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DOI: 10.1055/s-0040-1701455
Robotic-Assisted versus Manual Unicompartmental Knee Arthroplasty: Contemporary Systematic Review and Meta-analysis of Early Functional Outcomes
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Abstract
Robotic-assisted unicompartmental knee arthroplasty (RA-UKA) aims to improve accuracy of component placement. Studies have shown improvement in radiographic positioning/alignment with RA-UKA but have not addressed clinical outcome measures (COMs). The purpose of this study was to determine if RA-UKA is associated with improved early revision rates and functional outcome scores (FOS) compared with manual UKA. A systematic review of all English language articles from 1999 to 2019 on RA-UKA using Medline, EMBASE, Scopus, and Web of Science databases identified 277 studies. Seven (three randomized controlled trials) met inclusion criteria. Revision rates/FOS were aggregated for RA-UKA and manual UKA; a forest plot was constructed utilizing inverse variance/Mantel–Haenszel fixed-effects meta-analysis. The seven articles included a total of 363 RA-UKA patients and 425 manual UKA patients. Mean age was 66 ± 3.5 and 65 ± 4.0 years, and mean body mass index (BMI) was 26.8 ± 2.1 and 27.1 ± 1.5 kg/m2, respectively. Mean follow-up was 25.5 months (4.5–48) and 29.1 months (4.5–48) for RA-UKA and manual UKA, respectively. At latest follow-up, RA-UKA patients showed a 26% ± 12 improvement in COMs versus 24% ± 12 improvement for manual UKA patients (p = 0.6). The revision rate was 3% for both groups (p = 0.8); however, a meta-analysis of RCTs showed no difference. Robotic and manual UKAs offer comparable improvements in pain, FOS, and revision rates. The effects of follow-up duration, ceiling effects of COMs, and surgeon experience remain unknown. Future studies comparing robotic versus manual UKAs with longer term follow-up may inform further benefits of each, with respect to component durability, alignment, and functional improvement.
Keywords
robotic assisted - unicompartmental knee arthroplasty - clinical outcomes - manual outcomes - meta-analysisPublikationsverlauf
Eingereicht: 14. September 2019
Angenommen: 13. Dezember 2019
Artikel online veröffentlicht:
30. Januar 2020
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