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Published on: June 24, 2022
Systematic review and meta-analysis of difficulty scoring systems for laparoscopic and robotic liver resections
Yun-Le Linn1, Andrew G Wu2, Ho-Seong Han3
1Department of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital, Singapore City, Singapore.
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.
