Dynamic sensor-balanced knee arthroplasty: can the sensor “train” the surgeon?

• Published in: Arthroplasty today Vol. 5; no. 2; pp. 202 - 210
• Main Authors: Woon, Colin Y.L., Carroll, Kaitlin M., Lyman, Stephen, Mayman, David J.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.06.2019; Elsevier
• Subjects: Computer-assisted surgery; Dynamic sensor; Navigation; Original Research; Total knee arthroplasty; Total knee arthroplasty; Navigation; Dynamic sensor; Computer-assisted surgery
• ISSN: 2352-3441; 2352-3441
• DOI: 10.1016/j.artd.2019.03.001

Dynamic tibial tray sensors are playing an increasing role in total knee arthroplasty (TKA) coronal balancing. Sensor balance is proposed to lead to improved patient outcomes compared with sensor-unbalanced TKA, and traditional manual-balanced TKA. However, the “learning curve” of this technology is not known, and also whether sensor use can improve manual TKA balance skills once the sensor is taken away, effectively “training” the surgeon. We conducted a single-surgeon prospective study on 104 consecutive TKAs. In Nonblinded Phase I (n = 49), sensor-directed releases were performed during trialing and final intercompartmental load was recorded. In Blinded Phase II (n = 55), manual-balanced TKA was performed and final sensor readings were recorded by a blinded observer after cementation. We used cumulative summation analysis and sequential probability ratio testing to analyze the surgeon learning curve in both phases. In Nonblinded Phase I, sensor balance proficiency was attained most easily at 10°, followed by 90°, and most difficult to attain at 45° of flexion. In Blinded Phase II, manual balance was lost most quickly at 45°, followed by 90°, and preserved for longest at 10° of flexion. The number of cases in the steady state periods (early phase periods where there is a mix of sensor balance and sensor imbalance) for both phases is similar. A surgeon who consistently uses the dynamic sensor demonstrates a learning curve with its use, and an “attrition” curve once it is removed. Consistent sensor balance is more predictable with constant sensor use.