Open AccessThe learning curve in robotic assisted knee arthroplasty is flattened by the presence of a surgeon experienced with robotic assisted surgery
Author(s) -
Schopper Clemens,
Proier Philipp,
Luger Matthias,
Gotterbarm Tobias,
Klasan Antonio
Publication year - 2023
Publication title -
knee surgery, sports traumatology, arthroscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.806
H-Index - 125
eISSN - 1433-7347
pISSN - 0942-2056
DOI - 10.1007/s00167-022-07048-6
Subject(s) - cusum , learning curve , unicompartmental knee arthroplasty , inflection point , medicine , arthroplasty , surgery , general surgery , osteoarthritis , operations management , computer science , engineering , mathematics , alternative medicine , geometry , pathology , operating system
Purpose The purpose of this study was to investigate the learning curve associated with robotic assisted knee arthroplasty (RAS KA). Therefore, the evaluation of the influence of an experienced surgeon on the overall team performance of three surgeons regarding the learning curve in RAS KA was investigated. It was hypothesized that the presence of an experienced surgeon flattens the learning curve and that there was no inflection point for the learning curve of the surgical team. Methods Fifty‐five cases consisting of 31 total knee arthroplasties (TKA) and 24 unicompartmental arthroplasties (UKA) performed by three surgeons during 2021 were prospectively investigated. Single surgeon and team performance for operation time learning curve and inflection points were investigated using cumulative sum analysis (CUSUM). Results A downward trend line for individual surgeons and the team performance regarding the operation time learning curve was observed. No inflexion point was observed for the overall team performance regarding TKA and UKA. The surgeon that performed all cases with the assistance of the experienced surgeon had significantly shorter surgical times than the surgeon that only occasionally received assistance from the experienced surgeon ( p = 0.004 TKA; p = 0.002 UKA). Conclusion The presence of an experienced surgeon in robotically assisted knee arthroplasty can flatten the learning curve of the surgical team formerly unexperienced in robotic assisted systems. Manufacturers should provide expanded support during initial cases in centres without previous experience to robotic assisted knee arthroplasty. Level of evidence III.