Patient-Specific Instruments’ Effects on TKA Revision
Whenever we introduce new technology or techniques in hopes of improving orthopaedic surgery, at least one of two criteria should be met: The new technology should improve the outcome at a maintained cost, or it should decrease cost while maintaining at least an equivalent outcome. If neither of these conditions is met, we need to think twice about adopting it. To help us answer these “value” questions, we need relevant data. This is why studies such as the one by McAuliffe et al. in the April 3, 2019 issue of The Journal are so important.
The authors use the Australian Orthopaedic Association National Joint Replacement Registry to compare the rate of revision between 3 types of primary total knee arthroplasty (TKA):
- Those performed with image-derived instrumentation (IDI, i.e., patient-specific cutting jigs)
- Those performed using computer navigation
- Those using neither technology
McAuliffe et al. found no significant differences between groups in terms of cumulative percent revision at 5 years. Subgroup analysis revealed a higher rate of revision (hazard ratio [HR] 1.52, p = 0.01) for the IDI group relative to the computer-navigated group when patients were ≤65 years old. In addition, the IDI group had a much higher rate of patellar revision when patients received posterior-stabilized knees (HR of 5.33 when compared with the computer-navigated group, and HR of 4.16 when compared with the neither-technology group).
This study seems to suggest that whatever the benefits of IDI may be in terms of attaining a “proper” mechanical axis during TKA, IDI does not translate into a lower revision rate. And when these revision data are viewed in the face of the added costs associated with IDI, it makes little sense to advocate for the widespread use of this technology for TKA at this time.
While this study focused on TKAs, the take-home message can be extended. Orthopaedic surgery is by nature complex, requiring that multiple steps be performed in harmony to produce an optimal outcome. It is easy for us to focus on (and measure) a couple of key outcome variables and base our opinions of a technique’s or technology’s success on such findings. But when it comes to “novel” techniques and technological “breakthroughs,“ we need a lot of data on many different variables before we can make meaningful conclusions, change our practice, and advise our patients.
Chad A. Krueger, MD
JBJS Deputy Editor for Social Media