Total knee arthroplasty component templating: a predictive model

Abstract

Preoperative planning is essential to total knee arthroplasty (TKA); however, TKA templating is historically inaccurate. To improve on templating accuracy and streamline preoperative planning, we set out to predict component sizes based on patient characteristics without radiographs. A total of 123 consecutive patients undergoing unilateral TKA were identified and included in the model study. Input variables consisted of age, gender (as a binary number), height, weight, and body mass index. A linear regression model was created. The models predicted component size exactly in 74% of femurs and 85% of tibias. All model predictions were within a ±1 size of the actual components implanted. Our models were more accurate than any previous model for TKA reported.