Assessment of knee kinematics during robotic-assisted total knee arthroplasty: Description of a new method and reliability analysis.

BACKGROUND

Altered knee kinematics following total knee arthroplasty (TKA) are thought to contribute to patient dissatisfaction and inferior functional outcomes. While multiple methods have been used to study knee kinematics, reliable and reproducible intraoperative assessment remains challenging. This study aimed to describe a novel intraoperative method for assessing knee kinematics during robotic-assisted TKA and to examine the reliability of this new method.

METHODS

Following ethical approval, 30 patients undergoing robotic-assisted TKA using the MAKO system with a cruciate-retaining implant were prospectively enrolled. Sequential intraoperative screenshots were captured through a standardized passive range of motion. Femoro-tibial contact points on the medial and lateral compartments were measured postoperatively using a predefined reference method. Measurements were performed independently by two assessors to determine inter-rater reliability, and repeated measurements by a blinded assessor were used to assess intra-rater reliability. Additionally, screenshots were recorded independently by two surgeons to evaluate inter-surgeon reliability. Reliability was assessed using correlation coefficients.

RESULTS

The method demonstrated excellent reliability. Inter-rater reliability of the screenshot measurements showed correlation coefficients ranging from 0.992 to 0.994. Intra-rater reliability was similarly high, with correlation coefficients ranging from 0.996 to 0.998 across repeated measurements. When assessing inter-surgeon reliability of the screenshot recordings, a correlation coefficient of 0.942 was obtained, indicating excellent agreement. No differences were observed in the overall knee motion pattern when comparing screenshots acquired by different surgeons.

CONCLUSION

This study describes a simple, reproducible, and highly reliable method for intraoperative assessment of knee kinematics during robotic-assisted TKA using the MAKO platform. The technique demonstrated excellent inter-rater, intra-rater, and inter-surgeon reliability without requiring additional hardware or operative time. This approach may facilitate real-time intraoperative kinematic assessment and support future efforts to better restore physiological knee kinematics in total knee arthroplasty.