Predictive Gap-balancing Reduces the Extent of Soft-tissue Adjustment Required After Bony Resection in Robot-assisted Total Knee Arthroplasty—A Comparison With Simulated Measured Resection

Abstract

Background: To understand the extent and frequency of soft-tissue adjustment required to achieve mediolateral (ML) balance in measured resection (MR) vs gap-balancing (GB) total knee arthroplasty, this study compared ML balance and joint laxity throughout flexion between the 2 techniques. The precision of predictive GB in achieving ML balance and laxity was also assessed. Methods: Two surgeons performed 95 robot-assisted GB total knee arthroplasties with predictive balancing, limiting tibial varus to 3° and adjusting femoral positioning to optimize balance. A robotic ligament tensioner measured joint laxity. Planned MR (pMR) was simulated by applying neutral tibial and femoral coronal resections and 3° of external femoral rotation. ML balance, laxity, component alignment, and resection depths were compared between planned GB (pGB) and pMR. ML balance and laxity were compared between pGB and final GB (fGB). Results: The proportion of knees with >2 mm of ML imbalance in flexion or extension ranged from 3% to 18% for pGB vs 50% to 53% for pMR (P 3 mm ranged from 0% to 9% for pGB and 30% to 38% for MR (P 3 mm in 30% of knees. GB planning improved ML balance throughout flexion but increased femoral posterior rotation variability and bone resection compared to MR. fGB laxity was likely not clinically significantly different than pGB.

Keywords

• Gap balancing
• Laxity
• Measured resection
• Total knee arthroplasty
• Computer-assisted
• Robotic-assisted