Systematic review and meta-analysis of difficulty scoring systems for laparoscopic and robotic liver resections

Introduction The ability to stratify the difficulty of minimally invasive liver resection (MILR) allows surgeons at different phases of the learning curve to tackle cases of appropriate difficulty safely. Several difficulty scoring systems (DSS) have been formulated which attempt to accurately stratify this difficulty. The present study aims to review the literature pertaining to the existing DSS for MILR. Methods We performed a systematic review and metanalysis of the literature reporting on the formulation, supporting data, and comparison of DSS for MILR. Results A total of 11 studies were identified which reported on the formulation of unique DSS for MILR. Five of these (Ban, Iwate, Hasegawa, Institut Mutaliste Montsouris [IMM], and Southampton DSS) were externally validated and shown to predict difficulty of MILR via a range of outcome measures. The Ban DSS was supported by pooled data from 10 studies (9 LLR, 1 RLR), Iwate by 10 studies (8 LLR, 2 RLR), Hasegawa by four studies (all LLR), IMM by eight studies (all LLR), and Southampton by five studies (all LLR). There was no clear superior DSS. Conclusion The existing DSS were all effective in predicting difficulty of MILR. Present studies comparing between DSS have not established a clear superior system, and the five main DSS have been found to be predictive of difficulty in LLR and two of these in RLR.

Automated summary

This study reviewed the literature on difficulty scoring systems (DSS) for minimally invasive liver resection (MILR) and found that existing DSS are effective in predicting the difficulty of the surgery.