Gavin J. Macpherson

Edinburgh Royal Infirmary

Papers

5

Total Citations

557

H-Index

5

About

Gavin J. Macpherson is a leading orthopaedic surgery researcher whose work has significantly advanced the understanding and adoption of robotic-assisted joint replacement surgery. His research primarily focuses on total knee arthroplasty, total hip arthroplasty, and unicompartmental knee arthroplasty, with a particular emphasis on comparing robotic-arm assisted techniques against conventional manual approaches. Macpherson's most influential contribution is his 2021 systematic review and meta-analysis on robotic-arm assisted total knee arthroplasty, which has accumulated an impressive 258 citations, establishing it as a landmark reference in the field. This work, alongside his parallel investigations into robotic hip and unicompartmental knee procedures, demonstrates a comprehensive and systematic approach to evaluating how emerging surgical technologies improve component positioning accuracy, patient-reported outcomes, and reduce complications. His research has been instrumental in quantifying the real-world benefits of robotic surgical systems, including the MAKO platform, and in characterizing the learning curves surgeons face when adopting these technologies. With a combined citation count exceeding 550 across his key publications, Macpherson's scholarship provides evidence-based guidance that directly influences surgical decision-making and helps clinicians and patients better understand the potential advantages of robotic-assisted orthopaedic procedures.

Research Focus

Key Achievements

5
H-Index
5
Papers
557
Total Citations
111
Avg Citations/Paper
🏆 Most Cited Paper
Robotic‐arm assisted total knee arthroplasty is associated with improved accuracy and patient reported outcomes: a systematic review and meta‐analysis
258 citations · 2021
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Edinburgh Royal Infirmary

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago