Abstract

Several difficulty scoring systems (DSSs) have been proposed for evaluating difficulty of laparoscopic liver resection (LLR) and no study has validated their performance in a hepatocellular carcinoma (HCC)-only cohort at the same time. All cases with HCC that underwent LLR from January 2015 to December 2020 in our center were retrospectively collected. Performance of the IWATE-DSS, Halls-DSS, Hasegawa-DSS, and Kawaguchi-DSS in predicting perioperative outcomes was evaluated. Subgroup analyses were conducted to compare perioperative outcomes between surgeons on the learning curve and surgeons that have gone through the learning curve. For all four DSSs, there were significant distributions of applying bleeding control, surgical time, estimated blood loss, postoperative major complications, and postoperative hospital stay among different groups of each DSS (P all < 0.05). Conversion to laparotomy or not was significantly distributed in different groups of the IWATE-DSS (P = 0.006) and Halls-DSS (P = 0.022), while it was not in the Hasegawa-DSS (P = 0.056) and Kawaguchi-DSS (P = 0.183). Trend tests showed that the conversion rates increased with higher DSS points in the IWATE-DSS (P < 0.001) and the Kawaguchi-DSS (P = 0.021), while not in the Halls-DSS (P = 0.064) and the Hasegawa-DSS (P = 0.068). In the medium and advanced/expert difficulty-level subgroupsdefined by theIWATE-DSS, there were larger estimated blood loss (P in medium-difficulty group = 0.009; P in the advanced/expert difficulty group = 0.004) and longer postoperative hospital stay (P in the medium-difficulty group = 0.012; P in the advanced/expert group = 0.035) in the learner-performed cases. All DSSs performed well in predicting applying bleeding control, surgical time, estimated blood loss, postoperative major complications, and postoperative hospital stay, while only the IWATE-DSS was able to predict whether conversion to laparotomy or not for HCC patients underwent LLR. The IWATE-DSS was also able to help surgeons on the LLR learning curve choose cases and guide clinical practices.

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