ISAKOS: 2019 Congress in Cancun, Mexico
ISAKOS

2019 ISAKOS Biennial Congress ePoster #930

 

Robotic-Arm Assisted Total Knee Arthroplasty Has a Learning Curve of Seven Cases for Integration Into the Surgical Workflow but No Learning Curve Effect for Accuracy of Implant Positioning

Babar Kayani, BSc (HONS), MBBS, MRCS (Eng), London UNITED KINGDOM
Sujith Konan, MD(Res), MBBS, MRCS, FRCS(Tr&Orth), London UNITED KINGDOM
Sumon S. Huq, MBBS, MRCS, London UNITED KINGDOM
Jenni Tahmassebi, BSc, London UNITED KINGDOM
Fares S. Haddad, MCh(Orth), BSc, FRCS(Orth), London UNITED KINGDOM

University College London Hospital, London, UNITED KINGDOM

FDA Status Cleared

Summary

Implementation of robotic-arm assisted TKA led to increased operative times and heightened levels of anxiety amongst the surgical team for the initial seven cases but there was no learning curve for achieving the planned implant positioning.

Abstract

Purpose

The primary objective of this study was to determine the surgical team’s learning curve for robotic-arm assisted TKA through assessments of operative times, surgical team comfort levels, accuracy of implant positioning, limb alignment, and postoperative complications. Secondary objectives were to compare accuracy of implant positioning and limb alignment in conventional jig-based TKA versus robotic-arm assisted TKA.

Methods

This prospective cohort study included 60 consecutive conventional jig-based TKAs followed by 60 consecutive robotic-arm assisted TKAs performed by a single surgeon. Independent observers recorded surrogate markers of the learning curve including operative times, stress levels amongst the surgical team using the state-trait anxiety inventory (STAI) questionnaire, accuracy of implant positioning, limb alignment, and complications within 30 days of surgery. Cumulative summation (CUSUM) analyses were used to assess learning curves for operative time and STAI scores in robotic TKA. Root mean square error values were calculated for accuracy of implant positioning and limb alignment in both treatment groups. Normally distributed continuous variables were compared using independent t-tests for unpaired variables, paired t-test for paired outcomes, and one-way ANOVA for multiple variables. The Mann-Whitney test was used for non-parametric data. Categorical data was compared using the chi-squared test and Fisher’s exact test.

Results

Robotic-arm assisted TKA was associated with a learning curve of seven cases for operative times (p=0.01) and surgical team anxiety levels (p=0.02). Cumulative robotic experience did not affect accuracy of implant positioning (p=0.90), limb alignment (p=0.61), posterior condylar offset ratio (p=0.87), posterior tibial slope (p=0.79), and joint line restoration (p=0.76). Robotic TKA improved accuracy of implant positioning (p<0.001) and limb alignment (p<0.001) with no additional risk of postoperative complications compared to conventional manual TKA.

Conclusion

Implementation of robotic-arm assisted TKA led to increased operative times and heightened levels of anxiety amongst the surgical team for the initial seven cases but there was no learning curve for achieving the planned implant positioning. Robotic-arm assisted TKA improved accuracy of implant positioning and limb alignment compared to conventional jig-based TKA.