Demographic data is more predictive of component size than digital radiographic templating in total knee arthroplasty

Abstract

Background Preoperative radiographic templating for total knee arthroplasty (TKA) has been shown to be inaccurate. Patient demographic data, such as gender, height, weight, age, and race, may be more predictive of implanted component size in TKA. Materials and methods A multivariate linear regression model was designed to predict implanted femoral and tibial component size using demographic data along a consecutive series of 201 patients undergoing index TKA. Traditional, two-dimensional, radiographic templating was compared to demographic-based regression predictions on a prospective 181 consecutive patients undergoing index TKA in their ability to accurately predict intraoperative implanted sizes. Surgeons were blinded of any predictions. Results Patient gender, height, weight, age, and ethnicity/race were predictive of implanted TKA component size. The regression model more accurately predicted implanted component size compared to radiographically templated sizes for both the femoral (P = 0.04) and tibial (P < 0.01) components. The regression model exactly predicted femoral and tibial component sizes in 43.7 and 43.7% of cases, was within one size 90.1 and 95.6% of the time, and was within two sizes in every case. Radiographic templating exactly predicted 35.4 and 36.5% of cases, was within one size 86.2 and 85.1% of the time, and varied up to four sizes for both the femoral and tibial components. The regression model averaged within 0.66 and 0.61 sizes, versus 0.81 and 0.81 sizes for radiographic templating for femoral and tibial components. Conclusions A demographic-based regression model was created based on patient-specific demographic data to predict femoral and tibial TKA component sizes. In a prospective patient series, the regression model more accurately and precisely predicted implanted component sizes compared to radiographic templating. Level of evidence Prospective cohort, level II.

Artificial Intelligence Based Patient-Specific Preoperative Planning Algorithm for Total Knee Arthroplasty

“…For the tibial implant size, elastic net penalized linear regression was optimal with 43.8% accuracy. Wallace et al’s study found similar results for predicting TKA intraoperative implant sizes based on demographic data ( Wallace et al, 2020 ). Using linear regression based on patient age, gender, height, weight, and race the predicted component sizes with accuracy of 43.7% for femoral and 43.7% for tibial implant size.…”

Artificial intelligence in knee arthroplasty: current concept of the available clinical applications

“…[ 23 ] 2021 VR and AR training in knee arthroplasty Preop Review Few assessments of VR training but promising P reoperative planning Wallace et al . [ 24 ] 382 2020 PM Implant Size Preop Component size prediction Sex, height, weight, age, and ethnicity More accurate than radiographic templating Kunze et al . [ 25 ] 17,283 2021 PM Implant size Preop Component size prediction Demographic variables (age, height, weight, BMI, sex) Good to excellent performance for predicting TKA component Size.…”

“…Still, the limited predictive factors and limited size of certain products are the drawbacks [ 39 – 41 ]. Demographic-based multivariate linear regression models can be used to predict more accurate implant size than digitally-templated sizes for femoral ( P = 0.04) and tibial ( P < 0.01) components [ 24 ]. The regression models are created using the stochastic gradient boosting model, allowing users to input data and receive individualized sizing predictions and explanations [ 25 ].…”

Magnification assessment of radiographs for knee replacement (MARKeR) – A pilot study in a low-resource setting

“…Templating is an important exercise in preoperative planning for total knee arthroplasty (TKA), which has clinical, logistical and economic benefits. 1,2 Preoperative templating allows surgeons to choose the most appropriate size of implant that would restore alignment and stability of the knee, resulting in better functional outcomes. 1-3 Templating also facilitates improved theatre efficiency and lower cost; by identifying the implant sizes preoperatively, the correct sizes can be ordered in advance reducing cancellations and intraoperative delays.…”

“…To address this issue, several studies have investigated the use of patient demographics to predict TKA implant size, reporting accuracy within one size in 85–100% of cases. 1,5-7 In spite of its accuracy, surgeons are generally more comfortable viewing radiographs when templating, which allows them to analyse bone loss and deformity.…”