Abstract: |
BACKGROUND: Several studies have proposed regression equations that can increase the accuracy of predicting femur and tibia component sizes for total knee arthroplasty (TKA). This study compared available regression equations in their ability to prospectively predict component size in a unique patient series. METHODS: Demographic data and implanted femur and tibia TKA component sizes were collected on a consecutive 382 patients undergoing index TKA. Equations by Bhowmik-Stoker et al, Ren et al, Sershon et al, and Miller et al were identified that used age, race, ethnicity, gender, height, weight, or body mass index. Equation outputs were converted to implant-corrected sizes and compared to the implanted component. RESULTS: Femur and tibia sizes were accurately predicted within 1 size 88% and 92%, 84% and 86%, and 79% and 92% for Bhowmik-Stoker et al, Sershon et al, and Miller et al, respectively. Ren et al was within 1 tibia size 88% of the time. Adding one more common implant size improved this accuracy by an average of 9.1% and 6.6% for the femur and tibia, respectively. For femur components, Bhowmik-Stoker et al outperformed Sershon et al by 0.14 sizes (P .001) and Miller et al by 0.21 sizes (P .001) on average. For tibia components, Bhowmik-Stoker et al outperformed Sershon et al by 0.09 sizes (P = .028) and Ren et al by 0.11 sizes (P = .005) on average. CONCLUSION: Equations by Bhowmik-Stoker et al more accurately predicted implanted TKA size. In cases of greater uncertainty, the practicing surgeon may err on having more common TKA sizes available. |