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Image-based robot assisted bicompartmental knee arthroplasty versus total knee arthroplasty

Publication Type : Journal Article

Publisher : National Library of Medicine

Source : National Centre for biotechnology information

Url :

Campus : Kochi

School : School of Medicine

Department : Orthopaedics

Year : 2022

Abstract :

Objective: To evaluate the short-term clinical outcomes of image-based robot-assisted bicruciate retaining bicompartmental knee arthroplasty and compare it to robot-assisted total knee arthroplasty in the Indian population.

Methods: Between December 2018 and November 2019, five patients (six knees) underwent robot-assisted bicompartmental knee arthroplasty (BCKA). These patients were demographically matched with five patients (six knees) who underwent robot-assisted total knee arthroplasty (TKA) during the same period. Clinical outcomes of these twelve knees were assessed in the form of knee society score (KSS) score, Oxford knee score (OKS), and forgotten joint score (FJS) after a minimum follow-up period of 25 months. The data between the two cohorts were compared and analyzed.

Results: Scores obtained from both cohorts were subjected to statistical analysis. SPSS software was utilized and the Mann Whitney U-test was utilized to compare the two groups. There was no statistically significant difference found between the two groups in terms of functional outcome.

Conclusion: Image-based robot-assisted BCKA is a bone stock preserving and more physiological procedure which can be a promising alternative to patients presenting with isolated arthritis of only two compartments of the knee. Although long-term, larger trials are warranted to establish it as an alternative, our pilot study shows an equally favorable outcome as TKA, making it an exciting new avenue in the field of arthroplasty.

Cite this Research Publication : Thilak J, Nagaraja Rao S, Mohan V, Babu BC. Image-based robot assisted bicompartmental knee arthroplasty versus total knee arthroplasty. SICOT J. 2022;8:48. doi: 10.1051/sicotj/2022048. Epub 2022 Dec 16. PMID: 36648272.

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