[Robotic knee arthroplasty-an evidence-based, narrative assessment of the current state]

Robotically assisted knee arthroplasty (r-CAS) enables highly precise implant placement. However, current evidence shows no consistent advantage in clinical outcomes or implant survivorship. Scientific evaluation is challenged by both the technical heterogeneity of robotic systems and the rapid evolution of software, including AI-driven optimization algorithms. These differences affect workflow, accuracy, and outcomes, limiting study comparability.

Future value will likely lie less in further improving precision and more in enabling personalized treatment through integration of kinematic analysis and intelligent decision-support models. This will require not only advanced hardware, software, and algorithms, but also new dynamic real-world evidence approaches to assess patient benefit.The present article provides an overview of the current state of evidence-based research for r-CAS and discusses approaches for bringing rapid technological advancements into balance with valid, patient-centered research in the future.