Learning Curve of Laparoscopic Liver Resection: Experience with the First 150 Cases of a Self-Taught Pioneer Surgeon

Ramiro Arrechea, Lucia Aragone, Federico Yael Veracierto, Rafael Maurette, Daniel Pirchi
2023 · doi:10.21203/rs.3.rs-3672572/v1
preprint OA: closed CC-BY-4.0
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Abstract

BACKROUND: The learning curve (LC) of laparoscopic liver resection (LLR) can be long, depending on the patient, tumor features, and surgeon training. Our aim was to evaluate LC in LLR performed by a self-taught "pioneer" surgeon and to analyze its evolution. METHODS: A retrospective analysis was conducted between December 2008 and February 2023.The series was divided chronologically into three equal groups. LC was evaluated by analyzing the surgical difficulty according to the IWATE criteria and intra- and postoperative results. RESULTS: 150 patients underwent LLR, which were divided into 3 periods. A significant increase in the difficulty of cases was observed, as reflected in the mean IWATE (p=0.00001). Conversion rate (p=0.117), "hand-assisted" resection rate (p=0.004), and median time adjusted by the number of resections (p=0.705) decreased. The number of resections per case (p=0.017) and mean blood loss (p=0.465) increased. Finally, there was a significant reduction in postoperative complications (p=0.024) and mean length of hospital stay (p=0.005). DISCUSION: This study confirmed an improvement in LC after LLR. Although there was no significant reduction in the mean blood loss rate and mean surgical time, this may be a consequence of selecting more difficult cases and increasing the number of resections per case.

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License: CC-BY-4.0