Demographic-Based Algorithm Used to Predict the Implant Sizing in Total Knee Arthroplasty

Abstract

Abstract Background: Prediction of the accurate implant improves preparedness for surgery and helps to reduce intraoperative difficulties. Conventionally, the prediction of implant sizes by preoperative templating is improper owing to a variable degree of accuracy. We correlated patients’ demographic features of gender, weight, height, and body mass index (BMI) with the size of the implants used in total knee arthroplasty (TKA) so as to formulate an algorithm between the implant size and these parameters. Materials and Methods: Demographic variables from the records of all patients who underwent TKA of the same type were reviewed for gender, weight (in kg), and height (in cm). Intraoperatively, the size of femoral and tibial components was noted and correlated with the demographic variables, and linear regression was used to formulate an equation to predict the sizes depending on demographic variables. Results: Two hundred and three primary total knee replacements in 146 patients were included in the study. The mean age, weight, height, and BMI were 66.13 years (range: 46–89 years), 74.69 kg (range: 44–104 kg), 156.078 cm (range: 130–181 cm), and 30.796 kg/cm 2 (range: 18.59–49.88), respectively. The mean size of the femoral and tibial components used was 2.99 (range: 1–5) and 2.52 (range: 1–4), respectively. Both femoral and tibial components correlated significantly with gender, weight, and height only and not with BMI. Conclusion: Demographic profiles can predict the component size accurately, and it is a reliable, accurate, inexpensive, time-efficient, and safe means to predict the final implant size.