Robotic-assisted unicompartmental knee replacement offers no early advantage over conventional unicompartmental knee replacement View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-02-12

AUTHORS

Jason Wong, Taylor Murtaugh, Akshay Lakra, H. John Cooper, Roshan P. Shah, Jeffrey A. Geller

ABSTRACT

PURPOSE: Unicompartmental knee arthroplasty (UKA) is effective for treating degenerative joint disease in a single compartment. Robotic-arm-assisted arthroplasty (RAA) has gained popularity and has theoretical benefits of improved outcomes over conventional (CONV) UKA due to the technical precision of bone preparation. This study compares the short-term clinical outcomes, including survivorship and patient-reported functional outcomes, for a series of medial UKAs performed with RAA and CONV. METHODS: One hundred seventy-six consecutive fixed-bearing medial UKAs were retrospectively identified with a minimum follow-up of 2 years. One hundred and eighteen CONV and 58 RAA were performed. Pre- and post-operative SF12, WOMAC, and KSS Functional Questionnaires were available for all patients. RESULTS: At 2 years, both groups improved in all functional outcomes, with no significant difference between the RAA and CONV cohorts. However, the RAA cohort had a significantly longer operative time (p < 0.001) and a higher early revision rate than the CONV group (7 [12.0%] vs. 7 [6.8%]; p < 0.05). CONCLUSIONS: These results demonstrate that at short-term follow-up of 2 years, RAA was not superior to CONV in terms of functional scores and instead was associated with greater operative time and cost and lower survivorship. Therefore, at this time usage of RAA in UKA is not recommended compared to conventional UKA. Longer term studies are necessary to draw conclusions about the overall outcomes of RAA compared to CONV. LEVEL OF EVIDENCE: III. More... »

PAGES

1-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00167-019-05386-6

DOI

http://dx.doi.org/10.1007/s00167-019-05386-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112073867

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30747237


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