Our Initial Experience of First 50 Cases of Robotic-Arm-Assisted Total Knee Arthroplasty
Journal of Clinical Orthopaedics | Vol 9 | Issue 2 | July-December 2024 | page: 47-51 | Chandan Mehta, Mohan Madhav Desai, Swapnil Chitnavis, Kushagra Jain, Urvil Shah
DOI: https://doi.org/10.13107/jcorth.2024.v09i02.662
Submitted Date: 09 Aug 2024, Review Date: 26 Aug 2024, Accepted Date: 17 Sep 2024 & Published Date: 10 Dec 2024
Author: Chandan Mehta [1], Mohan Madhav Desai [1], Swapnil Chitnavis [1], Kushagra Jain [1], Urvil Shah [1]
[1] Department of Orthopaedics, Seth GS Medical College and KEM Hospital, Mumbai, Maharashtra, India
Address of Correspondence
Dr. Chandan Mehta,
Department of Orthopaedics, Seth GS Medical College and KEM Hospital, Mumbai, Maharashtra, India.
E-mail: drchandanmehta01@gmail.com
Abstract
Purpose: Robotic-arm-assisted total knee arthroplasty (RA-TKA) has been criticized for an increased operative time, longer incision, the extra incision for insertion of pins and various other potential complications. We want to describe our initial experience of the first 50 cases of RA-TKA (of fully automatic robot) regarding the learning curve for operative time, accuracy of implant positioning, and the accuracy of achieving a well-balanced knee through the assessment of gaps.
Materials and Methods: Retrospective analysis of the first 50 patients was done who underwent RA-TKA, all of which were performed by a senior surgeon experienced in conventional manual jig-based TKA. Operative time, accuracy of implant positing, restoration of limb alignment, and intraoperative gap balancing were assessed. Linear regression analysis and cumulative sum (CUSUM) sequential analysis were used to assess the learning curve for the operative time.
Results: In our experience, the learning curve for operative time in RA-TKA is around 25 cases as per CUSUM sequential analysis. The linear regression analysis showed a gradual decrease in the operative time as the number of RA-TKA performed cases increased (cases 1–10 = 76.8 ± 16 min, cases 11–20 = 72.5 ± 13 min, cases 21–30 = 63.6 ± 7 min, cases 31–40 = 61.3 ± 6 min, and cases 41–50 = 57.3 ± 10 min) – statically significant (P < 0.05) after 20 cases. There is no learning curve for the accuracy of achieving the planned implant position (P = n.s.) and limb alignment (P = n.s.). Only three cases were outliers, HKA angle <174° for varus phenotype, and HKA >183° for valgus phenotype. Forty-six cases (out of 50) had all the gaps within 3 mm of each other (sensitivity of the robot is <1 mm).
Conclusion: Implementation of RA-TKA into the surgical workflow is associated with a learning curve for the operative times, which eventually decreases but this does not lead to any compromise in the accuracy of implant positioning or overall limb alignment. The RA-TKA has shown improved accuracy in implant positioning, improved limb alignment, thereby reducing outliers, and improved gap balancing. All this translates to better clinical outcomes and patient satisfaction.
Keywords: Robotic arm assisted Total Knee Arthroplasty, Learning Curve, Operative time, Implant Positioning, Gap Balancing
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| How to Cite this article: Mehta C, Desai MM, Chitnavis S, Jain K, Shah U. Our Initial Experience of First 50 Cases of Robotic-Arm Assisted Total Knee Arthroplasty. Journal of Clinical Orthopaedics July-December 2024;9(2):47-51. |
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