robotic and laparoscopic liver resections of low-to-intermediate difficulty score: a retrospective analysis of the learning curve

Sci Rep. 2024 Feb 13;14(1):3595. doi: 10.1038/s41598-024-54253-z.

Abstract

In the setting of minimally invasive liver surgery (MILS), training in robotic liver resections (RLR) usually follows previous experience in laparoscopic liver resections (LLR). The aim of our study was to assess the learning curve of RLR in case of concomitant training with LLR. We analyzed consecutive RLRs and LLRs by a surgeon trained simultaneously in both techniques (Surg1); while a second surgeon trained only in LLRs was used as control (Surg2). A regression model was used to adjust for confounders and a Cumulative Sum (CUSUM) analysis was carried out to assess the learning phases according to operative time and difficulty of the procedures (IWATE score). Two-hundred-forty-five procedures were identified (RobSurg1, n = 75, LapSurg1, n = 102, LapSurg2, n = 68). Mean IWATE was 4.0, 4.3 and 5.8 (p < 0.001) in each group. The CUSUM analysis of the adjusted operative times estimated the learning phase in 40 cases (RobSurg1), 40 cases (LapSurg1), 48 cases (LapSurg2); for IWATE score it was 38 cases (RobSurg1), 33 cases (LapSurg1), 38 cases (LapSurg2) respectively. Our preliminary experience showed a similar learning curve of 40 cases for low and intermediate difficulty RLR and LLR. Concomitant training in both techniques was safe and may be a practical option for starting a MILS program.

MeSH terms

  • Hepatectomy / methods
  • Humans
  • Laparoscopy* / methods
  • Learning Curve
  • Liver
  • Operative Time
  • Retrospective Studies
  • Robotic Surgical Procedures* / methods