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

preprint OA: closed CC-BY-4.0
📄 Open PDF View at publisher

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 (LC) 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 LC 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.

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-05-24T02:00:01.246996+00:00
License: CC-BY-4.0