Chang Hyun Nam

Himchan Hospital

Papers

7

Total Citations

77

H-Index

4

About

Chang Hyun Nam is an orthopedic surgeon and researcher whose work is focused on advancing the precision and safety of total knee arthroplasty (TKA), with a particular emphasis on robotic-assisted surgical techniques. His research has made meaningful contributions to understanding how robot-assisted TKA improves mechanical alignment and component positioning compared to conventional approaches — findings documented in his most-cited work, which has accumulated 44 citations since its 2022 publication and provided compelling clinical evidence favoring robotic systems. A distinctive thread running through Nam's portfolio is his meticulous attention to surgical safety, particularly the problem of pin tracker placement during robotic TKA. His multi-year investigations into distal femoral tracker pin positioning demonstrated that strategic placement can prevent pin tract-induced fractures, a complication with serious consequences for patients. His work has also expanded the application of robotic TKA into challenging clinical scenarios, including patients with retained hardware, failed high tibial osteotomy, and post-traumatic extra-articular deformities — populations for whom conventional techniques carry elevated risk. With a cumulative citation count approaching 80 across his key publications, Nam's research is shaping evolving best practices in reconstructive knee surgery, offering clinicians evidence-based guidance for optimizing both outcomes and patient safety in the robotic era.

Research Focus

Key Achievements

4
H-Index
7
Papers
77
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Robot‐assisted total knee arthroplasty improves mechanical alignment and accuracy of component positioning compared to the conventional technique
44 citations · 2022
📈 Most Prolific Year: 2022 (4 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Himchan Hospital

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago